graph-data.js

const GRAPH_DATA = {

  meta: {
    title: "ML & AI Knowledge Graph",
    subtitle: "by Sajil C. K. — Machine Learning Malayalam",
    channelUrl: "https://www.youtube.com/@sajil36",
    githubUrl: "https://github.com/cksajil",
    websiteUrl: "https://intuitivetutorial.com",
    linkedinUrl: "https://linkedin.com/in/sajilck",
  },

  nodes: [
    {
      id: "two-areas-statistics",
      label: "Two Areas of Statistics",
      domain: "foundations",
      level: "beginner",
      summary: "Overview of descriptive and inferential statistics and their role in data science.",
      resources: [{"type": "video", "label": "Two areas of statistics", "url": "https://www.youtube.com/embed/FePF2YIdntM", "duration": ""}, {"type": "video", "label": "Intro to Descriptive Statistics", "url": "https://www.youtube.com/embed/8Q4oSDfhso8", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics for Data Science and Machine", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_15.md"}]
    },
    {
      id: "math-for-dsml",
      label: "Math for DSML",
      domain: "foundations",
      level: "beginner",
      summary: "Why mathematics is essential for data science and machine learning careers.",
      resources: [{"type": "video", "label": "Math4DSML", "url": "https://www.youtube.com/embed/R3Lf-MyQ9Cg", "duration": ""}, {"type": "video", "label": "math notations 1", "url": "https://www.youtube.com/embed/aT3Oc4Z--qQ", "duration": ""}, {"type": "video", "label": " Measures of central tendency", "url": "https://www.youtube.com/embed/Q3WDm0OV_DY", "duration": ""}, {"type": "video", "label": "Percentiles and Quartiles", "url": "https://www.youtube.com/embed/5Zb8EExsXsI", "duration": ""}, {"type": "video", "label": "Finding outliers using Quartiles", "url": "https://www.youtube.com/embed/sK0QbCA81Fg", "duration": ""}, {"type": "video", "label": "Measures of dispersion", "url": "https://www.youtube.com/embed/LumyZy9-MLk", "duration": ""}, {"type": "video", "label": "corr_cause", "url": "https://www.youtube.com/embed/gh1MV72Otm0", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics for Data Science and Machine", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_15.md"}]
    },
    {
      id: "why-functions",
      label: "Why Functions",
      domain: "foundations",
      level: "beginner",
      summary: "The concept of mathematical functions and their importance in ML models.",
      resources: [{"type": "video", "label": "Functions in Mathematics", "url": "https://www.youtube.com/embed/gWRvE2_RR98", "duration": ""}, {"type": "video", "label": "Visualizing Functions", "url": "https://www.youtube.com/embed/W7S4tFQxDWY", "duration": ""}, {"type": "video", "label": "infinity", "url": "https://www.youtube.com/embed/0IOfGyncK3g", "duration": ""}, {"type": "video", "label": "concept of derivative", "url": "https://www.youtube.com/embed/JpQUtO09xi8", "duration": ""}, {"type": "video", "label": "Direction in Derivative", "url": "https://www.youtube.com/embed/-rofr5JMOpU", "duration": ""}, {"type": "video", "label": "Partial Derivative", "url": "https://www.youtube.com/embed/P8VbRBfEPXc", "duration": ""}, {"type": "blog", "label": "Session Notes — Calculus for Data Science", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_22.md"}]
    },
    {
      id: "vscode-intro",
      label: "VS Code Intro",
      domain: "tools",
      level: "beginner",
      summary: "Quick introduction to Visual Studio Code as a development environment for ML.",
      resources: [{"type": "video", "label": "Quick Intro to VS Code", "url": "https://www.youtube.com/embed/cds3AVwB_lI", "duration": ""}, {"type": "blog", "label": "Session Notes — Data Science Tools", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_07.md"}]
    },
    {
      id: "ds-installation",
      label: "DS Installation",
      domain: "tools",
      level: "beginner",
      summary: "Installing Python, Jupyter, and essential data science libraries from scratch.",
      resources: [{"type": "video", "label": "Data Science Installation Requirements", "url": "https://www.youtube.com/embed/_fuAooCJTpA", "duration": ""}]
    },
    {
      id: "touch-typing",
      label: "Touch Typing",
      domain: "foundations",
      level: "beginner",
      summary: "Why touch typing is a high-leverage foundational skill for developers.",
      resources: [{"type": "video", "label": "typing_club", "url": "https://www.youtube.com/embed/zogFqFJivwI", "duration": ""}, {"type": "blog", "label": "Session Notes — IT Foundations for Data Science", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_02.md"}]
    },
    {
      id: "github-profile",
      label: "GitHub Profile",
      domain: "tools",
      level: "beginner",
      summary: "Importance of a strong GitHub profile for landing data science jobs.",
      resources: [{"type": "video", "label": "github_dsml", "url": "https://www.youtube.com/embed/8VPh9Yk9QZI", "duration": ""}, {"type": "blog", "label": "Session Notes — IT Foundations for Data Science", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_02.md"}]
    },
    {
      id: "descriptive-stats",
      label: "Descriptive Statistics",
      domain: "foundations",
      level: "beginner",
      summary: "Key concepts in descriptive statistics including mean, median, mode, and spread.",
      resources: [{"type": "video", "label": "Descriptive Statistics", "url": "https://www.youtube.com/embed/XLIDV976zr0", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics for Data Science and Machine", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_15.md"}]
    },
    {
      id: "python-numeric",
      label: "Python Numeric Types",
      domain: "foundations",
      level: "beginner",
      summary: "Python's integer and float types, operations, and numeric data handling.",
      resources: [{"type": "video", "label": "Python Numeric Data Types", "url": "https://www.youtube.com/embed/IMrXLi2laS4", "duration": ""}, {"type": "video", "label": "Python String", "url": "https://www.youtube.com/embed/MTgNjXlO9po", "duration": ""}, {"type": "video", "label": "Python List", "url": "https://www.youtube.com/embed/GI-PeOJDAps", "duration": ""}, {"type": "video", "label": "Python Tuple", "url": "https://www.youtube.com/embed/0U4h0hDkH7k", "duration": ""}, {"type": "video", "label": "Python Set", "url": "https://www.youtube.com/embed/RDGxJFbDcag", "duration": ""}, {"type": "video", "label": "Python Standard I/O", "url": "https://www.youtube.com/embed/iFZlU-ZWuzg", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "python-strings",
      label: "Python Strings",
      domain: "foundations",
      level: "beginner",
      summary: "String data type in Python \u2014 creation, indexing, slicing, and common methods.",
      resources: [{"type": "video", "label": "Python Strings", "url": "https://www.youtube.com/embed/MTgNjXlO9po", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "python-lists",
      label: "Python Lists",
      domain: "foundations",
      level: "beginner",
      summary: "Python lists \u2014 creating, accessing, modifying, and iterating over list elements.",
      resources: [{"type": "video", "label": "Python Lists", "url": "https://www.youtube.com/embed/GI-PeOJDAps", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "python-tuples",
      label: "Python Tuples",
      domain: "foundations",
      level: "beginner",
      summary: "Immutable sequences in Python and when to use tuples over lists.",
      resources: [{"type": "video", "label": "Python Tuples", "url": "https://www.youtube.com/embed/0U4h0hDkH7k", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "python-range",
      label: "Python Range",
      domain: "foundations",
      level: "beginner",
      summary: "The range data type in Python and its use in loops and sequences.",
      resources: [{"type": "video", "label": "Python Range", "url": "https://www.youtube.com/embed/i9mJngeSCHw", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "python-dict",
      label: "Python Dictionaries",
      domain: "foundations",
      level: "beginner",
      summary: "Key-value data storage in Python using dictionaries with common operations.",
      resources: [{"type": "video", "label": "Python Dictionary", "url": "https://www.youtube.com/embed/ZtqoZ34W8lA", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "python-sets",
      label: "Python Sets",
      domain: "foundations",
      level: "beginner",
      summary: "Python sets for storing unique elements and performing set operations.",
      resources: [{"type": "video", "label": "Python Sets", "url": "https://www.youtube.com/embed/RDGxJFbDcag", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "python-boolean",
      label: "Python Booleans",
      domain: "foundations",
      level: "beginner",
      summary: "Boolean data type, True/False values, and logical expressions in Python.",
      resources: [{"type": "video", "label": "Python Boolean", "url": "https://www.youtube.com/embed/94huU3v5TAU", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "python-none",
      label: "Python None Type",
      domain: "foundations",
      level: "beginner",
      summary: "The None type in Python representing absence of value and its common uses.",
      resources: [{"type": "video", "label": "Python None", "url": "https://www.youtube.com/embed/AR5nH9qF2sM", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "python-arithmetic",
      label: "Python Arithmetic Ops",
      domain: "foundations",
      level: "beginner",
      summary: "Arithmetic operators in Python including addition, subtraction, multiplication, and division.",
      resources: [{"type": "video", "label": "Python Arithmetic Ops", "url": "https://www.youtube.com/embed/5Rzy8ikgsts", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "python-operators",
      label: "Python Operators",
      domain: "foundations",
      level: "beginner",
      summary: "Comparison, logical, and assignment operators in Python with examples.",
      resources: [{"type": "video", "label": "Python Operators 1", "url": "https://www.youtube.com/embed/5Rzy8ikgsts", "duration": ""}, {"type": "video", "label": "Python Operators 2", "url": "https://www.youtube.com/embed/5I0FYZVyYeU", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "python-if",
      label: "Python IF Statement",
      domain: "foundations",
      level: "beginner",
      summary: "Conditional logic in Python using the if statement for decision making.",
      resources: [{"type": "video", "label": "Python IF", "url": "https://www.youtube.com/embed/nY4XQDsZzFY", "duration": ""}, {"type": "blog", "label": "Session Notes — Control Flow", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_09.md"}]
    },
    {
      id: "python-if-else",
      label: "Python If Else",
      domain: "foundations",
      level: "beginner",
      summary: "Two-way branching in Python using if-else for handling alternate conditions.",
      resources: [{"type": "video", "label": "Python IF-ELSE", "url": "https://www.youtube.com/embed/lE3IGtyXjLg", "duration": ""}, {"type": "video", "label": "Python IF-ELIF-ELSE", "url": "https://www.youtube.com/embed/YDBZ0rban3M", "duration": ""}, {"type": "blog", "label": "Session Notes — Control Flow", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_09.md"}]
    },
    {
      id: "python-if-elif",
      label: "Python If Elif Else",
      domain: "foundations",
      level: "beginner",
      summary: "Multi-way branching in Python using if-elif-else chains.",
      resources: [{"type": "video", "label": "Python If Elif Else", "url": "https://www.youtube.com/embed/YDBZ0rban3M", "duration": ""}, {"type": "blog", "label": "Session Notes — Control Flow", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_09.md"}]
    },
    {
      id: "operator-overloading",
      label: "Operator Overloading",
      domain: "foundations",
      level: "intermediate",
      summary: "How Python allows redefining operator behavior for custom objects.",
      resources: [{"type": "video", "label": "Operator Overloading", "url": "https://www.youtube.com/embed/lal8F6H1bXc", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "python-for-loop",
      label: "Python For Loop",
      domain: "foundations",
      level: "beginner",
      summary: "Iterating over sequences in Python using the for loop.",
      resources: [{"type": "video", "label": "Python For Loop", "url": "https://www.youtube.com/embed/oywGQ0wVJQs", "duration": ""}, {"type": "blog", "label": "Session Notes — Loops & Functions in Python", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_10.md"}]
    },
    {
      id: "python-while-loop",
      label: "Python While Loop",
      domain: "foundations",
      level: "beginner",
      summary: "Repeating code blocks in Python using the while loop with conditions.",
      resources: [{"type": "video", "label": "Python For While Loop", "url": "https://www.youtube.com/embed/6mKpZdIfnew", "duration": ""}, {"type": "blog", "label": "Session Notes — Loops & Functions in Python", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_10.md"}]
    },
    {
      id: "break-continue",
      label: "Break and Continue",
      domain: "foundations",
      level: "beginner",
      summary: "Controlling loop flow in Python using break and continue statements.",
      resources: [{"type": "video", "label": "Python Continue-break", "url": "https://www.youtube.com/embed/Vv8YQqvg4KQ", "duration": ""}, {"type": "video", "label": "Python Continue-break", "url": "https://www.youtube.com/embed/DHfuVRoTC9o", "duration": ""}, {"type": "blog", "label": "Session Notes — Loops & Functions in Python", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_10.md"}]
    },
    {
      id: "python-functions",
      label: "Python Functions",
      domain: "foundations",
      level: "beginner",
      summary: "Defining and calling reusable code blocks using functions in Python.",
      resources: [{"type": "video", "label": "Python Intro to Functions", "url": "https://www.youtube.com/embed/a3tlV9LZ6aQ", "duration": ""}, {"type": "blog", "label": "Session Notes — Loops & Functions in Python", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_10.md"}]
    },
    {
      id: "python-input-output",
      label: "Python Input Output",
      domain: "foundations",
      level: "beginner",
      summary: "Standard input and output functions in Python for reading and printing data.",
      resources: [{"type": "video", "label": "Python Input Output", "url": "https://www.youtube.com/embed/iFZlU-ZWuzg", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "function-arguments",
      label: "Function Arguments",
      domain: "foundations",
      level: "beginner",
      summary: "Passing and returning values in Python functions using input/output arguments.",
      resources: [{"type": "video", "label": "Function Arguments", "url": "https://www.youtube.com/embed/DHfuVRoTC9o", "duration": ""}, {"type": "blog", "label": "Session Notes — Loops & Functions in Python", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_10.md"}]
    },
    {
      id: "default-arguments",
      label: "Default Arguments",
      domain: "foundations",
      level: "beginner",
      summary: "Setting default parameter values in Python functions for flexible calling.",
      resources: [{"type": "video", "label": "Python Default Arguments", "url": "https://www.youtube.com/embed/96JrQ1cZsSQ", "duration": ""}, {"type": "blog", "label": "Session Notes — Loops & Functions in Python", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_10.md"}]
    },
    {
      id: "intro-oops",
      label: "Intro to OOPs",
      domain: "foundations",
      level: "intermediate",
      summary: "Object-oriented programming concepts \u2014 classes, objects, and encapsulation in Python.",
      resources: [{"type": "video", "label": "Python OOPs Intro", "url": "https://www.youtube.com/embed/dw0A_xw0glA", "duration": ""}, {"type": "blog", "label": "Session Notes — Object Oriented Programming (OOP)", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_11.md"}]
    },
    {
      id: "python-objects",
      label: "Python Objects",
      domain: "foundations",
      level: "intermediate",
      summary: "Creating and using objects from classes in Python.",
      resources: [{"type": "video", "label": "Python Objects", "url": "https://www.youtube.com/embed/HXxxa2mxG6c", "duration": ""}, {"type": "video", "label": "Python practice 001", "url": "https://www.youtube.com/embed/fc7VKrSvF_E", "duration": ""}, {"type": "video", "label": "Python practice 002", "url": "https://www.youtube.com/embed/GSWETBkd6Ho", "duration": ""}, {"type": "video", "label": "Python practice 003", "url": "https://www.youtube.com/embed/DY8N-xNhrsY", "duration": ""}, {"type": "video", "label": "Python practice 004", "url": "https://www.youtube.com/embed/v6r0GBcY730", "duration": ""}, {"type": "video", "label": "Python practice 005", "url": "https://www.youtube.com/embed/eBLzUiQaeL8", "duration": ""}, {"type": "video", "label": "Python practice 006", "url": "https://www.youtube.com/embed/vsaN5bgTBek", "duration": ""}, {"type": "video", "label": "Python practice 007", "url": "https://www.youtube.com/embed/rFocOiHnbEs", "duration": ""}, {"type": "blog", "label": "Session Notes — Object Oriented Programming (OOP)", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_11.md"}]
    },
    {
      id: "class-inheritance",
      label: "Class Inheritance",
      domain: "foundations",
      level: "intermediate",
      summary: "Inheriting and extending class behavior in Python using inheritance.",
      resources: [{"type": "video", "label": "Python Class Inheritance", "url": "https://www.youtube.com/embed/oWwdVik7qU0", "duration": ""}, {"type": "blog", "label": "Session Notes — Object Oriented Programming (OOP)", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_11.md"}]
    },
    {
      id: "markdown-format",
      label: "Markdown Format",
      domain: "tools",
      level: "beginner",
      summary: "Writing formatted documentation using Markdown for GitHub and Jupyter notebooks.",
      resources: [{"type": "video", "label": "markdown", "url": "https://www.youtube.com/embed/i5X5VYzEJCo", "duration": ""}, {"type": "blog", "label": "Session Notes — Data Science Tools", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_07.md"}]
    },
    {
      id: "intro-git-bash",
      label: "Intro to Git Bash",
      domain: "tools",
      level: "beginner",
      summary: "Version control basics using Git Bash \u2014 the most powerful tool for data science.",
      resources: [{"type": "video", "label": "Git Bash", "url": "https://www.youtube.com/embed/cWnPSnpLb2M", "duration": ""}, {"type": "video", "label": "Command Line Basics", "url": "https://www.youtube.com/embed/B5ISXHnYVCg", "duration": ""}, {"type": "blog", "label": "Session Notes — Command Line Basics", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_14.md"}, {"type": "video", "label": "HTML CSS 1", "url": "https://www.youtube.com/embed/vLOltaWPIz0", "duration": ""}, {"type": "video", "label": "HTML CSS 2", "url": "https://www.youtube.com/embed/T-18Cpclsn4", "duration": ""}, {"type": "video", "label": "HTML CSS 3", "url": "https://www.youtube.com/embed/vuR0nGMnytE", "duration": ""}, {"type": "video", "label": "HTML CSS 4", "url": "https://www.youtube.com/embed/xF_q_XAP4g4", "duration": ""}, {"type": "blog", "label": "Session Notes — Introduction to HTML and CSS", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_51.md"}]
    },
    {
      id: "basics-notation",
      label: "Math Notation Basics",
      domain: "foundations",
      level: "beginner",
      summary: "Reading and writing mathematical notation used in ML papers and textbooks.",
      resources: [{"type": "video", "label": "Math Notation Basics", "url": "https://www.youtube.com/embed/aT3Oc4Z--qQ", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics for Data Science and Machine", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_15.md"}]
    },
    {
      id: "abstract-math",
      label: "Abstract Mathematics",
      domain: "foundations",
      level: "beginner",
      summary: "Understanding the abstract nature of mathematics and how it applies to ML.",
      resources: [{"type": "video", "label": "about_math", "url": "https://www.youtube.com/embed/JfoQp_btlHo", "duration": ""}, {"type": "video", "label": "orthogonality", "url": "https://www.youtube.com/embed/oDjwNhk1jSs", "duration": ""}, {"type": "video", "label": "mat_inv", "url": "https://www.youtube.com/embed/BXS7Ccb-Us8", "duration": ""}, {"type": "video", "label": "mat_trans", "url": "https://www.youtube.com/embed/MmL-KLK-a9c", "duration": ""}, {"type": "video", "label": "mat_inv", "url": "https://www.youtube.com/embed/BSlbJ8gwZMM", "duration": ""}, {"type": "video", "label": "eigen_val_vec", "url": "https://www.youtube.com/embed/vrEPiB5-7d8", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics and its Abstract Nature", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_19.md"}]
    },
    {
      id: "multivariable-assign",
      label: "Multivariable Assignment",
      domain: "foundations",
      level: "beginner",
      summary: "Assigning multiple variables simultaneously and formatted printing in Python.",
      resources: [{"type": "video", "label": "Multivariable Assignment", "url": "https://www.youtube.com/embed/qwwPc2bxkx8", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "print-formatting",
      label: "Python Print Formatting",
      domain: "foundations",
      level: "beginner",
      summary: "String formatting techniques in Python using f-strings and format methods.",
      resources: [{"type": "video", "label": "Python Print Formatting", "url": "https://www.youtube.com/embed/LoBQw86XT5Y", "duration": ""}, {"type": "video", "label": "Python Print Formatting", "url": "https://www.youtube.com/embed/qwwPc2bxkx8", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "list-operations",
      label: "Python List Operations",
      domain: "foundations",
      level: "beginner",
      summary: "Advanced list operations in Python including sorting, slicing, and list methods.",
      resources: [{"type": "video", "label": "Python List Operations", "url": "https://www.youtube.com/embed/fLHKIrht5j0", "duration": ""}, {"type": "blog", "label": "Session Notes — Python Data Types", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_08.md"}]
    },
    {
      id: "split-join",
      label: "Split and Join",
      domain: "foundations",
      level: "beginner",
      summary: "Splitting strings into lists and joining lists back into strings in Python.",
      resources: [{"type": "video", "label": "Python split join", "url": "https://www.youtube.com/embed/_W--TwDA6Nk", "duration": ""}, {"type": "blog", "label": "Session Notes — Control Flow", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_09.md"}]
    },
    {
      id: "vectors-intro",
      label: "Vectors Introduction",
      domain: "foundations",
      level: "beginner",
      summary: "Understanding vectors, their dimensions, and directions in linear algebra.",
      resources: [{"type": "video", "label": "row_col_vectors", "url": "https://www.youtube.com/embed/JAdl83M-e_s", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics and its Abstract Nature", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_19.md"}]
    },
    {
      id: "vector-as-force",
      label: "Vector as Force",
      domain: "foundations",
      level: "beginner",
      summary: "Visualizing vectors as pushes or forces in a direction for ML intuition.",
      resources: [{"type": "video", "label": "vector_push", "url": "https://www.youtube.com/embed/GZjHB-zwcLY", "duration": ""}, {"type": "video", "label": "vector_direction", "url": "https://www.youtube.com/embed/ks7YatPVfxI", "duration": ""}, {"type": "video", "label": "basis_vector", "url": "https://www.youtube.com/embed/S1ipna8-ipM", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics and its Abstract Nature", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_19.md"}]
    },
    {
      id: "basis-vectors",
      label: "Basis Vectors",
      domain: "foundations",
      level: "beginner",
      summary: "Expressing vectors as combinations of basis vectors in linear algebra.",
      resources: [{"type": "video", "label": "Basis Vectors", "url": "https://www.youtube.com/embed/S1ipna8-ipM", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics and its Abstract Nature", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_19.md"}]
    },
    {
      id: "vector-magnitude",
      label: "Vector Magnitude",
      domain: "foundations",
      level: "beginner",
      summary: "Computing the magnitude or length of a vector using the Euclidean norm.",
      resources: [{"type": "video", "label": "vector_magnitude", "url": "https://www.youtube.com/embed/GdGxteaAt3M", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics and its Abstract Nature", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_19.md"}]
    },
    {
      id: "unit-vector",
      label: "Unit Vector",
      domain: "foundations",
      level: "beginner",
      summary: "Understanding unit vectors and normalizing vectors to unit length.",
      resources: [{"type": "video", "label": "unit_vector", "url": "https://www.youtube.com/embed/l-CbspzeHlY", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics and its Abstract Nature", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_19.md"}]
    },
    {
      id: "dot-product",
      label: "Dot Product",
      domain: "foundations",
      level: "beginner",
      summary: "Vector dot product, its geometric interpretation, and orthogonality in ML.",
      resources: [{"type": "video", "label": "dot_product", "url": "https://www.youtube.com/embed/tqxq3XBW53E", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics and its Abstract Nature", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_19.md"}]
    },
    {
      id: "resume-guidelines",
      label: "Resume Guidelines",
      domain: "tools",
      level: "beginner",
      summary: "Practical guidelines for writing a strong data science and ML resume.",
      resources: [{"type": "video", "label": "resume", "url": "https://www.youtube.com/embed/Y3uWpQlTIWU", "duration": ""}, {"type": "blog", "label": "Session Notes — IT Foundations for Data Science", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_02.md"}]
    },
    {
      id: "orthogonality",
      label: "Orthogonality",
      domain: "foundations",
      level: "beginner",
      summary: "The concept of orthogonality between vectors and its significance in ML.",
      resources: [{"type": "video", "label": "Orthogonality", "url": "https://www.youtube.com/embed/oDjwNhk1jSs", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics for Data Science and Machine", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_15.md"}]
    },
    {
      id: "cosine-similarity",
      label: "Cosine Similarity",
      domain: "foundations",
      level: "intermediate",
      summary: "Measuring similarity between vectors using cosine similarity \u2014 key for NLP and search.",
      resources: [{"type": "video", "label": "Cosine Similarity", "url": "https://www.youtube.com/embed/LfjWIj9yW4s", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics for Data Science and Machine", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_15.md"}]
    },
    {
      id: "vector-projection",
      label: "Vector Projection",
      domain: "foundations",
      level: "intermediate",
      summary: "Projecting one vector onto another and its applications in dimensionality reduction.",
      resources: [{"type": "video", "label": "vector_projection", "url": "https://www.youtube.com/embed/BXS7Ccb-Us8", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics and its Abstract Nature", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_19.md"}]
    },
    {
      id: "colab-tutorial-1",
      label: "Google Colab Part 1",
      domain: "tools",
      level: "beginner",
      summary: "Getting started with Google Colab \u2014 setting up notebooks and running Python in the cloud.",
      resources: [{"type": "video", "label": "Data Science Tools", "url": "https://www.youtube.com/embed/_fuAooCJTpA", "duration": ""}, {"type": "video", "label": "Google Colab Tutorial 1", "url": "https://www.youtube.com/embed/cswmnpVymHQ", "duration": ""}, {"type": "video", "label": "Google Colab Tutorial 2", "url": "https://www.youtube.com/embed/bh820H9MD3k", "duration": ""}, {"type": "video", "label": "Kaggle Tutorial", "url": "https://www.youtube.com/embed/IgihTAagHHk", "duration": ""}, {"type": "video", "label": "VS Extensions 1", "url": "https://www.youtube.com/embed/sqJhKbsZqtA", "duration": ""}, {"type": "video", "label": "VS Extensions 2", "url": "https://www.youtube.com/embed/1XgCiD5QHQU", "duration": ""}, {"type": "video", "label": "VS Extensions 3", "url": "https://www.youtube.com/embed/rxhtjmuM6E0", "duration": ""}, {"type": "blog", "label": "Session Notes — Data Science Tools", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_07.md"}]
    },
    {
      id: "correlation-heatmap",
      label: "Correlation Heatmap",
      domain: "tools",
      level: "intermediate",
      summary: "Visualizing feature correlations using an upper triangular heatmap in seaborn.",
      resources: [{"type": "video", "label": "Triangular Correlation Heatmap", "url": "https://www.youtube.com/embed/7RMbrZgUBp8", "duration": ""}, {"type": "blog", "label": "Session Notes — Data Visualization and Feature Engineeri", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_35.md"}]
    },
    {
      id: "tqdm-library",
      label: "TQDM Library",
      domain: "tools",
      level: "beginner",
      summary: "Adding progress bars to Python loops using the TQDM library.",
      resources: [{"type": "video", "label": "TQDM Library", "url": "https://www.youtube.com/embed/v6r0GBcY730", "duration": ""}, {"type": "blog", "label": "Session Notes — Loops & Functions in Python", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_10.md"}]
    },
    {
      id: "colab-tutorial-2",
      label: "Google Colab Part 2",
      domain: "tools",
      level: "beginner",
      summary: "Advanced Google Colab features \u2014 GPU access, file handling, and drive integration.",
      resources: [{"type": "video", "label": "Google Colab Part 2", "url": "https://www.youtube.com/embed/bh820H9MD3k", "duration": ""}, {"type": "blog", "label": "Session Notes — Data Science Tools", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_07.md"}]
    },
    {
      id: "bias-variance",
      label: "Bias and Variance",
      domain: "ml-core",
      level: "intermediate",
      summary: "Understanding the bias-variance tradeoff and its impact on model performance.",
      resources: [{"type": "video", "label": "Intro 2 Bias and Variance ", "url": "https://www.youtube.com/embed/vEKaehF3d9U", "duration": ""}, {"type": "blog", "label": "Session Notes — Types of Algorithms", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_42.md"}]
    },
    {
      id: "vscode-walkthrough",
      label: "VS Code Walkthrough",
      domain: "tools",
      level: "beginner",
      summary: "Full walkthrough of Visual Studio Code features for ML development.",
      resources: [{"type": "video", "label": "VS Code Walkthrough", "url": "https://www.youtube.com/embed/ZCn9dgRLQ_8", "duration": ""}, {"type": "blog", "label": "Session Notes — Data Science Tools", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_07.md"}]
    },
    {
      id: "linear-regression-intuition",
      label: "Linear Regression Intuition",
      domain: "ml-core",
      level: "beginner",
      summary: "Building geometric intuition for how linear regression fits a line to data.",
      resources: [{"type": "video", "label": "Linear Regression Intuition", "url": "https://www.youtube.com/embed/XnaJ04s6DTs", "duration": ""}, {"type": "video", "label": "Linear Regression from Scratch", "url": "https://www.youtube.com/embed/_yiTZQ0vR60", "duration": ""}, {"type": "blog", "label": "Session Notes — Types of Algorithms", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_42.md"}]
    },
    {
      id: "knn-algorithm",
      label: "KNN Algorithm",
      domain: "ml-core",
      level: "beginner",
      summary: "K-Nearest Neighbors classification \u2014 intuition, distance metrics, and choosing K.",
      resources: [{"type": "video", "label": "KNN from scratch", "url": "https://www.youtube.com/embed/8cHGBZ_3K-8", "duration": ""}, {"type": "blog", "label": "Session Notes — Logistic Regression", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_43.md"}]
    },
    {
      id: "numpy-intro",
      label: "NumPy Introduction",
      domain: "foundations",
      level: "beginner",
      summary: "Introduction to NumPy arrays \u2014 the foundation for numerical computing in Python.",
      resources: [{"type": "video", "label": "DSML Libraries", "url": "https://www.youtube.com/embed/gABxNYVrLKg", "duration": ""}, {"type": "video", "label": "Numpy Part 1", "url": "https://www.youtube.com/embed/ogEfmubVJqI", "duration": ""}, {"type": "video", "label": "Numpy Tutorial", "url": "https://www.youtube.com/embed/XC0oFw84Oz8", "duration": ""}, {"type": "video", "label": "Numpy Part 1", "url": "https://www.youtube.com/embed/fWX0KvqE6AU", "duration": ""}, {"type": "blog", "label": "Session Notes — Introduction to Data Science and Machine", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_23.md"}]
    },
    {
      id: "pandas-intro",
      label: "Pandas Introduction",
      domain: "foundations",
      level: "beginner",
      summary: "Introduction to Pandas DataFrames for loading, exploring, and manipulating tabular data.",
      resources: [{"type": "video", "label": "Pandas Tutorial", "url": "https://www.youtube.com/embed/0SPB2VhpoNY", "duration": ""}, {"type": "blog", "label": "Session Notes — Introduction to Data Science and Machine", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_23.md"}]
    },
    {
      id: "data-visualization-1",
      label: "Data Visualization Part 1",
      domain: "tools",
      level: "beginner",
      summary: "Creating basic plots with Matplotlib \u2014 line, bar, scatter, and histogram charts.",
      resources: [{"type": "video", "label": "Data Visualization with Matplotlib", "url": "https://www.youtube.com/embed/3vGtB77BNJU", "duration": ""}, {"type": "video", "label": "Data Visualization Part 2", "url": "https://www.youtube.com/embed/SsosANWiitQ", "duration": ""}, {"type": "blog", "label": "Session Notes — Data Visualization and Feature Engineeri", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_35.md"}]
    },
    {
      id: "fastapi-intro",
      label: "FastAPI Introduction",
      domain: "mlops",
      level: "intermediate",
      summary: "Building REST APIs for ML models using FastAPI with automatic documentation.",
      resources: [{"type": "video", "label": "Flask Part 1", "url": "https://www.youtube.com/embed/lG3RgrzppnI", "duration": ""}, {"type": "video", "label": "Flask Part 2", "url": "https://www.youtube.com/embed/_GNoYvanXYo", "duration": ""}, {"type": "video", "label": "Flask Part 3", "url": "https://www.youtube.com/embed/EH4u8hAjm2A", "duration": ""}, {"type": "video", "label": "Flask Part 4", "url": "https://www.youtube.com/embed/MNQkSF8h6wo", "duration": ""}, {"type": "video", "label": "Flask Part 5", "url": "https://www.youtube.com/embed/IAackuaGdzM", "duration": ""}, {"type": "video", "label": "Flask Part 6", "url": "https://www.youtube.com/embed/flOKENTLw1k", "duration": ""}, {"type": "video", "label": "Flask Part 7", "url": "https://www.youtube.com/embed/-vPwKsyC0LA", "duration": ""}, {"type": "video", "label": "Flask Part 8", "url": "https://www.youtube.com/embed/63Drf-skV3A", "duration": ""}, {"type": "blog", "label": "Session Notes — Introduction to Flask", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_52.md"}, {"type": "video", "label": "FAST API Part 1", "url": "https://www.youtube.com/embed/aAnQj2jfufk", "duration": ""}, {"type": "video", "label": "FAST API Part 2", "url": "https://www.youtube.com/embed/xpasTBQ5EXc", "duration": ""}, {"type": "video", "label": "Streamlit Part 1", "url": "https://www.youtube.com/embed/bWasfCZHo-g", "duration": ""}, {"type": "video", "label": "Streamlit Part 2", "url": "https://www.youtube.com/embed/ss6KOS7fI64", "duration": ""}, {"type": "video", "label": "Streamlit Part 3", "url": "https://www.youtube.com/embed/gOvNATdGFbo", "duration": ""}, {"type": "blog", "label": "Session Notes — Fast API and Streamlit", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_53.md"}]
    },
    {
      id: "scikit-learn-intro",
      label: "Scikit-learn Intro",
      domain: "ml-core",
      level: "beginner",
      summary: "The go-to Python ML library \u2014 fit, predict, and evaluate models with a unified API.",
      resources: [{"type": "video", "label": "Variance Equation to Code", "url": "https://www.youtube.com/embed/dQkoi2eTx8", "duration": ""}]
    },
    {
      id: "data-preprocessing-pipeline",
      label: "Data Preprocessing",
      domain: "ml-core",
      level: "beginner",
      summary: "End-to-end data preprocessing pipeline \u2014 cleaning, transforming, and preparing data for ML.",
      resources: [{"type": "video", "label": "Data Preprocessing", "url": "https://www.youtube.com/embed/SNpUkV-kuj4", "duration": ""}, {"type": "blog", "label": "Session Notes — Data Proprocessing", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_39.md"}]
    },
    {
      id: "seaborn-intro",
      label: "Seaborn Introduction",
      domain: "tools",
      level: "beginner",
      summary: "Statistical data visualization with Seaborn \u2014 distributions, relationships, and categorical plots.",
      resources: [{"type": "video", "label": "Command Line Basics Part 1", "url": "https://www.youtube.com/embed/SsosANWiitQ", "duration": ""}]
    },
    {
      id: "python-os-library",
      label: "Python OS Library",
      domain: "tools",
      level: "beginner",
      summary: "Navigating file systems and managing paths with Python's os library.",
      resources: [{"type": "video", "label": "Introduction to Kaggle", "url": "https://www.youtube.com/embed/cul52ne8iGQ", "duration": ""}]
    },
    {
      id: "sql-select-where",
      label: "SQL SELECT & WHERE",
      domain: "tools",
      level: "beginner",
      summary: "Querying databases with SQL SELECT, WHERE, GROUP BY, and ORDER BY clauses.",
      resources: [{"type": "video", "label": "Introduction to SQL for Data Scientists", "url": "https://www.youtube.com/embed/0x0dW8T-4uo", "duration": ""}, {"type": "blog", "label": "Session Notes — SQL Basics and CRUD", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_26.md"}]
    },
    {
      id: "classification-regression-clustering",
      label: "ML Problem Types",
      domain: "ml-core",
      level: "beginner",
      summary: "Introduction to classification, regression, and clustering as core ML problem types.",
      resources: [{"type": "video", "label": "Classification, Regression, Clustering", "url": "https://www.youtube.com/embed/T4Ha6U0PJ7s", "duration": ""}, {"type": "blog", "label": "Session Notes — Types of Algorithms", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_42.md"}]
    },
    {
      id: "pyyaml-config",
      label: "PyYAML Configuration",
      domain: "tools",
      level: "beginner",
      summary: "Reading configuration values from YAML files using the PyYAML library in Python.",
      resources: [{"type": "video", "label": "Python Writing Raw Text Files", "url": "https://www.youtube.com/embed/A5GoYjlDVVY", "duration": ""}]
    },
    {
      id: "matplotlib-tutorial-1",
      label: "Matplotlib Tutorial 1",
      domain: "tools",
      level: "beginner",
      summary: "Comprehensive introduction to Matplotlib for creating charts and visualizations.",
      resources: [{"type": "video", "label": "Python Matplotlib Tutorial 1", "url": "https://www.youtube.com/embed/3vGtB77BNJU", "duration": ""}]
    },
    {
      id: "python-os-intro",
      label: "Python OS Library Intro",
      domain: "tools",
      level: "beginner",
      summary: "Introduction to Python's os library for file and directory management.",
      resources: [{"type": "video", "label": "Python: Introduction to OS Library", "url": "https://www.youtube.com/embed/cul52ne8iGQ", "duration": ""}]
    },
    {
      id: "image-processing-cv",
      label: "Image Processing for CV",
      domain: "deep-learning",
      level: "intermediate",
      summary: "Loading, manipulating, and preprocessing images for computer vision with OpenCV.",
      resources: [{"type": "video", "label": "Image Processing for CV", "url": "https://www.youtube.com/embed/fWX0KvqE6AU", "duration": ""}, {"type": "blog", "label": "Session Notes — Introduction to Data Science and Machine", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_23.md"}]
    },
    {
      id: "reading-json",
      label: "Reading JSON in Python",
      domain: "tools",
      level: "beginner",
      summary: "Parsing and working with JSON data structures in Python.",
      resources: [{"type": "video", "label": "Reading JSON files in Python", "url": "https://www.youtube.com/embed/H999zBdovoI", "duration": ""}]
    },
    {
      id: "data-preprocessing-full",
      label: "Data Preprocessing Full",
      domain: "ml-core",
      level: "intermediate",
      summary: "Complete data preprocessing workflow including cleaning, encoding, and scaling.",
      resources: [{"type": "video", "label": "Data Preprocessing", "url": "https://www.youtube.com/embed/SNpUkV-kuj4", "duration": ""}]
    },
    {
      id: "save-numpy-arrays",
      label: "Save NumPy Arrays",
      domain: "tools",
      level: "beginner",
      summary: "Persisting NumPy arrays to disk and loading them back for reproducible workflows.",
      resources: [{"type": "video", "label": "Saving and Reading Numpy Arrays in Python", "url": "https://www.youtube.com/embed/F3XIOlKR85k", "duration": ""}]
    },
    {
      id: "sql-joins",
      label: "SQL JOINs",
      domain: "tools",
      level: "beginner",
      summary: "Combining data from multiple tables using INNER, LEFT, RIGHT, and FULL joins in SQL.",
      resources: [{"type": "video", "label": "SQL for Data Science Malayalam | SELECT WHERE GROUP BY explained", "url": "https://www.youtube.com/embed/_-aHSYRK80I", "duration": ""}]
    },
    {
      id: "ml-algorithm-types",
      label: "ML Algorithm Types",
      domain: "ml-core",
      level: "beginner",
      summary: "Survey of common classification and regression algorithms and when to use each.",
      resources: [{"type": "video", "label": "ML Algorithm Types", "url": "https://www.youtube.com/embed/T4Ha6U0PJ7s", "duration": ""}, {"type": "blog", "label": "Session Notes — Types of Algorithms", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_42.md"}]
    },
    {
      id: "cnn-architectures-overview",
      label: "CNN Architectures Overview",
      domain: "deep-learning",
      level: "advanced",
      summary: "Comparing ResNet, VGG, Inception, and EfficientNet architectures for vision tasks.",
      resources: [{"type": "video", "label": "Overview of CNN Architectures", "url": "https://www.youtube.com/embed/Onj6xwYEVNE", "duration": ""}, {"type": "blog", "label": "Session Notes — Deep Learning", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_56.md"}]
    },
    {
      id: "word-embedding-techniques",
      label: "Word Embedding Techniques",
      domain: "nlp",
      level: "intermediate",
      summary: "Comparing Word2Vec, GloVe, and FastText embedding techniques for NLP applications.",
      resources: [{"type": "video", "label": "Word Embedding Techniques in NLP", "url": "https://www.youtube.com/embed/KxBjea3khEs", "duration": ""}, {"type": "blog", "label": "Session Notes — Deep Learning", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_56.md"}]
    },
    {
      id: "python-best-practices",
      label: "Python Best Practices",
      domain: "foundations",
      level: "intermediate",
      summary: "Writing clean, readable, and maintainable Python code following best practices.",
      resources: [{"type": "video", "label": "Python Coding Best Practices", "url": "https://www.youtube.com/embed/TDbo1mLpjOM", "duration": ""}, {"type": "blog", "label": "Session Notes — Coding Best Practices", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_12.md"}]
    },
    {
      id: "version-control",
      label: "Version Control",
      domain: "tools",
      level: "beginner",
      summary: "Git fundamentals \u2014 commits, branches, merges, and collaborating on GitHub.",
      resources: [{"type": "video", "label": "Version Control", "url": "https://www.youtube.com/embed/gGCohy7TCfw", "duration": ""}, {"type": "blog", "label": "Session Notes — Command Line Basics", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_14.md"}]
    },
    {
      id: "deep-learning-nlp-1",
      label: "Deep Learning for NLP 1",
      domain: "nlp",
      level: "intermediate",
      summary: "Applying deep learning techniques to NLP tasks using RNNs and embeddings.",
      resources: [{"type": "video", "label": "Deep Learning for NLP", "url": "https://www.youtube.com/embed/-m6JZKNoE6E", "duration": ""}, {"type": "blog", "label": "Session Notes — Deep Learning", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_56.md"}]
    },
    {
      id: "feature-engineering",
      label: "Feature Engineering",
      domain: "ml-core",
      level: "intermediate",
      summary: "Creating informative features from raw data to improve machine learning model performance.",
      resources: [{"type": "video", "label": "Feature Engineering", "url": "https://www.youtube.com/embed/KP_05zKgj98", "duration": ""}, {"type": "blog", "label": "Session Notes — Data Visualization and Feature Engineeri", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_35.md"}]
    },
    {
      id: "data-viz-part-2",
      label: "Data Visualization Part 2",
      domain: "tools",
      level: "intermediate",
      summary: "Advanced visualization techniques with Matplotlib and Seaborn for data analysis.",
      resources: [{"type": "video", "label": "Data Visualization Part 2", "url": "https://www.youtube.com/embed/SsosANWiitQ", "duration": ""}, {"type": "blog", "label": "Session Notes — Data Visualization and Feature Engineeri", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_35.md"}]
    },
    {
      id: "ml-algorithm-types-2",
      label: "ML Algorithm Types Survey",
      domain: "ml-core",
      level: "beginner",
      summary: "Types of machine learning algorithms \u2014 supervised, unsupervised, and semi-supervised.",
      resources: [{"type": "video", "label": "Types of Machine Learning Algorithms", "url": "https://www.youtube.com/embed/zjR48Bf60zE", "duration": ""}]
    },
    {
      id: "common-ml-algorithms",
      label: "Common ML Algorithms",
      domain: "ml-core",
      level: "beginner",
      summary: "Survey of the most commonly used classification and regression algorithms.",
      resources: [{"type": "video", "label": "Common Classification and Regression Algorithms", "url": "https://www.youtube.com/embed/6VaRdVum__o", "duration": ""}]
    },
    {
      id: "sklearn-apis",
      label: "Common Scikit-learn APIs",
      domain: "ml-core",
      level: "beginner",
      summary: "The most commonly used Scikit-learn classes and methods for end-to-end ML workflows.",
      resources: [{"type": "video", "label": "Common Scikit Learn APIs", "url": "https://www.youtube.com/embed/dQkoi2eTx8", "duration": ""}]
    },
    {
      id: "office-productivity",
      label: "Office Productivity Tools",
      domain: "tools",
      level: "beginner",
      summary: "Essential productivity tools for data scientists \u2014 shortcuts, apps, and workflows.",
      resources: [{"type": "video", "label": "Office Productivity Tools", "url": "https://www.youtube.com/embed/3TolpADjH1E", "duration": ""}]
    },
    {
      id: "vim-editor",
      label: "Intro to VIM Editor",
      domain: "tools",
      level: "beginner",
      summary: "Navigating and editing files in VIM \u2014 the essential terminal text editor.",
      resources: [{"type": "video", "label": "Intro to VIM Editor", "url": "https://www.youtube.com/embed/H_g7_niAp1Y", "duration": ""}]
    },
    {
      id: "pillow-library",
      label: "Pillow Library",
      domain: "tools",
      level: "beginner",
      summary: "Reading, manipulating, and saving images using Python's Pillow (PIL) library.",
      resources: [{"type": "video", "label": "Intro to Pillow Library", "url": "https://www.youtube.com/embed/OQT38WXPCio", "duration": ""}]
    },
    {
      id: "min-max-scaling",
      label: "Min-Max Scaling",
      domain: "ml-core",
      level: "beginner",
      summary: "Scaling features to a fixed range using min-max normalization for ML preprocessing.",
      resources: [{"type": "video", "label": "Image Processing for CV", "url": "https://www.youtube.com/embed/fWX0KvqE6AU", "duration": ""}, {"type": "blog", "label": "Session Notes — Encoding, Scaling, Normalization, Corrle", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_40.md"}]
    },
    {
      id: "reading-audio-files",
      label: "Reading Audio Files",
      domain: "tools",
      level: "beginner",
      summary: "Loading and inspecting audio files in Python for speech and audio ML tasks.",
      resources: [{"type": "video", "label": "Reading Audio Files", "url": "https://www.youtube.com/embed/cAF_sl31IL8", "duration": ""}]
    },
    {
      id: "gaussian-distribution",
      label: "Gaussian Distribution",
      domain: "foundations",
      level: "intermediate",
      summary: "Normal distribution visualized \u2014 properties, empirical rule, and its role in ML.",
      resources: [{"type": "video", "label": "Gaussian Distribution", "url": "https://www.youtube.com/embed/TbS1iYIA6QI", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics for Data Science and Machine", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_15.md"}]
    },
    {
      id: "tensorflow-gpu",
      label: "TensorFlow GPU Setup",
      domain: "tools",
      level: "beginner",
      summary: "Checking and configuring GPU availability with TensorFlow for deep learning.",
      resources: [{"type": "video", "label": "Checking GPU Avaialability with TensorFlow", "url": "https://www.youtube.com/embed/DOM6BKt2n1Y", "duration": ""}]
    },
    {
      id: "covariance-matrix",
      label: "Covariance Matrix",
      domain: "foundations",
      level: "intermediate",
      summary: "Understanding covariance matrices and their role in PCA and multivariate analysis.",
      resources: [{"type": "video", "label": "Covariance Matrix", "url": "https://www.youtube.com/embed/aaRkjeGRgHA", "duration": ""}, {"type": "blog", "label": "Session Notes — Mathematics and its Abstract Nature", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_19.md"}]
    },
    {
      id: "computer-vision-primer",
      label: "Computer Vision Primer",
      domain: "deep-learning",
      level: "beginner",
      summary: "Introduction to computer vision \u2014 images, pixels, color spaces, and CV tasks.",
      resources: [{"type": "video", "label": "Computer Vision Primer", "url": "https://www.youtube.com/embed/HbV7bQs3DKs", "duration": ""}]
    },
    {
      id: "sql-joins-2",
      label: "SQL Joins Malayalam",
      domain: "tools",
      level: "beginner",
      summary: "Combining tables using SQL JOIN operations \u2014 INNER, LEFT, RIGHT, and FULL OUTER.",
      resources: [{"type": "video", "label": "SQL Joins Malayalam", "url": "https://www.youtube.com/embed/zcI5QrMAuwQ", "duration": ""}]
    },
    {
      id: "qwen-grader-demo",
      label: "Qwen Code Grader Demo",
      domain: "projects",
      level: "advanced",
      summary: "Demo of the AI assignment grader built with Qwen2.5-Coder via Ollama and Gradio.",
      resources: [{"type": "video", "label": "Qwen Code Grader Demo", "url": "https://www.youtube.com/embed/mn-7UMb5nkE", "duration": ""}]
    },
    {
      id: "colab-github-workflow",
      label: "Colab & GitHub Workflow",
      domain: "mlops",
      level: "intermediate",
      summary: "End-to-end ML development workflow combining Google Colab with GitHub version control.",
      resources: [{"type": "video", "label": "ML Develoopment with Google Colab & GitHub", "url": "https://www.youtube.com/embed/JjQG4Oc20jo", "duration": ""}]
    },
    {
      id: "pymupdf-pdf-reading",
      label: "Reading PDFs with PyMuPDF",
      domain: "tools",
      level: "intermediate",
      summary: "Extracting text and data from PDF files using the PyMuPDF library in Python.",
      resources: [{"type": "video", "label": "Reading PDF files with PyMuPDF", "url": "https://www.youtube.com/embed/zsSce8IKfRw", "duration": ""}]
    },
    {
      id: "python-library-ecosystem",
      label: "Python Library Ecosystem",
      domain: "foundations",
      level: "beginner",
      summary: "Overview of the Python library ecosystem for data science, ML, and AI development.",
      resources: [{"type": "video", "label": "Python Library", "url": "https://www.youtube.com/embed/TA3n-txytck", "duration": ""}, {"type": "video", "label": "DSML Library", "url": "https://www.youtube.com/embed/gABxNYVrLKg", "duration": ""}, {"type": "blog", "label": "Session Notes — Loops & Functions in Python", "url": "https://github.com/cksajil/DSAIRP25/blob/main/notes/session_10.md"}]
    },
    {
      id: "map-of-mathematics",
      label: "Map of Mathematics",
      domain: "foundations",
      level: "beginner",
      summary: "Visual overview of all major branches of mathematics and how they connect.",
      resources: [{"type": "video", "label": "Map of Mathematics", "url": "https://www.youtube.com/embed/au3AJq922nI", "duration": ""}]
    },
    {
      id: "intro-probability",
      label: "Intro to Probability",
      domain: "foundations",
      level: "beginner",
      summary: "Foundational probability concepts \u2014 experiments, outcomes, events, and probability rules.",
      resources: [{"type": "video", "label": "Intro to Probability", "url": "https://www.youtube.com/embed/BztRkxDb3h0", "duration": ""}]
    },
    {
      id: "key-terms-probability",
      label: "Key Probability Terms",
      domain: "foundations",
      level: "beginner",
      summary: "Essential probability vocabulary \u2014 sample space, events, union, intersection, complement.",
      resources: [{"type": "video", "label": "Key Probability Terms", "url": "https://www.youtube.com/embed/YoIIunQArhc", "duration": ""}]
    },
    {
      id: "joint-conditional-prob",
      label: "Joint & Conditional Probability",
      domain: "foundations",
      level: "intermediate",
      summary: "Joint, conditional, dependent, and independent probabilities explained with examples.",
      resources: [{"type": "video", "label": "Joint & Conditional Probability", "url": "https://www.youtube.com/embed/q8MHbZ6ifWA", "duration": ""}]
    },
    {
      id: "inferential-statistics",
      label: "Inferential Statistics",
      domain: "foundations",
      level: "intermediate",
      summary: "Why inferential statistics matters \u2014 making predictions and decisions from sample data.",
      resources: [{"type": "video", "label": "Inferential Statistics", "url": "https://www.youtube.com/embed/qYU_mbz2qEw", "duration": ""}]
    },
    {
      id: "list-comprehension",
      label: "List Comprehension",
      domain: "foundations",
      level: "beginner",
      summary: "Writing concise and efficient list transformations using Python list comprehension.",
      resources: [{"type": "video", "label": "List Comprehension", "url": "https://www.youtube.com/embed/tdvl8dv0tzk", "duration": ""}]
    },
    {
      id: "python-files-read",
      label: "Python File Reading",
      domain: "foundations",
      level: "beginner",
      summary: "Reading text and CSV files in Python using built-in file handling functions.",
      resources: [{"type": "video", "label": "Python File Reading", "url": "https://www.youtube.com/embed/iFZlU-ZWuzg", "duration": ""}]
    },
    {
      id: "python-files-write",
      label: "Python File Writing",
      domain: "foundations",
      level: "beginner",
      summary: "Writing data to files in Python \u2014 creating, appending, and managing file output.",
      resources: [{"type": "video", "label": "Python File Writing", "url": "https://www.youtube.com/embed/3cJMqHyaKGU", "duration": ""}]
    },
    {
      id: "generic-python-1",
      label: "Generic Python Techniques 1",
      domain: "foundations",
      level: "intermediate",
      summary: "Useful Python tricks and patterns that every data scientist should know.",
      resources: [{"type": "video", "label": "Generic Python Techniques 1", "url": "https://www.youtube.com/embed/6nfVFuEY25o", "duration": ""}]
    },
    {
      id: "generic-python-2",
      label: "Generic Python Techniques 2",
      domain: "foundations",
      level: "intermediate",
      summary: "More Python idioms and patterns for writing efficient data science code.",
      resources: [{"type": "video", "label": "Generic Python Techniques 2", "url": "https://www.youtube.com/embed/QeQZFj8g8Nk", "duration": ""}]
    },
    {
      id: "practice-vowel-print",
      label: "Practice: Vowel Printing",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 filtering and printing only vowels from a text string.",
      resources: [{"type": "video", "label": "Practice: Vowel Printing", "url": "https://www.youtube.com/embed/__NgWy-yBNo", "duration": ""}]
    },
    {
      id: "practice-otp",
      label: "Practice: OTP Generator",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice problem \u2014 building an OTP (one-time password) generator.",
      resources: [{"type": "video", "label": "Practice: OTP Generator", "url": "https://www.youtube.com/embed/fc7VKrSvF_E", "duration": ""}]
    },
    {
      id: "practice-string-reverse",
      label: "Practice: String Reversing",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice problem \u2014 reversing strings with different techniques.",
      resources: [{"type": "video", "label": "Practice: String Reversing", "url": "https://www.youtube.com/embed/GSWETBkd6Ho", "duration": ""}]
    },
    {
      id: "practice-pattern-print",
      label: "Practice: Pattern Printing",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice problem \u2014 printing patterns using nested loops.",
      resources: [{"type": "video", "label": "Practice: Pattern Printing", "url": "https://www.youtube.com/embed/DY8N-xNhrsY", "duration": ""}]
    },
    {
      id: "practice-progress-bar",
      label: "Practice: Progress Bar",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice problem \u2014 implementing a simple progress bar using TQDM.",
      resources: [{"type": "video", "label": "Practice: Progress Bar", "url": "https://www.youtube.com/embed/v6r0GBcY730", "duration": ""}]
    },
    {
      id: "practice-animation",
      label: "Practice: Print Animation",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice problem \u2014 creating simple terminal animations with print.",
      resources: [{"type": "video", "label": "Practice: Print Animation", "url": "https://www.youtube.com/embed/vsaN5bgTBek", "duration": ""}]
    },
    {
      id: "practice-date-format",
      label: "Practice: Date Formatting",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice problem \u2014 converting date formats using string manipulation.",
      resources: [{"type": "video", "label": "Practice: Date Formatting", "url": "https://www.youtube.com/embed/eBLzUiQaeL8", "duration": ""}]
    },
    {
      id: "practice-problem-12",
      label: "Practice Problem 12",
      domain: "foundations",
      level: "beginner",
      summary: "Python coding practice problem to reinforce programming fundamentals.",
      resources: [{"type": "video", "label": "Practice Problem 12", "url": "https://www.youtube.com/embed/ubsN2Hy1XSs", "duration": ""}]
    },
    {
      id: "practice-if-else-in",
      label: "Practice: If Else with In",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 using the `in` operator with if-else for membership testing.",
      resources: [{"type": "video", "label": "Practice: If Else with In", "url": "https://www.youtube.com/embed/woMeFJEc-PE", "duration": ""}]
    },
    {
      id: "practice-dot-product",
      label: "Practice: Dot Product",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice problem \u2014 computing dot product of two vectors from scratch.",
      resources: [{"type": "video", "label": "Practice: Dot Product", "url": "https://www.youtube.com/embed/-tixNE3kOow", "duration": ""}]
    },
    {
      id: "practice-string-filter",
      label: "Practice: String Filter",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 filtering and reversing strings using list comprehension.",
      resources: [{"type": "video", "label": "Practice: String Filter", "url": "https://www.youtube.com/embed/ju_kpGWUtXE", "duration": ""}]
    },
    {
      id: "practice-split-reverse",
      label: "Practice: Split Reverse Join",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 splitting, reversing, and joining strings.",
      resources: [{"type": "video", "label": "Practice: Split Reverse Join", "url": "https://www.youtube.com/embed/wrJC-UX2-Ks", "duration": ""}]
    },
    {
      id: "practice-list-join",
      label: "Practice: List Joining",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 joining and appending list elements.",
      resources: [{"type": "video", "label": "Practice: List Joining", "url": "https://www.youtube.com/embed/prAOtxVu3p0", "duration": ""}]
    },
    {
      id: "practice-second-largest",
      label: "Practice: Second Largest",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 finding the second largest element in a list.",
      resources: [{"type": "video", "label": "Practice: Second Largest", "url": "https://www.youtube.com/embed/o_rVD3PxOrs", "duration": ""}]
    },
    {
      id: "practice-elementwise-sum",
      label: "Practice: Element-wise Sum",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 computing element-wise sum of two lists.",
      resources: [{"type": "video", "label": "Practice: Element-wise Sum", "url": "https://www.youtube.com/embed/UFK7VXpiKKs", "duration": ""}]
    },
    {
      id: "practice-mix-list",
      label: "Practice: Mix List Elements",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 mixing and interleaving list elements.",
      resources: [{"type": "video", "label": "Practice: Mix List Elements", "url": "https://www.youtube.com/embed/gxTnlJcUBOI", "duration": ""}]
    },
    {
      id: "practice-word-uppercase",
      label: "Practice: Word Uppercase",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 capitalizing words in a sentence.",
      resources: [{"type": "video", "label": "Practice: Word Uppercase", "url": "https://www.youtube.com/embed/tCR2vnFL2rM", "duration": ""}]
    },
    {
      id: "practice-unique-list",
      label: "Practice: Unique List",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 extracting unique elements from a list.",
      resources: [{"type": "video", "label": "Practice: Unique List", "url": "https://www.youtube.com/embed/BT4zynEm4Ts", "duration": ""}]
    },
    {
      id: "practice-problem-14",
      label: "Practice Problem 14",
      domain: "foundations",
      level: "beginner",
      summary: "Python coding practice to strengthen programming problem-solving skills.",
      resources: [{"type": "video", "label": "Practice Problem 14", "url": "https://www.youtube.com/embed/xhAvwPCQEMo", "duration": ""}]
    },
    {
      id: "practice-split-join-2",
      label: "Practice: Split Join",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 using split and join for string transformation.",
      resources: [{"type": "video", "label": "Practice: Split Join", "url": "https://www.youtube.com/embed/9j336gZt9wQ", "duration": ""}]
    },
    {
      id: "practice-map-function",
      label: "Practice: Map Function",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 applying map and lambda functions to lists.",
      resources: [{"type": "video", "label": "Practice: Map Function", "url": "https://www.youtube.com/embed/oKFLSPMSF9M", "duration": ""}]
    },
    {
      id: "practice-avg-numbers",
      label: "Practice: Average Numbers",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 computing the average of a list of numbers.",
      resources: [{"type": "video", "label": "Practice: Average Numbers", "url": "https://www.youtube.com/embed/B5nYGYBTHSI", "duration": ""}]
    },
    {
      id: "practice-railway-time",
      label: "Practice: Railway Time",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 converting 24-hour railway time to AM/PM format.",
      resources: [{"type": "video", "label": "Practice: Railway Time", "url": "https://www.youtube.com/embed/vfEM7CctN8s", "duration": ""}]
    },
    {
      id: "practice-median",
      label: "Practice: Statistical Median",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 computing the statistical median from scratch.",
      resources: [{"type": "video", "label": "Practice: Statistical Median", "url": "https://www.youtube.com/embed/Ge5MH_Wjmn8", "duration": ""}]
    },
    {
      id: "practice-type-conversion",
      label: "Practice: Type Conversion",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 using type conversion functions int, float, and str.",
      resources: [{"type": "video", "label": "Practice: Type Conversion", "url": "https://www.youtube.com/embed/FprG4mjUo0c", "duration": ""}]
    },
    {
      id: "practice-mode",
      label: "Practice: Statistical Mode",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 computing the statistical mode from a list of numbers.",
      resources: [{"type": "video", "label": "Practice: Statistical Mode", "url": "https://www.youtube.com/embed/Od9BpazCRVk", "duration": ""}]
    },
    {
      id: "practice-variance",
      label: "Practice: Variance",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 computing statistical variance from a list of numbers.",
      resources: [{"type": "video", "label": "Practice: Variance", "url": "https://www.youtube.com/embed/GVcXOT_Th6U", "duration": ""}]
    },
    {
      id: "practice-minmax-scaling",
      label: "Practice: Min-Max Scaling",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 implementing min-max feature scaling from scratch.",
      resources: [{"type": "video", "label": "Practice: Min-Max Scaling", "url": "https://www.youtube.com/embed/Kcgz1vdtkKU", "duration": ""}]
    },
    {
      id: "practice-countdown",
      label: "Practice: Reverse Countdown",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice \u2014 printing a reverse countdown using loops.",
      resources: [{"type": "video", "label": "Practice: Reverse Countdown", "url": "https://www.youtube.com/embed/Kcgz1vdtkKU", "duration": ""}]
    },
    {
      id: "practice-sigmoid",
      label: "Practice: Sigmoid Function",
      domain: "foundations",
      level: "intermediate",
      summary: "Python practice \u2014 implementing the sigmoid activation function from scratch.",
      resources: [{"type": "video", "label": "Practice: Sigmoid Function", "url": "https://www.youtube.com/embed/tf6KflwnTqI", "duration": ""}]
    },
    {
      id: "practice-problem-35",
      label: "Practice Problem 35",
      domain: "foundations",
      level: "beginner",
      summary: "Python coding practice to build programming confidence and speed.",
      resources: [{"type": "video", "label": "Practice Problem 35", "url": "https://www.youtube.com/embed/hc4zLXYo4EI", "duration": ""}]
    },
    {
      id: "vscode-extensions-1",
      label: "VS Code Extensions 1",
      domain: "tools",
      level: "beginner",
      summary: "Installing and using essential VS Code extensions for data science development.",
      resources: [{"type": "video", "label": "VS Code Extensions Part 1", "url": "https://www.youtube.com/embed/sqJhKbsZqtA", "duration": ""}]
    },
    {
      id: "vscode-extensions-2",
      label: "VS Code Extensions 2",
      domain: "tools",
      level: "beginner",
      summary: "More VS Code extensions for Python, linting, formatting and productivity.",
      resources: [{"type": "video", "label": "VS Code Extensions Part 2", "url": "https://www.youtube.com/embed/1XgCiD5QHQU", "duration": ""}]
    },
    {
      id: "vscode-extensions-3",
      label: "VS Code Extensions 3",
      domain: "tools",
      level: "beginner",
      summary: "Advanced VS Code extensions and configuration tips for ML engineers.",
      resources: [{"type": "video", "label": "VS Code Extensions Part 3", "url": "https://www.youtube.com/embed/rxhtjmuM6E0", "duration": ""}]
    },
    {
      id: "vscode-extensions-4",
      label: "VS Code Extensions 4",
      domain: "tools",
      level: "beginner",
      summary: "Final set of VS Code extensions covering data science workflow essentials.",
      resources: [{"type": "video", "label": "VS Code Walkthrough", "url": "https://www.youtube.com/embed/ZCn9dgRLQ_8", "duration": ""}]
    },
    {
      id: "practice-problem-7",
      label: "Practice Problem 7",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice problem to strengthen core programming skills.",
      resources: [{"type": "video", "label": "Python Practice Problem 7", "url": "https://www.youtube.com/embed/rFocOiHnbEs", "duration": ""}]
    },
    {
      id: "practice-problem-8",
      label: "Practice Problem 8",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice problem to reinforce data structures and logic.",
      resources: [{"type": "video", "label": "Python Practice Problem 8", "url": "https://www.youtube.com/embed/vsaN5bgTBek", "duration": ""}]
    },
    {
      id: "practice-problem-9",
      label: "Practice Problem 9",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice problem covering string and list operations.",
      resources: [{"type": "video", "label": "Python Practice Problem 9", "url": "https://www.youtube.com/embed/DY8N-xNhrsY", "duration": ""}]
    },
    {
      id: "practice-problem-10",
      label: "Practice Problem 10",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice problem building on functions and control flow.",
      resources: [{"type": "video", "label": "Python Practice Problem 10", "url": "https://www.youtube.com/embed/v6r0GBcY730", "duration": ""}]
    },
    {
      id: "practice-problem-11",
      label: "Practice Problem 11",
      domain: "foundations",
      level: "beginner",
      summary: "Python practice problem reinforcing Python fundamentals.",
      resources: [{"type": "video", "label": "Python Practice Problem 11", "url": "https://www.youtube.com/embed/fc7VKrSvF_E", "duration": ""}]
    },
    {
      id: "linear-regression-scratch",
      label: "Linear Regression Scratch",
      domain: "ml-core",
      level: "intermediate",
      summary: "Implementing linear regression from scratch in Python without scikit-learn.",
      resources: [{"type": "video", "label": "Linear Regression from Scratch", "url": "https://www.youtube.com/embed/_yiTZQ0vR60", "duration": ""}]
    },
    {
      id: "sigmoid-function",
      label: "Sigmoid Function",
      domain: "deep-learning",
      level: "beginner",
      summary: "Understanding and implementing the sigmoid activation function in Python.",
      resources: [{"type": "video", "label": "Sigmoid / Operator Overloading", "url": "https://www.youtube.com/embed/lal8F6H1bXc", "duration": ""}]
    },
    {
      id: "row-col-vectors",
      label: "Row & Column Vectors",
      domain: "foundations",
      level: "beginner",
      summary: "Row and column vector notation and their role in matrix operations.",
      resources: [{"type": "video", "label": "Row and Column Vectors", "url": "https://www.youtube.com/embed/JAdl83M-e_s", "duration": ""}]
    },
    {
      id: "matrix-multiplication",
      label: "Matrix Multiplication",
      domain: "foundations",
      level: "intermediate",
      summary: "What matrix multiplication actually means geometrically and computationally.",
      resources: [{"type": "video", "label": "Matrix Transformations", "url": "https://www.youtube.com/embed/MmL-KLK-a9c", "duration": ""}]
    },
    {
      id: "matrix-inverse",
      label: "Matrix Inverse",
      domain: "foundations",
      level: "intermediate",
      summary: "Computing and understanding the inverse of a matrix and when it exists.",
      resources: [{"type": "video", "label": "Inverse of a Matrix", "url": "https://www.youtube.com/embed/BSlbJ8gwZMM", "duration": ""}]
    },
    {
      id: "eigenvalues-vectors",
      label: "Eigenvalues & Eigenvectors",
      domain: "foundations",
      level: "intermediate",
      summary: "Eigenvalues and eigenvectors \u2014 the backbone of PCA and dimensionality reduction.",
      resources: [{"type": "video", "label": "Eigen Values and Eigen Vectors", "url": "https://www.youtube.com/embed/vrEPiB5-7d8", "duration": ""}]
    },
    {
      id: "visualizing-functions",
      label: "Visualizing Functions",
      domain: "foundations",
      level: "beginner",
      summary: "Plotting and visualizing mathematical functions to build intuition for ML.",
      resources: [{"type": "video", "label": "Visualizing Functions", "url": "https://www.youtube.com/embed/W7S4tFQxDWY", "duration": ""}]
    },
    {
      id: "concept-derivative",
      label: "Concept of Derivative",
      domain: "foundations",
      level: "intermediate",
      summary: "Understanding derivatives geometrically as the slope of a function at a point.",
      resources: [{"type": "video", "label": "Concept of Derivative", "url": "https://www.youtube.com/embed/JpQUtO09xi8", "duration": ""}]
    },
    {
      id: "infinity-infinitesimal",
      label: "Infinity & Infinitesimal",
      domain: "foundations",
      level: "intermediate",
      summary: "The ideas of infinity and infinitesimals that underpin calculus for ML.",
      resources: [{"type": "video", "label": "Idea of Infinity and Infinitesimal", "url": "https://www.youtube.com/embed/0IOfGyncK3g", "duration": ""}]
    },
    {
      id: "derivative-direction",
      label: "Derivative Direction",
      domain: "foundations",
      level: "intermediate",
      summary: "How derivatives point in the direction of steepest ascent \u2014 the basis of gradient descent.",
      resources: [{"type": "video", "label": "Direction in Derivative", "url": "https://www.youtube.com/embed/-rofr5JMOpU", "duration": ""}]
    },
    {
      id: "partial-derivative",
      label: "Partial Derivative",
      domain: "foundations",
      level: "intermediate",
      summary: "Partial derivatives and gradient vectors used in multi-variable optimization.",
      resources: [{"type": "video", "label": "Partial Derivative", "url": "https://www.youtube.com/embed/P8VbRBfEPXc", "duration": ""}]
    },
    {
      id: "descriptive-recap-1",
      label: "Descriptive Stats Recap 1",
      domain: "foundations",
      level: "beginner",
      summary: "Quick recap of key descriptive statistics concepts for data science.",
      resources: [{"type": "video", "label": "Intro to Descriptive Statistics", "url": "https://www.youtube.com/embed/8Q4oSDfhso8", "duration": ""}]
    },
    {
      id: "descriptive-recap-2",
      label: "Descriptive Stats Recap 2",
      domain: "foundations",
      level: "beginner",
      summary: "Continued recap of descriptive statistics including variance and standard deviation.",
      resources: [{"type": "video", "label": "Measures of Central Tendency", "url": "https://www.youtube.com/embed/Q3WDm0OV_DY", "duration": ""}]
    },
    {
      id: "central-tendency",
      label: "Measures of Central Tendency",
      domain: "foundations",
      level: "beginner",
      summary: "Mean, median, and mode \u2014 the three measures of central tendency explained visually.",
      resources: [{"type": "video", "label": "Measures of Central Tendency", "url": "https://www.youtube.com/embed/Q3WDm0OV_DY", "duration": ""}]
    },
    {
      id: "percentiles-quartiles",
      label: "Percentiles & Quartiles",
      domain: "foundations",
      level: "beginner",
      summary: "Understanding percentiles, quartiles, and IQR for data distribution analysis.",
      resources: [{"type": "video", "label": "Percentiles and Quartiles", "url": "https://www.youtube.com/embed/5Zb8EExsXsI", "duration": ""}]
    },
    {
      id: "outlier-detection",
      label: "Outlier Detection",
      domain: "foundations",
      level: "beginner",
      summary: "Finding outliers using quartiles and the IQR method in Python.",
      resources: [{"type": "video", "label": "Finding Outliers Using Quartiles", "url": "https://www.youtube.com/embed/sK0QbCA81Fg", "duration": ""}]
    },
    {
      id: "measures-dispersion",
      label: "Measures of Dispersion",
      domain: "foundations",
      level: "beginner",
      summary: "Range, variance, standard deviation, and z-score for measuring data spread.",
      resources: [{"type": "video", "label": "Measures of Dispersion", "url": "https://www.youtube.com/embed/LumyZy9-MLk", "duration": ""}]
    },
    {
      id: "correlation-causation",
      label: "Correlation vs Causation",
      domain: "foundations",
      level: "beginner",
      summary: "Why correlation does not imply causation \u2014 a critical concept for data analysis.",
      resources: [{"type": "video", "label": "Correlation vs Causation", "url": "https://www.youtube.com/embed/gh1MV72Otm0", "duration": ""}]
    },
    {
      id: "html-css-1",
      label: "HTML & CSS Part 1",
      domain: "tools",
      level: "beginner",
      summary: "Introduction to HTML structure and CSS styling for building ML web interfaces.",
      resources: [{"type": "video", "label": "HTML & CSS Part 1", "url": "https://www.youtube.com/embed/vLOltaWPIz0", "duration": ""}]
    },
    {
      id: "html-css-2",
      label: "HTML & CSS Part 2",
      domain: "tools",
      level: "beginner",
      summary: "HTML forms, tables, and CSS layouts for data science web applications.",
      resources: [{"type": "video", "label": "HTML & CSS Part 2", "url": "https://www.youtube.com/embed/T-18Cpclsn4", "duration": ""}]
    },
    {
      id: "html-css-3",
      label: "HTML & CSS Part 3",
      domain: "tools",
      level: "beginner",
      summary: "Responsive CSS design and flexbox for building ML dashboards.",
      resources: [{"type": "video", "label": "HTML & CSS Part 3", "url": "https://www.youtube.com/embed/vuR0nGMnytE", "duration": ""}]
    },
    {
      id: "html-css-4",
      label: "HTML & CSS Part 4",
      domain: "tools",
      level: "beginner",
      summary: "JavaScript integration with HTML/CSS for interactive ML web apps.",
      resources: [{"type": "video", "label": "HTML & CSS Part 4", "url": "https://www.youtube.com/embed/xF_q_XAP4g4", "duration": ""}]
    },
    {
      id: "thinking-tools-1",
      label: "Thinking Tools 1",
      domain: "tools",
      level: "beginner",
      summary: "Mental models and thinking frameworks for problem-solving in data science.",
      resources: [{"type": "video", "label": "DS/ML Libraries Overview", "url": "https://www.youtube.com/embed/gABxNYVrLKg", "duration": ""}]
    },
    {
      id: "dsml-libraries-intro",
      label: "DSML Libraries Intro",
      domain: "tools",
      level: "beginner",
      summary: "Introduction to the Python data science and ML library ecosystem.",
      resources: [{"type": "video", "label": "Introduction to DSML Python Libraries", "url": "https://www.youtube.com/embed/gABxNYVrLKg", "duration": ""}]
    },
    {
      id: "ai4bharat",
      label: "AI 4 Bharat",
      domain: "tools",
      level: "beginner",
      summary: "Overview of AI initiatives and resources for the Indian developer community.",
      resources: [{"type": "video", "label": "AI 4 Bharat / DSML Libraries", "url": "https://www.youtube.com/embed/gABxNYVrLKg", "duration": ""}]
    },
    {
      id: "flask-1",
      label: "Flask Part 1",
      domain: "mlops",
      level: "intermediate",
      summary: "Introduction to Flask web framework for deploying ML models as web apps.",
      resources: [{"type": "video", "label": "Flask for DSML Part 1", "url": "https://www.youtube.com/embed/lG3RgrzppnI", "duration": ""}]
    },
    {
      id: "model-metrics",
      label: "Model Performance Metrics",
      domain: "ml-core",
      level: "beginner",
      summary: "Accuracy, precision, recall, F1-score \u2014 evaluating ML model performance.",
      resources: [{"type": "video", "label": "Model Performance Metrics / Feature Engineering", "url": "https://www.youtube.com/embed/KP_05zKgj98", "duration": ""}]
    },
    {
      id: "flask-2",
      label: "Flask Part 2",
      domain: "mlops",
      level: "intermediate",
      summary: "Flask routing, templates, and handling POST requests for ML applications.",
      resources: [{"type": "video", "label": "Flask for DSML Part 2", "url": "https://www.youtube.com/embed/_GNoYvanXYo", "duration": ""}]
    },
    {
      id: "flask-3",
      label: "Flask Part 3",
      domain: "mlops",
      level: "intermediate",
      summary: "Flask forms and user input handling for interactive ML prediction apps.",
      resources: [{"type": "video", "label": "Flask for DSML Part 3", "url": "https://www.youtube.com/embed/EH4u8hAjm2A", "duration": ""}]
    },
    {
      id: "flask-4",
      label: "Flask Part 4",
      domain: "mlops",
      level: "intermediate",
      summary: "Flask blueprints and project structure for production ML web apps.",
      resources: [{"type": "video", "label": "Flask for DSML Part 4", "url": "https://www.youtube.com/embed/MNQkSF8h6wo", "duration": ""}]
    },
    {
      id: "flask-6",
      label: "Flask Part 6",
      domain: "mlops",
      level: "intermediate",
      summary: "Flask database integration and session management for ML applications.",
      resources: [{"type": "video", "label": "Flask for DSML Part 6", "url": "https://www.youtube.com/embed/flOKENTLw1k", "duration": ""}]
    },
    {
      id: "flask-7",
      label: "Flask Part 7",
      domain: "mlops",
      level: "intermediate",
      summary: "Deploying Flask ML applications to cloud platforms.",
      resources: [{"type": "video", "label": "Flask for DSML Part 7", "url": "https://www.youtube.com/embed/-vPwKsyC0LA", "duration": ""}]
    },
    {
      id: "flask-8",
      label: "Flask Part 8",
      domain: "mlops",
      level: "intermediate",
      summary: "Flask REST APIs and JSON responses for serving ML model predictions.",
      resources: [{"type": "video", "label": "Flask for DSML Part 8", "url": "https://www.youtube.com/embed/63Drf-skV3A", "duration": ""}]
    },
    {
      id: "streamlit-1",
      label: "Streamlit Part 1",
      domain: "mlops",
      level: "intermediate",
      summary: "Building interactive ML dashboards with Streamlit in pure Python.",
      resources: [{"type": "video", "label": "Streamlit for DSML Part 1", "url": "https://www.youtube.com/embed/bWasfCZHo-g", "duration": ""}]
    },
    {
      id: "numpy-random",
      label: "NumPy Random Module",
      domain: "foundations",
      level: "beginner",
      summary: "Key functions in NumPy's random module for data generation and ML experiments.",
      resources: [{"type": "video", "label": "NumPy Tutorial", "url": "https://www.youtube.com/embed/XC0oFw84Oz8", "duration": ""}]
    },
    {
      id: "streamlit-2",
      label: "Streamlit Part 2",
      domain: "mlops",
      level: "intermediate",
      summary: "Adding charts, widgets, and file uploads to Streamlit ML apps.",
      resources: [{"type": "video", "label": "Streamlit for DSML Part 2", "url": "https://www.youtube.com/embed/ss6KOS7fI64", "duration": ""}]
    },
    {
      id: "activation-functions-dl",
      label: "Activation Functions DL",
      domain: "deep-learning",
      level: "intermediate",
      summary: "ReLU, sigmoid, tanh, and softmax activation functions in deep learning.",
      resources: [{"type": "video", "label": "Activation Functions / Sigmoid", "url": "https://www.youtube.com/embed/lal8F6H1bXc", "duration": ""}]
    },
    {
      id: "streamlit-3",
      label: "Streamlit Part 3",
      domain: "mlops",
      level: "intermediate",
      summary: "Deploying Streamlit apps and integrating trained scikit-learn models.",
      resources: [{"type": "video", "label": "Streamlit for DSML Part 3", "url": "https://www.youtube.com/embed/gOvNATdGFbo", "duration": ""}]
    },
    {
      id: "fastapi-1",
      label: "FastAPI Part 1",
      domain: "mlops",
      level: "intermediate",
      summary: "Building your first REST API with FastAPI to serve ML model predictions.",
      resources: [{"type": "video", "label": "FastAPI for DSML Part 1", "url": "https://www.youtube.com/embed/aAnQj2jfufk", "duration": ""}]
    },
    {
      id: "why-databases",
      label: "Why Databases?",
      domain: "tools",
      level: "beginner",
      summary: "Why relational databases are better than flat files for data science workflows.",
      resources: [{"type": "video", "label": "Pandas / Database Intro", "url": "https://www.youtube.com/embed/0SPB2VhpoNY", "duration": ""}]
    },
    {
      id: "python-libraries-intro",
      label: "Python Libraries Intro",
      domain: "tools",
      level: "beginner",
      summary: "Overview of core Python libraries: NumPy, Pandas, Matplotlib, Scikit-learn.",
      resources: [{"type": "video", "label": "Intro to Python Libraries", "url": "https://www.youtube.com/embed/gABxNYVrLKg", "duration": ""}]
    },
    {
      id: "reading-text-files",
      label: "Reading Text Files",
      domain: "tools",
      level: "beginner",
      summary: "Reading raw text files in Python using built-in file I/O functions.",
      resources: [{"type": "video", "label": "Python Writing Raw Text Files", "url": "https://www.youtube.com/embed/3cJMqHyaKGU", "duration": ""}]
    },
    {
      id: "numpy-part-2",
      label: "NumPy Part 2",
      domain: "foundations",
      level: "intermediate",
      summary: "Advanced NumPy \u2014 array operations, broadcasting, linear algebra functions.",
      resources: [{"type": "video", "label": "NumPy Part 2 / Tutorial", "url": "https://www.youtube.com/embed/XC0oFw84Oz8", "duration": ""}]
    },
    {
      id: "pyyaml-reading",
      label: "PyYAML Config Reading",
      domain: "tools",
      level: "beginner",
      summary: "Reading YAML configuration files in Python using PyYAML for ML project setup.",
      resources: [{"type": "video", "label": "Reading Configuration Values in Python Using PyYAML", "url": "https://www.youtube.com/embed/A5GoYjlDVVY", "duration": ""}]
    },
    {
      id: "channel-promo",
      label: "Channel Promo",
      domain: "tools",
      level: "beginner",
      summary: "Introduction to the Machine Learning Malayalam YouTube channel.",
      resources: [{"type": "video", "label": "Data Science Tools / Channel Promo", "url": "https://www.youtube.com/embed/_fuAooCJTpA", "duration": ""}]
    },
    {
      id: "channel-intro",
      label: "Channel Introduction",
      domain: "tools",
      level: "beginner",
      summary: "Why Sajil started the Machine Learning Malayalam channel and the roadmap.",
      resources: [{"type": "video", "label": "Introduction to the Channel", "url": "https://www.youtube.com/embed/_fuAooCJTpA", "duration": ""}]
    }
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    { source: "version-control", target: "colab-github-workflow" },
    { source: "pymupdf-pdf-reading", target: "qwen-grader-demo" },
    { source: "python-numeric", target: "pandas-intro" },
    { source: "map-of-mathematics", target: "intro-probability" },
    { source: "intro-probability", target: "key-terms-probability" },
    { source: "key-terms-probability", target: "joint-conditional-prob" },
    { source: "joint-conditional-prob", target: "inferential-statistics" },
    { source: "inferential-statistics", target: "gaussian-distribution" },
    { source: "python-functions", target: "list-comprehension" },
    { source: "python-lists", target: "list-comprehension" },
    { source: "map-of-mathematics", target: "descriptive-stats" },
    { source: "math-for-dsml", target: "map-of-mathematics" },
    { source: "python-functions", target: "python-files-read" },
    { source: "python-files-read", target: "python-files-write" },
    { source: "python-functions", target: "generic-python-1" },
    { source: "generic-python-1", target: "generic-python-2" },
    { source: "python-strings", target: "practice-vowel-print" },
    { source: "python-functions", target: "practice-otp" },
    { source: "python-functions", target: "practice-string-reverse" },
    { source: "python-functions", target: "practice-pattern-print" },
    { source: "python-functions", target: "practice-progress-bar" },
    { source: "python-functions", target: "practice-date-format" },
    { source: "python-functions", target: "practice-animation" },
    { source: "python-functions", target: "practice-problem-12" },
    { source: "python-functions", target: "practice-if-else-in" },
    { source: "python-functions", target: "practice-problem-14" },
    { source: "python-functions", target: "practice-split-join-2" },
    { source: "python-functions", target: "practice-railway-time" },
    { source: "python-functions", target: "practice-type-conversion" },
    { source: "python-functions", target: "practice-dot-product" },
    { source: "python-functions", target: "practice-string-filter" },
    { source: "python-functions", target: "practice-split-reverse" },
    { source: "python-functions", target: "practice-list-join" },
    { source: "python-functions", target: "practice-second-largest" },
    { source: "python-functions", target: "practice-elementwise-sum" },
    { source: "python-functions", target: "practice-mix-list" },
    { source: "python-functions", target: "practice-word-uppercase" },
    { source: "python-functions", target: "practice-unique-list" },
    { source: "python-functions", target: "practice-map-function" },
    { source: "python-functions", target: "practice-avg-numbers" },
    { source: "python-functions", target: "practice-median" },
    { source: "python-functions", target: "practice-mode" },
    { source: "python-functions", target: "practice-variance" },
    { source: "python-functions", target: "practice-minmax-scaling" },
    { source: "python-functions", target: "practice-countdown" },
    { source: "python-functions", target: "practice-sigmoid" },
    { source: "python-functions", target: "practice-problem-35" },
    { source: "vscode-intro", target: "vscode-extensions-1" },
    { source: "vscode-extensions-1", target: "vscode-extensions-2" },
    { source: "vscode-extensions-2", target: "vscode-extensions-3" },
    { source: "vscode-extensions-3", target: "vscode-extensions-4" },
    { source: "descriptive-stats", target: "descriptive-recap-1" },
    { source: "descriptive-recap-1", target: "descriptive-recap-2" },
    { source: "descriptive-recap-2", target: "central-tendency" },
    { source: "central-tendency", target: "percentiles-quartiles" },
    { source: "percentiles-quartiles", target: "outlier-detection" },
    { source: "descriptive-stats", target: "measures-dispersion" },
    { source: "descriptive-stats", target: "correlation-causation" },
    { source: "row-col-vectors", target: "matrix-multiplication" },
    { source: "matrix-multiplication", target: "matrix-inverse" },
    { source: "matrix-inverse", target: "eigenvalues-vectors" },
    { source: "why-functions", target: "visualizing-functions" },
    { source: "visualizing-functions", target: "concept-derivative" },
    { source: "concept-derivative", target: "infinity-infinitesimal" },
    { source: "concept-derivative", target: "derivative-direction" },
    { source: "derivative-direction", target: "partial-derivative" },
    { source: "python-functions", target: "practice-problem-7" },
    { source: "python-functions", target: "practice-problem-8" },
    { source: "python-functions", target: "practice-problem-9" },
    { source: "python-functions", target: "practice-problem-10" },
    { source: "python-functions", target: "practice-problem-11" },
    { source: "python-functions", target: "flask-1" },
    { source: "flask-1", target: "flask-2" },
    { source: "flask-2", target: "flask-3" },
    { source: "flask-3", target: "flask-4" },
    { source: "flask-4", target: "flask-6" },
    { source: "flask-6", target: "flask-7" },
    { source: "flask-7", target: "flask-8" },
    { source: "flask-1", target: "fastapi-1" },
    { source: "fastapi-1", target: "streamlit-1" },
    { source: "streamlit-1", target: "streamlit-2" },
    { source: "streamlit-2", target: "streamlit-3" },
    { source: "html-css-1", target: "html-css-2" },
    { source: "html-css-2", target: "html-css-3" },
    { source: "html-css-3", target: "html-css-4" },
    { source: "html-css-4", target: "flask-1" },
    { source: "numpy-intro", target: "numpy-part-2" },
    { source: "numpy-intro", target: "numpy-random" },
    { source: "ds-installation", target: "python-libraries-intro" },
    { source: "python-libraries-intro", target: "dsml-libraries-intro" },
    { source: "pandas-intro", target: "why-databases" },
    { source: "python-files-read", target: "reading-text-files" },
    { source: "linear-regression-intuition", target: "linear-regression-scratch" },
    { source: "sigmoid-function", target: "activation-functions-dl" }
  ]

};