AI ML

Descriptive Statistics · Probability Theory · Probability Distributions · Sampling and Experimental Design · Inferential Statistics · Statistical Modeling · Time Series Analysis

Problem Types · Model Families · Core Algorithms · Multi-Class And Multi-Label Strategies · Ensemble Methods · Model Development · Model Evaluation · Imbalanced And Cost-Sensitive Learning · Interpretability And Explainability

Problem Types · Clustering Algorithms · Dimensionality Reduction · Density Estimation · Anomaly Detection · Association Rule Learning · Representation Learning · Model Development · Evaluation

Neural Network Basics · Activation Functions · Weight Initialization · Backpropagation · Optimizers · Regularization & Normalization · Convolutional Networks · Recurrent Networks (RNN/LSTM) · Transformer (Foundations)

RL Paradigms · Exploration vs Exploitation · Multi-Armed Bandits · Tabular Methods · Function Approximation · Deep Reinforcement Learning · Model-Based RL · Reward Engineering & Imitation · Extensions & Variants · RL Frameworks & Environments · Applications

Image Preprocessing · Classical CV · CNN Architectures · Recognition Tasks · Object Detection · Segmentation · Transfer Learning · Vision Transformers · Video Understanding · 3D Vision

Hyperparameter Optimization Libraries · Neural Architecture Search · Automated Feature Engineering · Automated Pipeline Construction · Model Selection & Ensembling · AutoML Frameworks (Open Source) · AutoML Platforms (Cloud) · Meta-Learning · Evaluation in AutoML · Applications

Edge Hardware · Model Optimization for Edge · Compilation & Runtimes · Deployment & Operations · Device & Workload Classes · Privacy & Security at Edge · Performance & Benchmarking · Applications

Agent Design & Reasoning · Tools & Interoperability · Multi-Agent Coordination · Building & Operating Agents · Evaluation & Safety · Specialised Agents & Applications

Problem Formulations · Collaborative Filtering · Matrix Factorization · Content-Based Filtering · Context-Aware Recommendation · Hybrid Approaches · Deep Learning for RecSys · Ranking, Retrieval & Serving · Cold Start & Sparsity · Evaluation · Bias, Fairness & Privacy · Attacks & Robustness