Zero to AI
A beginner-to-practitioner path for AI newcomers. Go from your first line of Python to building, deploying, and responsibly shipping ML, deep learning, and LLM systems.
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01 Programming & Software Engineering Basics Set up a professional dev environment and write clean, version-controlled Python code. 02 Mathematics for Machine Learning Build the linear algebra, calculus, and statistics intuition that every ML algorithm relies on. 03 Data Engineering & Preprocessing Collect, store, clean, and explore data so it is ready for modeling. 04 Classical Machine Learning Train, tune, and evaluate core supervised and unsupervised algorithms with scikit-learn. 05 Deep Learning Foundations Learn how neural networks and transformers work, then train them efficiently with modern frameworks. 06 Computer Vision Process images and build CNN and transformer models for classification, detection, and generation. 07 Natural Language Processing Turn text into features and build modern language applications with LLMs, RAG, and agents. 08 Reinforcement Learning Learn how agents improve from rewards, from tabular methods to deep RL and LLM alignment. 09 MLOps & Responsible AI Deploy, monitor, and govern models in production while keeping them fair, explainable, and secure. 10 Capstone Projects & Career Apply everything in end-to-end projects, build a portfolio, and prepare for AI job interviews. Zero to AI A beginner-to-practitioner path for AI newcomers. Go from your first line of Python to building, deploying, and responsibly shipping ML, deep learning, and LLM systems. 10 STAGES · 34 TOPICS · 90 SUBTOPICS 1.1 Development Environment Setup Terminal and Command Line Bash · Shell Scripting · File Navigation Environment Management uv · pip · venv · Conda IDEs and Tooling VS Code · Jupyter Notebooks · AI Coding Assistants 1.2 Introduction to Programming Python Basics Variables · Data Types · Loops · Conditionals · Functions Advanced Python OOP · Decorators · Generators · Error Handling · Comprehensions 1.3 Software Engineering Practices Git and Version Control Branching · Merging · Pull Requests · GitHub Actions Data Structures & Algorithms Big O Notation · Hash Tables · Trees · Graphs APIs and Web Interaction REST APIs · HTTP Requests · Web Scraping · BeautifulSoup 2.1 Linear Algebra Vectors and Matrices Dot Product · Matrix Multiplication · Determinants · Norms Matrix Decompositions Eigenvalues · Eigenvectors · SVD · PCA Math 2.2 Calculus Differential Calculus Derivatives · Chain Rule · Partial Derivatives · Gradients Optimization Gradient Descent · Convexity · Jacobians · Hessians 2.3 Probability and Statistics Probability Theory Random Variables · Distributions · Bayes' Theorem · Expected Value Statistical Inference Hypothesis Testing · P-values · Confidence Intervals · A/B Testing 3.1 Data Collection and Storage Relational Databases SQL Queries · Joins · Aggregations · Normalization NoSQL Databases MongoDB · Key-Value Stores · Document Stores Big Data Ecosystems Apache Spark · Kafka · Parquet · Delta Lake 3.2 Data Manipulation and Analysis NumPy N-dimensional Arrays · Broadcasting · Vectorization · Indexing Pandas and Polars DataFrames · GroupBy · Merging · Pivot Tables Data Cleaning Missing Values · Outlier Detection · Imputation · Scaling 3.3 Data Visualization and EDA Static Visualization Matplotlib · Seaborn · Distributions · Correlations Interactive Visualization Plotly · Streamlit · Dash · Bokeh Exploratory Data Analysis Data Profiling · Feature Selection · Feature Engineering 4.1 Supervised Learning Linear Models Linear Regression · Logistic Regression · Cost Functions Support Vector Machines Kernels · Margin Maximization · Hyperplanes Tree-Based Models Decision Trees · Random Forests · Gradient Boosting · XGBoost · LightGBM Probabilistic and Instance-Based Naive Bayes · k-Nearest Neighbors · Distance Metrics 4.2 Unsupervised Learning Clustering K-Means · Hierarchical Clustering · DBSCAN · Silhouette Score Dimensionality Reduction PCA · t-SNE · UMAP Association Rule Learning Apriori · Eclat · FP-Growth 4.3 Model Evaluation and Selection Classification Metrics Precision · Recall · F1-Score · ROC-AUC · Confusion Matrix Regression Metrics RMSE · MAE · R-Squared · Adjusted R-Squared Cross-Validation and Tuning K-Fold · Stratified K-Fold · Grid Search · Optuna 5.1 Artificial Neural Networks Network Architecture Neurons · Hidden Layers · Weights and Biases · Feedforward Activation Functions Sigmoid · Tanh · ReLU · Leaky ReLU · Softmax Training Neural Networks Loss Functions · Backpropagation · SGD · Adam Regularization Dropout · Batch Normalization · Weight Decay · Early Stopping Autoencoders Latent Space · Denoising Autoencoders · Variational Autoencoders 5.2 Deep Learning Frameworks PyTorch Tensors · Autograd · nn.Module · DataLoaders · Custom Datasets TensorFlow and Keras Keras 3 · Model Subclassing · Callbacks · TensorBoard Hardware Acceleration CUDA · GPUs · TPUs · Mixed Precision Training 5.3 Attention and Transformers Attention Mechanism Self-Attention · Multi-Head Attention · Positional Encoding Transformer Architecture Encoder-Decoder · Encoder-Only · Decoder-Only 6.1 Image Processing Fundamentals Core Techniques Filtering · Edge Detection · Color Spaces · Morphology Classical Computer Vision OpenCV · SIFT · ORB · HOG 6.2 Convolutional Neural Networks CNN Building Blocks Convolutions · Pooling · Stride and Padding · Receptive Fields Landmark Architectures ResNet · Inception · EfficientNet · MobileNet · ConvNeXt 6.3 Advanced CV Applications Object Detection YOLO · SSD · Faster R-CNN · RetinaNet · DETR Image Segmentation U-Net · Mask R-CNN · Semantic Segmentation · Instance Segmentation · SAM Vision Transformers ViT · Swin Transformer · DINOv2 Generative Vision Models GANs · Diffusion Models · Stable Diffusion 7.1 Text Processing Fundamentals Text Preprocessing Tokenization · Stemming · Lemmatization · POS Tagging · Regex Statistical Text Features Bag of Words · TF-IDF · N-grams · Stopwords 7.2 Sequence Models and Embeddings Word Embeddings Word2Vec · GloVe · FastText Recurrent Models RNNs · LSTMs · GRUs · Seq2Seq Models 7.3 Large Language Models Leading Model Families BERT · GPT · Llama · Gemini · Claude Prompt Engineering Zero-Shot · Few-Shot · Chain-of-Thought · Structured Outputs Fine-Tuning LLMs Full Fine-Tuning · PEFT · LoRA · QLoRA 7.4 Retrieval and Agents RAG Pipelines Chunking · Embeddings · Retrieval · Reranking Vector Databases Pinecone · Chroma · FAISS · pgvector LLM Frameworks and Agents LangChain · LangGraph · LlamaIndex · Tool Calling · MCP 8.1 Fundamentals of RL Core Concepts Agents · Environments · States and Actions · Rewards · Policies Markov Decision Processes Bellman Equations · Value Functions · Q-Values 8.2 Value and Policy Methods Tabular Methods Dynamic Programming · Monte Carlo · Q-Learning · SARSA Deep Q-Learning DQN · Double DQN · Experience Replay Policy Optimization Policy Gradients · Actor-Critic · TRPO · PPO 8.3 Modern RL Applications Games and Robotics AlphaGo · MuZero · Sim-to-Real Transfer · Gymnasium RL for Language Models RLHF · RLAIF · Reward Models · DPO · GRPO 9.1 Cloud and Containers Cloud ML Platforms AWS SageMaker · GCP Vertex AI · Azure ML Containers and Orchestration Docker · Docker Compose · Kubernetes · Helm 9.2 Model Serving and Deployment Serving Frameworks FastAPI · Triton Inference Server · Ray Serve · vLLM · BentoML Edge and Mobile Deployment ONNX Runtime · LiteRT · Core ML · TensorRT 9.3 ML Pipelines and Monitoring Experiment Tracking MLflow · Weights & Biases · DVC CI/CD for ML Automated Testing · Automated Retraining · Model Registry Production Monitoring Data Drift · Model Decay · Evidently · Alerting 9.4 Fairness and Privacy Bias and Fairness Dataset Representation · Bias Mitigation · Fairness Metrics Privacy and Compliance Differential Privacy · Federated Learning · GDPR · HIPAA · EU AI Act 9.5 Interpretability Explainable AI SHAP · LIME · Feature Importance · Saliency Maps Mechanistic Interpretability Circuit Discovery · Feature Visualization · Sparse Autoencoders 9.6 Security and Alignment Adversarial Robustness Prompt Injection · Jailbreaking · Data Poisoning · Adversarial Training AI Alignment Scalable Oversight · Constitutional AI · Safety Guardrails · Value Alignment 10.1 Capstone Projects End-to-End ML Project Data Pipeline · Model Training · Deployment · Monitoring LLM Application Project RAG Chatbot · AI Agent · Evaluation Suite Kaggle Competitions Tabular · Computer Vision · NLP 10.2 Portfolio and Presence GitHub Portfolio Clean READMEs · Live Demos · Model Cards Technical Writing Project Write-ups · Blog Posts · Paper Summaries 10.3 Interview Preparation Coding Interviews LeetCode-style Problems · Python · SQL ML Concept Interviews Algorithm Trade-offs · Metrics · Case Studies ML System Design Requirements · Data Flow · Serving · Trade-offs Behavioral Interviews STAR Method · Project Deep Dives