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MIT · Harvard · DARPA · Anthropic Level

Master the Age of Artificial Intelligence

A 3-year deep-dive programme covering Generative AI, Agentic Systems, LLMs, RAG, Neural Networks, Data Science, and everything in between — with hands-on labs, real-world projects, and the industry tools you'll actually use on the job.

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Three Years.
Zero Limits.

From Python fundamentals to building autonomous AI agents that rival research-grade systems.

Year 1 · Term 1 — Python, Math & the AI Universe
Core M1.01

Python for AI — Zero to Fluent

Variables, control flow, functions, OOP, async/await, decorators, generators. Build a mini interpreter by week 3.

6 weeks24 lessons8 labs
  • L01Environment Setup: Conda, VS Code, JupyterVideo
  • L02Data Types, Variables, ExpressionsLab
  • L03Control Flow: if/else, loops, comprehensionsLab
  • L04Functions: args, kwargs, closuresVideo
  • L05OOP: Classes, Inheritance, ProtocolsLab
  • L06Generators, Decorators, Context ManagersLab
  • L07Async/Await, Concurrency, ThreadingVideo
  • L08File I/O, JSON, CSV, YAML handlingLab
  • L09Python Packaging: pip, Poetry, setuptoolsReading
  • L10PROJECT: Build a CLI AI Tool SkeletonProject
  • L11NumPy: Arrays, Broadcasting, Linear AlgebraLab
  • L12Pandas: DataFrames, GroupBy, MergeLab
  • L13Matplotlib & Seaborn: Data VisualizationLab
  • L14Checkpoint Quiz: Python MasteryQuiz
Core M1.02

Mathematics for AI — Linear Algebra, Calculus & Probability

The mathematical bedrock of all ML. Interactive visualizations make it intuitive, not intimidating.

5 weeks20 lessons6 labs
  • L01Vectors, Matrices, Tensors — Visual IntuitionVideo
  • L02Matrix Operations, Dot Products, TransposesLab
  • L03Eigenvalues, Eigenvectors, PCALab
  • L04Derivatives: Chain Rule, GradientVideo
  • L05Gradient Descent — Interactive DemoLab
  • L06Backpropagation Math from ScratchLab
  • L07Probability: Distributions, Bayes' TheoremVideo
  • L08Statistics: MLE, MAP, Hypothesis TestingLab
  • L09Information Theory: Entropy, KL-DivergenceReading
  • L10QUIZ: Math FoundationsQuiz
Data Science M1.03

Data Engineering & Pipeline Architecture

Fetching, cleaning, transforming, and storing data at scale. APIs, scrapers, SQL, and modern data stacks.

4 weeks18 lessons7 labs
  • L01REST APIs: Requests, Auth, Rate LimitsLab
  • L02WebScraping: BeautifulSoup, PlaywrightLab
  • L03SQL: Queries, Joins, Window FunctionsLab
  • L04Data Cleaning: Missing Values, OutliersLab
  • L05Feature Engineering & TransformationVideo
  • L06Exploratory Data Analysis (EDA)Lab
  • L07Data Pipelines: Airflow, PrefectVideo
  • L08Streaming Data: Kafka basicsReading
  • L09PROJECT: End-to-End Data PipelineProject
Machine Learning M1.04

Classical Machine Learning with Scikit-Learn

Supervised & unsupervised learning. Regression, classification, clustering — understand the why, not just the how.

5 weeks22 lessons9 labs
  • L01The ML Workflow: Train/Val/Test SplitsVideo
  • L02Linear Regression: From Scratch + SklearnLab
  • L03Logistic Regression, Decision BoundariesLab
  • L04Decision Trees and Random ForestsLab
  • L05SVM, KNN, Naive BayesLab
  • L06Gradient Boosting: XGBoost, LightGBMLab
  • L07K-Means, DBSCAN, Hierarchical ClusteringLab
  • L08Dimensionality Reduction: PCA, t-SNE, UMAPLab
  • L09Cross-Validation, Hyperparameter TuningLab
  • L10Model Evaluation: AUC, F1, Precision/RecallVideo
  • L11PROJECT: Predict House Prices (Kaggle-style)Project
  • L12QUIZ: ML AlgorithmsQuiz
Year 1 · Term 2 — Neural Networks & Deep Learning
Machine Learning M1.05

Neural Networks from Scratch

Build a neural network using only NumPy. Understand every weight, bias, activation, and gradient.

4 weeks18 lessons8 labs
  • L01The Neuron: Weights, Bias, ActivationVideo
  • L02Forward Pass Implementation in NumPyLab
  • L03Activation Functions: ReLU, Sigmoid, GELULab
  • L04Loss Functions: MSE, Cross-EntropyLab
  • L05Backpropagation: Computing GradientsLab
  • L06Optimizers: SGD, Momentum, AdamLab
  • L07Regularization: Dropout, L1/L2, BatchNormLab
  • L08Multi-layer Networks: Hidden LayersLab
  • L09PROJECT: Build MNIST Classifier from ScratchProject
Machine Learning M1.06

TensorFlow & Keras — Deep Learning at Scale

Production-grade neural networks with TensorFlow. Cloud training, GPU acceleration, model serving.

5 weeks22 lessons10 labs
  • L01TensorFlow Architecture: Tensors, Graphs, SessionsVideo
  • L02Keras Sequential API: Build Your First ModelLab
  • L03Functional API: Complex ArchitecturesLab
  • L04Custom Layers, Models, Training LoopsLab
  • L05Callbacks: EarlyStopping, ModelCheckpointLab
  • L06TF Data Pipeline: tf.data APILab
  • L07GPU/TPU Training on Google CloudLab
  • L08TensorBoard: Visualize TrainingVideo
  • L09Model Export: SavedModel, TFLiteLab
  • L10TF Serving: REST API DeploymentLab
  • L11PROJECT: Image Classifier Deployed to CloudProject
  • L12QUIZ: TensorFlow Deep DiveQuiz
Machine Learning M1.07

Convolutional Neural Networks (CNNs)

Computer vision fundamentals. Object detection, image segmentation, real-time video analysis.

4 weeks16 lessons7 labs
  • L01Convolution Operation: Intuition & MathVideo
  • L02Pooling Layers, Stride, PaddingLab
  • L03LeNet → AlexNet → VGG: Architecture EvolutionReading
  • L04ResNet: Residual ConnectionsLab
  • L05Transfer Learning: Fine-Tuning Pre-trained ModelsLab
  • L06Object Detection: YOLO v8Lab
  • L07Semantic Segmentation: U-NetLab
  • L08PROJECT: Real-Time Object Detection AppProject
Machine Learning M1.08

Recurrent Networks & Sequence Models

RNNs, LSTMs, GRUs — sequence-to-sequence learning. The stepping stone to understanding Transformers.

3 weeks14 lessons6 labs
  • L01Sequences & Time Series: Problem SetupVideo
  • L02Vanilla RNN: Vanishing Gradient ProblemLab
  • L03LSTM: Gates, Cell State, MemoryLab
  • L04GRU: Gated Recurrent UnitsLab
  • L05Attention Mechanisms: The Bridge to TransformersVideo
  • L06Seq2Seq: Encoder-Decoder ArchitectureLab
  • L07PROJECT: Stock Price PredictorProject
Year 1 · Term 3 — NLP, Embeddings & Intro to LLMs
Generative AI M1.09

Natural Language Processing Fundamentals

Tokenization, word embeddings, topic modelling, sentiment analysis — the NLP toolbox.

4 weeks16 lessons7 labs
  • L01Text Preprocessing: Tokenization, StemmingLab
  • L02Bag of Words, TF-IDFLab
  • L03Word2Vec: Skip-gram & CBOWLab
  • L04GloVe, FastText EmbeddingsReading
  • L05Sentiment Analysis: VADER, TextBlob, BERTLab
  • L06Named Entity Recognition (NER)Lab
  • L07Topic Modelling: LDA, NMFLab
  • L08PROJECT: News Article ClassifierProject
Generative AI M1.10

The Transformer Architecture — Attention is All You Need

The architecture behind GPT, BERT, Claude, Gemini. Implement multi-head attention from first principles.

5 weeks20 lessons8 labs
  • L01Self-Attention: Query, Key, ValueVideo
  • L02Scaled Dot-Product AttentionLab
  • L03Multi-Head Attention ImplementationLab
  • L04Positional Encoding: Sinusoidal & RoPELab
  • L05Encoder Architecture: BERT-styleLab
  • L06Decoder Architecture: GPT-styleLab
  • L07Full Transformer: Encoder-DecoderLab
  • L08Layer Normalization, Residual ConnectionsReading
  • L09PROJECT: Implement Nano-GPT from ScratchProject
  • L10QUIZ: Transformer ArchitectureQuiz
Generative AI M1.11

Intro to LLMs — GPT, Claude, Gemini, Llama

What LLMs are, how they're trained, how to talk to them via API. Prompt engineering essentials.

4 weeks18 lessons6 labs
  • L01LLM Taxonomy: Sizes, Capabilities, Trade-offsVideo
  • L02Anthropic Claude API: First CallsLab
  • L03OpenAI API: GPT-4o, o1, o3Lab
  • L04Google Gemini API: Text & VisionLab
  • L05Running Local LLMs: Ollama, LM StudioLab
  • L06Prompt Engineering: Zero-shot, Few-shot, CoTLab
  • L07System Prompts, Temperature, SamplingVideo
  • L08Evaluating LLM Outputs: BLEU, ROUGE, BERTScoreLab
  • L09PROJECT: Multi-LLM Chat AppProject
Data Science M1.12

Year 1 Capstone: AI-Powered Data Dashboard

Synthesize everything learned. Build a full-stack dashboard that fetches live data, runs ML models, and generates LLM summaries.

3 weeksProject-basedTeam of 2
  • P01Project Kickoff & Architecture DesignProject
  • P02Data Pipeline: Live API → PostgreSQLLab
  • P03ML Module: Anomaly DetectionLab
  • P04LLM Summarization: Auto-Generated InsightsLab
  • P05FastAPI Backend + React FrontendLab
  • P06Cloud Deploy: GCP/AWSLab
  • P07Demo Day PresentationProject
Year 2 · Term 1 — Generative AI Mastery
Generative AI M2.01

LLM Pre-Training & Architecture Deep Dive

How GPT-4, Claude 3, Llama 3, Mixtral were actually built. Data curation, tokenization, training at scale.

5 weeks22 lessons8 labs
  • L01Pre-training Data: The Pile, Common Crawl, C4Reading
  • L02BPE Tokenization: Build Your Own TokenizerLab
  • L03Scaling Laws: Chinchilla OptimalVideo
  • L04Flash Attention 2, Grouped Query AttentionLab
  • L05Mixture of Experts (MoE): Mixtral, DeepSeekLab
  • L06RLHF: Reward Models & PPOVideo
  • L07DPO, GRPO, Constitutional AILab
  • L08Context Length: RoPE Scaling, ALiBiLab
  • L09PROJECT: Train a 125M LM on Custom DataProject
Generative AI M2.02

Fine-Tuning, PEFT & LoRA

Adapt any LLM to your domain. LoRA, QLoRA, Prefix Tuning, Adapters — production fine-tuning on limited hardware.

4 weeks18 lessons9 labs
  • L01Why Fine-tune? Use Cases & Trade-offsVideo
  • L02Full Fine-tuning: Instruction FollowingLab
  • L03LoRA: Low-Rank Adaptation Deep DiveLab
  • L04QLoRA: 4-bit Quantization + LoRALab
  • L05HuggingFace PEFT LibraryLab
  • L06Dataset Curation for Fine-tuningLab
  • L07Evaluation: Evals, MMLU, HumanEvalLab
  • L08Unsloth: 2x Speed Fine-tuningLab
  • L09PROJECT: Domain-Specific LLM for Medicine/Law/CodeProject
Generative AI M2.03

RAG — Retrieval Augmented Generation

Naive RAG → Advanced RAG → Modular RAG → GraphRAG. Build production knowledge systems.

5 weeks24 lessons11 labs
  • L01Why RAG? Hallucination & Knowledge GapsVideo
  • L02Embeddings: text-embedding-3, all-mpnetLab
  • L03Vector Databases: Chroma, Pinecone, WeaviateLab
  • L04Chunking Strategies: Fixed, Semantic, RecursiveLab
  • L05Hybrid Search: BM25 + Dense RetrievalLab
  • L06Reranking: Cohere, BGE-RerankerLab
  • L07HyDE: Hypothetical Document EmbeddingsLab
  • L08RAPTOR: Recursive Summarization TreesLab
  • L09GraphRAG: Microsoft's Knowledge Graph RAGLab
  • L10RAG Evaluation: RAGAS FrameworkLab
  • L11PROJECT: Enterprise Document Q&A SystemProject
  • L12QUIZ: Advanced RAGQuiz
Generative AI M2.04

Diffusion Models & Image Generation

Stable Diffusion, DALL-E, Flux, Sora internals. Train your own LoRA art style. Video generation.

4 weeks16 lessons7 labs
  • L01VAEs, GANs: Historical ContextVideo
  • L02DDPM: Denoising Diffusion MathLab
  • L03CLIP: Vision-Language AlignmentLab
  • L04Stable Diffusion Architecture: U-Net + VAELab
  • L05ControlNet, IP-AdapterLab
  • L06DreamBooth: Personalize Any ModelLab
  • L07Video Generation: AnimateDiff, Sora ArchitectureReading
  • L08PROJECT: AI Product Photo GeneratorProject
Year 2 · Term 2 — Agentic AI Systems
Agentic M2.05

AI Agents — Architecture & Fundamentals

ReAct, Plan-and-Execute, Reflexion, Tree-of-Thoughts. Build agents that think, act, and self-correct.

5 weeks22 lessons10 labs
  • L01What is an Agent? Sense → Think → Act LoopVideo
  • L02ReAct: Reasoning + ActingLab
  • L03Tool Use: Function Calling APIsLab
  • L04Memory: Short-term, Long-term, EpisodicLab
  • L05Planning: MCTS, A*, LLM PlannersLab
  • L06Reflexion: Self-Critique & RevisionLab
  • L07Tree of Thoughts: Multi-path ReasoningLab
  • L08LangChain: Chains, Agents, MemoryLab
  • L09LangGraph: Stateful Agent GraphsLab
  • L10PROJECT: Research Agent with Web AccessProject
Agentic M2.06

Multi-Agent Systems & Swarm Intelligence

AutoGen, CrewAI, MetaGPT. Agents that delegate, collaborate, argue, and solve complex tasks together.

4 weeks18 lessons8 labs
  • L01Multi-Agent Theory: Cooperation, CompetitionVideo
  • L02AutoGen: Microsoft Multi-Agent FrameworkLab
  • L03CrewAI: Role-Based Agent TeamsLab
  • L04MetaGPT: Software Company SimulationLab
  • L05Agent Communication ProtocolsReading
  • L06Debate: Adversarial Multi-AgentLab
  • L07HITL: Human-in-the-Loop SystemsLab
  • L08PROJECT: AI Software Dev Team (PM + Dev + QA)Project
Agentic M2.07

Computer Use & Browser Agents

Agents that control computers. Playwright automation, GUI agents, Claude Computer Use, Operator.

3 weeks14 lessons6 labs
  • L01Computer Use API: Claude's Screen VisionVideo
  • L02Browser Automation: Playwright + LLMLab
  • L03GUI Agent: Click, Type, NavigateLab
  • L04Web Scraping Agents: Dynamic SitesLab
  • L05Desktop Automation: PyAutoGUI + LLMLab
  • L06PROJECT: Autonomous Web Research AgentProject
Agentic M2.08

MCP — Model Context Protocol

Anthropic's open standard for connecting AI to any tool, database, or API. Build MCP servers from scratch.

3 weeks12 lessons5 labs
  • L01MCP Architecture: Hosts, Clients, ServersVideo
  • L02Tools, Resources, Prompts: MCP PrimitivesLab
  • L03Build MCP Server: Python SDKLab
  • L04Connect Database via MCPLab
  • L05MCP Security, OAuth, SandboxingReading
  • L06PROJECT: Custom MCP for Proprietary DataProject
Year 2 · Term 3 — MLOps, Safety & Advanced Systems
Machine Learning M2.09

MLOps & LLMOps — Production AI Systems

Take models from notebook to production. CI/CD for ML, monitoring, A/B testing, drift detection.

4 weeks18 lessons8 labs
  • L01MLflow: Experiment TrackingLab
  • L02Docker for ML: ContainerizationLab
  • L03Kubernetes: Orchestrating ML WorkloadsLab
  • L04FastAPI: Model Serving at ScaleLab
  • L05Model Monitoring: Evidently, WhyLabsLab
  • L06Feature Stores: Feast, HopsworksLab
  • L07LangSmith, Weights & Biases: LLM TracingLab
  • L08A/B Testing for LLMs: Prompt ExperimentsLab
  • L09PROJECT: Full MLOps Pipeline on GCP/AWSProject
Generative AI M2.10

AI Safety, Alignment & Ethics

Constitutional AI, RLHF alignment, red-teaming, jailbreaks, bias detection. The responsible AI practitioner.

3 weeks14 lessons5 labs
  • L01AI Alignment Problem: Why it MattersVideo
  • L02Constitutional AI: Anthropic's ApproachReading
  • L03Red-Teaming LLMs: Adversarial TestingLab
  • L04Bias Detection & Fairness MetricsLab
  • L05Interpretability: Attention Viz, SHAPLab
  • L06Mechanistic Interpretability: Circuits, FeaturesReading
  • L07EU AI Act, GDPR: Regulatory ComplianceReading
Agentic M2.11

Voice AI & Multimodal Systems

Speech recognition, TTS, real-time voice agents. Vision-language models. Build a voice AI assistant.

3 weeks14 lessons6 labs
  • L01ASR: Whisper, Assembly AI, DeepgramLab
  • L02TTS: ElevenLabs, Kokoro, Parler-TTSLab
  • L03Real-time Voice: LiveKit, Daily.coLab
  • L04Vision LLMs: GPT-4V, Claude Vision, GeminiLab
  • L05Video Understanding: Frame Sampling LLMsLab
  • L06PROJECT: Full-Stack Voice AssistantProject
Capstone M2.12

Year 2 Capstone: Autonomous Research Assistant

Build a full agentic system: web browsing, document reading, RAG memory, report writing. Deployed and monitored in production.

4 weeksSolo or TeamIndustry-grade
  • P01System Design: Agent ArchitectureProject
  • P02Web Search + Scraping AgentLab
  • P03RAG Memory System: Chroma + RAPTORLab
  • P04Report Generation: LLM + CitationsLab
  • P05Frontend: React Chat InterfaceLab
  • P06MLOps: Monitor, Alert, ImproveLab
  • P07Demo Day + Industry JudgesProject
Year 3 · Term 1 — Research-Grade AI
Generative AI M3.01

Frontier Model Research: What's Next After GPT-4

Read and implement papers from DeepMind, Anthropic, OpenAI, Google Brain. Reproduce state-of-the-art results.

5 weeks20 lessons10 labs
  • L01Reading AI Papers: How to Extract ValueReading
  • L02Gemini 1.5: Multi-Modal, 1M ContextReading
  • L03Claude 3 / 4: Constitutional AI at ScaleReading
  • L04DeepSeek R1: Reasoning via RLLab
  • L05Implement Paper: Reproduce Tiny-GPT-2Lab
  • L06Sparse Autoencoders: Feature DiscoveryLab
  • L07World Models: Dreamer V3Reading
  • L08Neuro-Symbolic AI: Logic + LLMsLab
  • L09AI for Science: AlphaFold, AI2 FuturehouseReading
  • L10PROJECT: Replicate a 2024 ArXiv PaperProject
Agentic M3.02

Advanced Agentic Systems: SWE-Agent, Devin-Style

Build autonomous coding agents. Full software engineering pipelines: read issue → write code → run tests → submit PR.

5 weeks22 lessons10 labs
  • L01SWE-Bench: Evaluating Code AgentsReading
  • L02Code Execution Sandboxing: E2BLab
  • L03Git Integration: Read Repos, Create PRsLab
  • L04Test-Driven Development with AI AgentsLab
  • L05Code Search: AST, Embeddings, RAGLab
  • L06Claude Code Architecture Deep DiveReading
  • L07Multi-File Reasoning: Context ManagementLab
  • L08Self-Debugging Agents: Iterative LoopsLab
  • L09PROJECT: Build a Devin-Lite Coding AgentProject
Machine Learning M3.03

Reinforcement Learning for AI Agents

Q-learning to PPO to GRPO. Train LLMs with RL. Build game-playing and robot control agents.

5 weeks22 lessons9 labs
  • L01RL Fundamentals: MDP, Reward, PolicyVideo
  • L02Q-Learning, SARSA, Deep Q-NetworkLab
  • L03Policy Gradients: REINFORCE, A2CLab
  • L04PPO: Proximal Policy OptimizationLab
  • L05GRPO: Group Relative Policy OptimizationLab
  • L06RLHF Full Pipeline: SFT → RM → PPOLab
  • L07DPO: Direct Preference OptimizationLab
  • L08Multi-Agent RL: Game TheoryLab
  • L09PROJECT: Train a Reasoning LLM with RLProject
Agentic M3.04

AI Infrastructure & Distributed Training

Train models across 100s of GPUs. FSDP, DeepSpeed, Megatron-LM. Cloud cost optimization.

4 weeks16 lessons7 labs
  • L01GPU Memory: VRAM, Offloading, PagingVideo
  • L02Data Parallelism: DDP, FSDPLab
  • L03Model Parallelism: Tensor, PipelineLab
  • L04DeepSpeed ZeRO: Memory OptimizationLab
  • L05vLLM: High-Throughput LLM InferenceLab
  • L06Quantization: GPTQ, AWQ, GGUFLab
  • L07Cloud GPU: AWS, GCP, Lambda LabsLab
Year 3 · Term 2 & 3 — Specialization Tracks & Thesis
Specialization M3.05

Track A: AI for Healthcare & Bioinformatics

Med-PaLM, BioGPT, AlphaFold. Clinical NLP, medical imaging, drug discovery. HIPAA-compliant systems.

6 weeks24 lessons10 labs
  • L01Medical NLP: Clinical Notes, ICD CodingLab
  • L02Medical Imaging: DICOM, Radiology AILab
  • L03BioGPT: Biomedical Text MiningLab
  • L04AlphaFold API: Protein Structure PredictionLab
  • L05Drug Discovery with GNNsLab
  • L06HIPAA Compliance for AI SystemsReading
  • L07PROJECT: AI Diagnostic AssistantProject
Specialization M3.06

Track B: Autonomous Systems & Robotics

ROS2, embodied AI, vision-language-action models. Connect LLMs to real hardware.

6 weeks20 lessons8 labs
  • L01Embodied AI: Foundation Models for RobotsVideo
  • L02ROS2: Robot Operating SystemLab
  • L03RT-2, π0: Vision-Language-Action ModelsReading
  • L04Simulation: IsaacSim, PyBulletLab
  • L05Sim-to-Real TransferLab
  • L06PROJECT: LLM-Controlled Robot ArmProject
Specialization M3.07

Track C: AI for Finance & Quantitative Systems

Sentiment trading, LLM financial analysts, fraud detection at scale. Backtesting frameworks.

6 weeks22 lessons9 labs
  • L01Financial NLP: Earnings Calls, News SentimentLab
  • L02Time Series Forecasting for FinanceLab
  • L03Algorithmic Trading with LLM SignalsLab
  • L04Fraud Detection: Graph Neural NetworksLab
  • L05BloombergGPT, FinGPTReading
  • L06Backtesting: Backtrader, ZiplineLab
  • L07PROJECT: Autonomous Trading SystemProject
Thesis M3.08

🎓 Final Thesis: Frontier AI Project

12-week original research or industry-grade project. DARPA / Anthropic benchmark level. Peer-reviewed, published on GitHub, presented at Demo Day.

12 weeksOriginal ResearchIndustry Panel
  • T01Thesis Proposal: Problem, Method, BaselineProject
  • T02Literature Review & Related WorkReading
  • T03Experiment Design & Data CollectionLab
  • T04Implementation Sprints (x4)Lab
  • T05Ablation Studies & AnalysisLab
  • T06Paper Writing: Abstract, Methods, ResultsReading
  • T07Final Demo: Industry + Academic PanelProject

Hands-On Playground

Interactive demos embedded in your learning environment. No setup required.

Neural Network Visualizer Live Demo
2
4
0.003
Epoch: 0 | Loss: —
LLM Tokenizer Visualizer Interactive
Tokens: 0 Chars: 0 Ratio: chars/token
Gradient Descent Visualizer Math Demo
0.10
2.5
Click Run to start gradient descent...
Data Pipeline Simulator Data Science
Raw API
Fetch
Clean
Transform
Vectorize
ML Ready
// Click "Run Pipeline" to simulate a full data processing run

Industry Tools You'll Master

Every tool, framework, and platform used by AI engineers at Anthropic, Google, OpenAI, and the world's top AI labs.

🔥
TensorFlowCloud ML / TPU
🔴
PyTorchResearch Standard
🤗
HuggingFaceModels & Datasets
🦜
LangChainLLM Orchestration
🕸
LangGraphAgent Graphs
🧠
Claude APIAnthropic LLM
OpenAI APIGPT-4o / o3
💎
Gemini APIGoogle DeepMind
📊
Scikit-LearnClassical ML
XGBoostGradient Boost
🔵
Chroma DBVector Store
📌
PineconeVector DB
🌊
WeaviateVector Search
🦙
OllamaLocal LLMs
🚀
vLLMFast Inference
🎭
CrewAIMulti-Agent
🤖
AutoGenMicrosoft MAS
🐋
DockerContainerization
KubernetesOrchestration
📈
MLflowExperiment Track
🏄
W&BWeights & Biases
🔍
LangSmithLLM Observability
🌍
FastAPIModel Serving
GCP / AWSCloud Training

72 Industry-Grade Projects

From your first classifier to publishing AI research. Every project is deployable, demonstrable, and portfolio-ready.

🧬
Year 2

Medical Diagnosis RAG System

Upload clinical notes, get differential diagnoses with cited medical literature. Vector search over PubMed + fine-tuned Bio-BERT.

Claude APIChroma BioBERTFastAPI
🤖
Year 3

Autonomous Coding Agent

Give it a GitHub issue URL. Watch it read code, write a fix, run tests, and submit a PR. Built with LangGraph + E2B sandboxing.

LangGraphE2B GPT-4oGitHub API
📈
Year 2

Real-Time Market Sentiment Engine

Stream Reddit + news, classify sentiment with fine-tuned FinBERT, generate trading signals. Live dashboard with Plotly.

KafkaFinBERT PlotlyRedis
🎙
Year 2

AI Meeting Summarizer & Action Tracker

Record a meeting → Whisper transcription → Claude summary → extract action items → push to Jira/Notion via MCP.

WhisperClaude MCPNotion API
🎨
Year 2

AI Product Photography Studio

Upload product photo → remove background → generate 10 different scene styles with Flux/SD + ControlNet. SaaS-ready API.

Stable DiffusionControlNet ReplicateNext.js
🧪
Year 3 Thesis

Reasoning LLM via GRPO

Train a small language model to reason step-by-step using Group Relative Policy Optimization. Reproduce DeepSeek-R1-Zero methodology.

PyTorchGRPO UnslothWandB

Your 3-Year Journey

From zero to frontier AI researcher. Each skill unlocks the next.

Year 1 — Foundations
Python MasteryFull language fluency + NumPy/Pandas
Math for AILinear algebra, calculus, probability
Data EngineeringAPIs, SQL, pipelines, EDA
Classical MLSklearn, XGBoost, ensemble methods
Neural NetworksBuild from scratch, TensorFlow
CNN & RNNVision + sequence models
TransformersImplement attention + nano-GPT
LLM BasicsAPIs, prompting, evaluation
Year 2 — Mastery
LLM InternalsPre-training, scaling laws, RLHF
Fine-TuningLoRA, QLoRA, instruction tuning
RAG SystemsFrom naive to GraphRAG
Image GenerationDiffusion, ControlNet, LoRA
AI AgentsReAct, LangGraph, memory
Multi-AgentAutoGen, CrewAI, MAS
MCP ProtocolBuild servers, connect tools
MLOpsDocker, K8s, monitoring
Year 3 — Research
Frontier ResearchImplement 2024/25 papers
Coding AgentsSWE-Agent, Devin-style
RL for LLMsPPO, GRPO, DPO pipelines
Distributed TrainingFSDP, DeepSpeed, vLLM
SpecializationHealth / Robotics / Finance
AI SafetyAlignment, interpretability
Thesis ResearchOriginal contribution
Industry ReadyPortfolio + peer review

Test Yourself

Q: In the Transformer attention mechanism, what do Q, K, and V stand for?

Q: Which technique adapts large language models using low-rank matrix decomposition with minimal parameters?

Q: What does RAG stand for in AI?