Deep Learning Masterclass
Complete Zero to Hero journey. CNNs, RNNs, Transformers, GANs, Diffusion Models, plus GenAI essentials: RAG, Vector Databases, LoRA & Quantization. Featuring rigorous "Paper & Pain" math and interactive visualizations.
Machine Learning Complete
The foundation. Regression, Classification, Clustering, SVMs, Decision Trees, and Ensembles. Master Scikit-Learn with complete mathematical derivations.
Statistics Complete
Descriptive and Inferential Statistics. Hypothesis testing, Distributions, P-values, and Bayesian concepts. 41 interactive topics.
Mathematics for AI
Calculus, Linear Algebra, and Probability. The engine room of AI. Derivatives, Matrix Operations, and Eigenvalues.
Feature Engineering
Data cleaning, transformation, scaling, encoding, and selection. The art of preparing data for models.
Data Visualization
Matplotlib, Seaborn, Plotly. Communicating insights effectively through beautiful charts and dashboards.
Prompt Engineering
Mastering LLMs. Zero-shot, Few-shot, Chain-of-Thought, plus Claude, Gemini & OpenAI provider-specific techniques.
ML Experiments & Data
Hands-on laboratory for datasets, experimental scripts, and practical ML applications.
Azure DevOps & MLOps
Master DevOps fundamentals, CI/CD pipelines, Kubernetes, and MLOps automation for production ML systems.
Python for Data Science & AI
Complete Python masterclass from fundamentals to production—NumPy, Pandas, PyTorch, TensorFlow, and optimization.