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Engineering-First·Production-Focused·Research-Backed

The Engineering Curriculum
for the AI Era

Learn it right. Build it right. Ship it.

From math to model to production - every concept, every system.

0Tracks
0+Modules
0+Lessons
In-DepthWeekly Issues
what you will learn
>>>Transformers, attention, and positional encoding from scratch
>>>Building RAG pipelines with vector DBs and reranking
>>>Deploying ML models with FastAPI, Docker, and Kubernetes
>>>Agent orchestration with ReAct loops and tool calling
The Ecosystem

Tools Built for AI Engineers

Practice, earn fairly, and land the role.

Curriculum

14 Tracks. One Journey.

From Python fundamentals to production AI - a deliberate sequence built for engineers who ship.

01
Python02
Math for AI03
Machine Learning04
Data Engineering05
LLMs06
AI Systems07
MLOps08
Agentic AI09
AI Engineering10
Break Into AI11
Hardware & Silicon12
Open Source Models13
Applied AI14
Foundational CS
Transformers · Attention Mechanisms · RAG Systems · Vector Databases · RLHF · Prompt Engineering · Agent Orchestration · Model Serving · Feature Stores · Diffusion Models · Knowledge Graphs · MCP Protocol · LoRA Fine-tuning · Chain-of-Thought · Embedding Models · GPU Optimization · Kubernetes for ML · Data Pipelines · Model Compression · Reasoning Models · Transformers · Attention Mechanisms · RAG Systems · Vector Databases · RLHF · Prompt Engineering · Agent Orchestration · Model Serving · Feature Stores · Diffusion Models · Knowledge Graphs · MCP Protocol · LoRA Fine-tuning · Chain-of-Thought · Embedding Models · GPU Optimization · Kubernetes for ML · Data Pipelines · Model Compression · Reasoning Models ·
Reasoning Models · Model Compression · Data Pipelines · Kubernetes for ML · GPU Optimization · Embedding Models · Chain-of-Thought · LoRA Fine-tuning · MCP Protocol · Knowledge Graphs · Diffusion Models · Feature Stores · Model Serving · Agent Orchestration · Prompt Engineering · RLHF · Vector Databases · RAG Systems · Attention Mechanisms · Transformers · Reasoning Models · Model Compression · Data Pipelines · Kubernetes for ML · GPU Optimization · Embedding Models · Chain-of-Thought · LoRA Fine-tuning · MCP Protocol · Knowledge Graphs · Diffusion Models · Feature Stores · Model Serving · Agent Orchestration · Prompt Engineering · RLHF · Vector Databases · RAG Systems · Attention Mechanisms · Transformers ·
Research Lab

Papers in the Right Order

Read papers with engineering context between each one. No more reading in isolation.

View all research →
RAG8 papers

From Lewis et al. to GraphRAG. Retrieval-augmented generation, fully explained.

Read roadmap →
Certifications

Prove What You Can Build

Project-based, engineering-focused certifications that reflect real production competence.

Why This

What Makes This Different

There are thousands of AI courses. Here's why engineers who ship choose this one.

Production-First

Every concept taught with the real-world context that determines whether it ships or doesn't.

Engineering-Grade Depth

Not surface-level tutorials. Full system thinking - trade-offs, failure modes, and what to do next.

Research to Reality

Paper breakdowns with production viability ratings. Know which papers matter and which are noise.

Honest Analysis

Paper autopsies on what underdelivered. Benchmarks decoded. No hype, just engineering truth.

One Structured Path

No random course hopping. A deliberate sequence from foundations to research frontier.

Stay Current Weekly

AI Letters distils the week's most important papers into 5-minute engineering reads.