Core Foundations
Python, linear algebra, calculus, and classical ML.
Python Programming Foundations
Python syntax, data structures, object-oriented patterns, and scientific computing basics.
3 Courses
Math for Machine Learning
Linear algebra, vector spaces, matrix factorizations (SVD/eigendecomposition), and calculus.
5 Courses
Data Cleaning and Prep
Data pipelines, missing value imputation, outlier detection, and feature engineering.
3 Courses
Probability for Data Science
Probability distributions, Bayes' theorem, maximum likelihood estimation, and hypothesis testing.
3 Courses
Introduction to Computer Vision
Convolutional kernels, image transformations, feature spaces, and vision backbones.
3 Courses
Full Stack AI Engineer
End-to-end AI application architecture: API contracts, backend integration, and stateful model serving.
5 Courses
Complete Data Science Path
Exploratory data analysis, statistical inference, feature importance, and predictive modeling.
5 Courses
Applied NLP
Tokenization algorithms, Word2Vec/GloVe embeddings, recurrent architectures, and self-attention.
3 Courses
AI Product Manager Essentials
Model sizing trade-offs, inference economics, evaluation criteria, and technical scoping.
4 Courses