What You Need to Do

  • Learn Python programming basics: variables, data types, control structures, functions
  • Study essential mathematical concepts: linear algebra, calculus, probability, and statistics
  • Practice data manipulation with libraries like NumPy and Pandas
  • Learn data visualization with Matplotlib and Seaborn
  • Understand basic data preprocessing and cleaning techniques
  • Complete small coding challenges on platforms like HackerRank or LeetCode

Learning Roadmap

Weeks 1-2

Python basics (syntax, variables, data types, control flow)

Weeks 3-4

Functions, modules, error handling, and basic algorithms

Weeks 5-6

Mathematics review (linear algebra, calculus, statistics)

Weeks 7-8

Data manipulation with NumPy and Pandas

Mathematics Fundamentals

  • Linear Algebra: Vectors, matrices, matrix operations (crucial for understanding how neural networks process data)
  • Calculus: Derivatives, gradients (essential for understanding optimization algorithms)
  • Probability & Statistics: Basic probability, distributions, statistical measures (mean, median, variance)
  • Basic optimization concepts