AI Learning Roadmap from Beginners to Experts - Getting Started from 2025

(AI Artificial Intelligence, a new coming future world from 2025)

Phase 1: Pre-requisite Maths Foundations

  •  Calculus (4 to 6 weeks)
    • Goals: Understand derivatives, integrals, and fundamental theorems. 
    • Stanford Classes: Maths 19-21
    • Free Resources (any one): 
      • KhanAcademyCalculus: Khan Academy Calculus 
      • MITOpenCourseWareSingle Variable Calculus
    • Book Recommended: 
      • Calculus for Dummies
  • Linear Algebra (4 to 6 weeks)
    • Goals: Master matrix operations, vector spaces, and linear transformations. 
    • Stanford Classes: Matrix Math104, MATH113, CS205L 
    • ○ Free Classes/Resources (any one below): 
      • KhanAcademyLinear Algebra 
      • MIT OpenCourseWare Introduction to Linear Algebra 
      • Book: A First Course in Probability, by Sheldon Ross, Pearson
  • All in one course: Mathematics for Machine Learning and Data Science Specialization 
    • Linear Algebra for Machine Learning and Data Science 
    • Calculus for Machine Learning and Data Science www.exaltitude.io 
    • ● www.youtube.com/@exaltitude ● jean@exaltitude.io○ Probability & Statistics for Machine Learning & Data Science


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Phase 2: Programming Fundamentals

              ((----- CS193 Summary Start - Linux Commands -----))










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