6 Lessons
All Levels (AI Foundations)
★ 4.96
(3,600+ Engineers Enrolled)
Mathematics, Statistics & Machine Learning (Big Tech Prep)
Linear Algebra, Multivariate Calculus, Probability Distributions, Scikit-Learn & Optimization
⏱️ 35 Hours
📖 5 Modules
⚡ 18 Interactive Lessons
🏆 Free Verified Certificate
Complete Track Curriculum & Modules
Step-by-step interactive lessons with live browser compilers & coding assignments.
18 Lessons
1
4 Lessons
Module 1: Linear Algebra for Machine Learning & Deep Learning
01. Vectors, Vector Spaces, Dot Products & Norms (L1, L2, L-Infinity) in High Dimensions
⏱️ 45 mins
•
⚡ Interactive Sandbox
02. Matrices, Matrix Multiplication & Linear Transformations (Rotation, Scaling, Shear)
⏱️ 45 mins
•
⚡ Interactive Sandbox
03. Eigenvalues & Eigenvectors: Geometric Intuition, Diagonalization & Spectral Theorem
⏱️ 50 mins
•
⚡ Interactive Sandbox
04. Principal Component Analysis (PCA) & Singular Value Decomposition (SVD) Math
⏱️ 50 mins
•
⚡ Interactive Sandbox
2
4 Lessons
Module 2: Multivariable Calculus, Gradients & Optimization Algorithms
05. Partial Derivatives, Directional Derivatives & The Gradient Vector (Del Operator)
⏱️ 45 mins
•
⚡ Interactive Sandbox
06. The Jacobian Matrix & Hessian Matrix (Second Derivative Curvature Analysis)
⏱️ 50 mins
•
⚡ Interactive Sandbox
07. Multivariate Chain Rule & The Mathematical Backbone of Neural Backpropagation
⏱️ 50 mins
•
⚡ Interactive Sandbox
08. Optimization Algorithms: Gradient Descent, SGD with Momentum, RMSprop & Adam Optimizer Math
⏱️ 50 mins
•
⚡ Interactive Sandbox
3
3 Lessons
Module 3: Probability Theory & Random Variables
09. Probability Foundations: Axioms of Probability, Conditional Probability & Independence
⏱️ 40 mins
•
⚡ Interactive Sandbox
10. Bayes' Theorem & Bayesian Inference: Prior, Likelihood, Posterior & Evidence
⏱️ 45 mins
•
⚡ Interactive Sandbox
11. Probability Distributions: Gaussian (Normal), Bernoulli, Binomial, Poisson & Exponential Distributions
⏱️ 45 mins
•
⚡ Interactive Sandbox
4
4 Lessons
Module 4: Inferential Statistics & Hypothesis Testing
12. Expectation, Variance, Covariance & Pearson Correlation Coefficient
⏱️ 40 mins
•
⚡ Interactive Sandbox
13. Law of Large Numbers & Central Limit Theorem (CLT) with Monte Carlo Simulations
⏱️ 45 mins
•
⚡ Interactive Sandbox
14. Hypothesis Testing: Null Hypothesis, p-Values, Z-Test, Student's t-Test & Chi-Square Test
⏱️ 45 mins
•
⚡ Interactive Sandbox
15. Maximum Likelihood Estimation (MLE) vs Maximum A Posteriori (MAP) Estimation
⏱️ 50 mins
•
⚡ Interactive Sandbox
5
3 Lessons
Module 5: Classical Machine Learning Algorithms from Scratch (NumPy)
16. Linear Regression from Scratch: Ordinary Least Squares (OLS) Closed Form vs Gradient Descent
⏱️ 50 mins
•
⚡ Interactive Sandbox
17. Logistic Regression & Binary Cross-Entropy Loss from Scratch with NumPy
⏱️ 50 mins
•
⚡ Interactive Sandbox
18. Regularization Mathematics: L1 Lasso (Sparsity) vs L2 Ridge (Weight Decay) Penalties
⏱️ 45 mins
•
⚡ Interactive Sandbox
Target Big Tech Roles
Google / Meta SDE-2
Senior Full-Stack Architect
Lead Backend Engineer
Skills You Will Master
- Production-Grade Clean Architecture
- V8 Internals, Memory Profiling & Leaks
- Time & Space Complexity Optimization
- Big Tech Behavioral & System Design Edge
Verified Digital Certificate
Complete all 18 lessons to earn a verifiable certificate with unique validation hash for LinkedIn.
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⚡
Live Interactive Sandbox
Test real-time code without installing Node, Python or C++ locally. Instant output in browser!
Launch Code Sandbox (8-in-1)