Phase 1 · days 1–210%
Code Foundations
Python from zero to fluent, plus the software-engineering habits — git, shell, testing, packaging, clean code — that everything else stands on.
PythonGit & shellTesting & debuggingClean code & packaging
0/21 days · quiz —
Phase 2 · days 22–490%
🔒 CS Core
Data structures, algorithms, SQL, operating systems, networking, concurrency, security, and system design — the invisible machinery under every production system.
DSA & Big OSQL & databasesOS & concurrencyNetworking, security & system design
0/28 days · quiz —
22□ Big O & Complexity23□ Arrays & Hashing24□ Two Pointers & Sliding Window25□ Stacks & Queues26□ Linked Lists27□ Recursion & Divide/Conquer28□ Week 4 Checkpoint: Pattern Drill29□ Binary Trees & BSTs30□ Heaps, Priority Queues & Tries31□ Graphs, BFS & DFS32□ Sorting33□ Binary Search & Variants34□ Dynamic Programming Intro35□ Week 5 Checkpoint: Interview Drill I36□ SQL I — Tables & Queries37□ SQL II — Joins & Modeling38□ Database Internals39□ Operating Systems Essentials40□ Concurrency & Async Python41□ HTTP & Build Your First API42□ Week 6 Checkpoint: API + DB Mini-Service43□ Networking — Packets to HTTPS44□ Security, AuthN & AuthZ45□ Web Service Architecture46□ Distributed Systems Fundamentals47□ Caching & Queues48□ System Design Method49□ Week 7 Checkpoint: Design & Build a URL Shortener
Phase 3 · days 50–630%
🔒 Math for ML
Vectors, matrices, gradients, probability, statistics and entropy — exactly the math modern ML runs on, taught visually and by building.
Linear algebraCalculus & optimizationProbability & statisticsInformation theory
0/14 days · quiz —
50□ Vectors & Dot Products51□ Matrices & Transformations52□ Rank, Eigenvectors & SVD Intuition53□ Derivatives & Gradients54□ Chain Rule & Optimization55□ Gradient Descent Lab56□ Week 8 Checkpoint: Linear Regression by Hand57□ Probability Fundamentals58□ Random Variables & Distributions59□ Bayes' Rule60□ Statistics I — Sampling & Confidence61□ Statistics II — Hypothesis Tests & A/B62□ Entropy, Cross-Entropy & KL63□ Week 9 Checkpoint: Math Assessment
Phase 4 · days 64–840%
🔒 Data & Machine Learning
From messy CSV to validated model: NumPy, pandas, EDA, feature engineering, supervised and unsupervised learning, metrics, and honest error analysis.
NumPy & pandasEDA & data craftSupervised learningEvaluation & ML practice
0/21 days · quiz —
64□ NumPy in Anger65□ pandas I — DataFrames66□ pandas II — Wrangling67□ Exploratory Data Analysis68□ Cleaning & Validation69□ Feature Engineering70□ Week 10 Checkpoint: EDA Report71□ ML Framing & Linear Regression72□ Logistic Regression & Losses73□ Decision Trees74□ Ensembles — Forests & Boosting75□ Evaluation Metrics76□ Validation, Bias/Variance & Regularization77□ Week 11 Checkpoint: Tabular Mini-Competition78□ Clustering79□ PCA & Dimensionality80□ Error Analysis81□ Experiment Tracking & Reproducibility82□ ML Code Structure & Pipelines83□ Phase Project: Churn Prediction End-to-End84□ Week 12 Checkpoint + Interview Drill II
Phase 5 · days 85–1050%
🔒 Deep Learning & Transformers
Neural networks from scratch, PyTorch, embeddings, attention, tokenization, and a tiny GPT you train yourself — the internals behind the APIs.
Neural nets & backpropPyTorchEmbeddings & attentionLLM internals
0/21 days · quiz —
85□ Neurons & Forward Pass86□ Backpropagation from Scratch87□ PyTorch — Tensors & Autograd88□ Training Loops & Data89□ Training Dynamics90□ MNIST Lab91□ Week 13 Checkpoint — The First Neural Check92□ Embeddings — Meaning as Geometry93□ word2vec Lab94□ Attention95□ The Transformer96□ Tokenization97□ Tiny GPT Lab I — Build It98□ Week 14 Checkpoint: Attention, Locked In99□ Tiny GPT Lab II — Train & Sample100□ How LLMs Are Trained101□ Scaling Laws, Capabilities & Limits102□ Decoding & Sampling103□ The Model Landscape & Local Inference104□ Context Windows & Hallucination Deep-Dive105□ Week 15 Checkpoint: Phase 5 Assessment
Phase 6 · days 106–1330%
🔒 AI Engineering
The 2026 job core: LLM APIs, prompting, structured outputs, tool use, RAG, vector search, agents, MCP, fine-tuning, multimodal, and AI security.
Prompting & tool useRAG & retrievalAgents & MCPFine-tuning, multimodal & AI security
0/28 days · quiz —
106□ LLM APIs I — The Request107□ LLM APIs II — Streaming, Retries & Cost108□ Prompt Engineering I — The Briefing Memo109□ Prompt Engineering II — Memos That Survive Contact110□ Structured Outputs — Forms, Not Essays111□ Tool Use & Function Calling112□ Week 16 Checkpoint: The Prompt Lab113□ RAG I — Architecture114□ Chunking Strategies115□ Embeddings & Vector Databases116□ Hybrid Search117□ Reranking & Query Transforms118□ Advanced RAG Patterns119□ Week 17 Checkpoint: Capstone Kickoff — Docs-QA v0120□ Agents I — The Loop121□ Agents II — Planning & Decomposition122□ Agents III — Memory & Context123□ Multi-Agent & Workflow Patterns124□ Model Context Protocol125□ Agent Reliability126□ Week 18 Checkpoint: Support-Triage Agent127□ Fine-Tuning I — When & Data128□ Fine-Tuning II — LoRA Lab129□ Distillation, Quantization & Model Selection130□ Multimodal I — Vision & Documents131□ Multimodal II — Audio & Voice132□ Guardrails, Injection & AI Security133□ Week 19 Checkpoint: Red-Team Your RAG
Phase 7 · days 134–1470%
🔒 Evaluation & Observability
The most underrated hiring signal: golden sets, LLM-as-judge, RAG metrics, regression gates, tracing, red teaming, and continuous evaluation.
Eval designLLM-as-judgeRAG & agent evalsObservability & continuous eval
0/14 days · quiz —
134□ Eval Mindset & Golden Sets135□ Graders — Code, Rubric & LLM-as-Judge136□ RAG Evaluation137□ Agent & Task Evals138□ Human Evaluation139□ Statistics for Evals140□ Week 20 Checkpoint: Capstone Eval Harness141□ Regression Gates & CI for AI142□ Tracing LLM Applications143□ Logging, Feedback & the Data Flywheel144□ Red-Teaming Lab145□ Drift & Continuous Eval in Prod146□ Quality & Cost Dashboards147□ Observability Complete
Phase 8 · days 148–1610%
🔒 Production & MLOps
Docker, cloud, CI/CD, serving and inference optimization, monitoring, reliability, incident response — shipping AI that stays up and earns its cost.
Docker & cloudCI/CD & IaCServing & costReliability & AI system design
0/14 days · quiz —
148□ Docker Fundamentals149□ Compose, Registries & Image Hygiene150□ Cloud Fundamentals151□ Deploy Lab — Container to Cloud URL152□ CI/CD with GitHub Actions153□ Infrastructure as Code & Environments154□ Week 22 Checkpoint: Staging Pipeline155□ Serving & Inference Optimization156□ Caching, Batching & Cost Engineering157□ Monitoring & SLOs158□ Reliability & Incident Response159□ Production Security & Compliance Basics160□ AI System Design161□ Week 23 Checkpoint: Production Cutover
Phase 9 · days 162–1800%
🔒 FDE & Capstone
Forward-deployed craft: discovery, specs, prototypes, enterprise integration, stakeholder communication — then ship and present your capstone.
Customer discoverySpecs & proposalsEnterprise deliveryInterview readiness
0/19 days · quiz —
162□ The FDE Role163□ Customer Discovery & the Mom Test164□ Ambiguity → Requirements165□ Proposals & Architecture Docs166□ Rapid Prototyping167□ Demo Craft168□ Week 24 Checkpoint: FDE Simulation I169□ Enterprise Integration170□ Customer Environments171□ Stakeholders & Trade-off Navigation172□ Production Debugging with Customers173□ ROI, Pricing & Cost Analysis174□ FDE Simulation II — Full Cycle175□ Week 25 Checkpoint: Debrief & Gap Closure176□ Capstone Hardening177□ Capstone Quality Gates178□ Capstone Ship & Document179□ Interview Gym180□ Demo Day