Learning Path Diagram

AI Engineer Roadmap

A step-by-step engineering progression path taking you from tokenizers and hyperparameters to autonomous agents, model gateways, and containerized evaluators.

AI Engineer Path progression

LLM FoundationIn Progress

Neural NetworksComing Soon

Sequence ModelsComing Soon

TransformersComing Soon

Embeddings / DBComing Soon

RAG EngineeringComing Soon

Structured AI AppsComing Soon

Agentic AIComing Soon

MCP / ToolsComing Soon

Multi-AgentComing Soon

AI System DesignComing Soon

Production AIComing Soon

Syllabus Modules Walkthrough

Module 1: LLM Foundation

In Progress

Learn how Large Language Models work from the ground up: tokens, context windows, hyperparameters, prompts, structured outputs, embeddings, semantic search, evaluation, and attention mechanics.

Master prompt engineering design methodologiesDeconstruct subword tokenizers and BPE algorithmsManage token budgets and context window limitsEnforce JSON schemas and type-safe structured outputsGenerate embeddings and perform vector search lookupsRun evaluation tests using golden sets and LLM-as-a-judge patterns

Projects: 11View Details

Module 2: Neural Network Foundations

Coming Soon

Deconstruct deep learning layers, weights, biases, backpropagation, and activation/loss functions from scratch.

Implement forward pass matrices from scratchCompute partial derivatives for backpropagationTune weight matrices using SGD and Adam optimizers

Projects: 7View Details

Module 3: Sequence Models

Coming Soon

Understand recurrent memory architectures, LSTMs, and gated structures preceding modern attention.

Build character prediction models using recurrent cellsTrace gradient paths inside LSTM gating circuitsUnderstand sequence-to-sequence translation architectures

Projects: 6View Details

Module 4: Transformer Architecture

Coming Soon

Deep dive into Attention Is All You Need. Study positional encoding, multi-head attention, and decoder layers.

Compute scaled dot-product attention manuallyImplement sine/cosine positional embedding matricesUnderstand layer norm vs batch norm scaling constraints

Projects: 7View Details

Module 5: Embeddings and Vector Databases

Coming Soon

Master vector representation spacing, similarity indexing algorithms, and hybrid metadata keyword searches.

Compare cosine, dot product, and Euclidean distance vector metricsImplement semantic and parent-child chunking parsersConfigure HNSW graph indexing configurations

Projects: 6View Details

Module 6: RAG Engineering

Coming Soon

Build robust retrieval-augmented pipelines integrating document loaders, rerankers, and retrieval evaluations.

Reduce hallucinations by optimizing prompt retrieval contextIntegrate cross-encoder rerankers to improve search recallConstruct ragas evaluation datasets evaluating faithfulness

Projects: 6View Details

Module 7: Structured AI Applications

Coming Soon

Build predictable business workflows enforcing structured JSON schema extractions and intents routing.

Enforce JSON output schemas on language modelsConstruct parsers extracting entities from unstructured text documentsImplement routing classification logic based on intent scores

Projects: 6View Details

Module 8: Agentic AI

Coming Soon

Design autonomous loops combining function call registrations, multi-step planners, and reflection cycles.

Construct robust agent loop engines with exception backoffsMap system functions to JSON schemas for reliable LLM tool callsManage conversational state using sliding context history windows

Projects: 6View Details

Module 9: MCP and Tool Ecosystem

Coming Soon

Establish Model Context Protocol clients, host secure custom servers, and define execution sandboxes.

Build custom MCP server integrations communicating via JSON-RPCSafeguard database write parameters using schema verification filtersConfigure tool execution sandboxes running external shell commands

Projects: 6View Details

Module 10: Multi-Agent Systems

Coming Soon

Orchestrate supervisor hierarchies, agent conversations protocols, and human-in-the-loop validation gates.

Build supervisor graphs allocating sub-tasks to specialized agentsEnforce human approval gates on destructive database updatesTrack system states across concurrent agent-to-agent processes

Projects: 6View Details

Module 11: AI System Design

Coming Soon

Scale model routing hubs. Integrate semantic caches, prompt registries, cost limits, and latency fallbacks.

Integrate OpenInference tracers capturing nested agent stepsBuild semantic caches reducing repeat API query costs by 80%Configure fallback routes switching to open-source models on API timeouts

Projects: 7View Details

Module 12: Deployment and Production AI

Coming Soon

Run models in production. Master Server-Sent Events streams, inputs guardrails, and automated evaluation pipelines.

Implement Server-Sent Events (SSE) streaming model completionsAdd input/output guardrail checks filtering toxic or sensitive termsConfigure automated evaluation pipelines checking schema accuracy on commit

Projects: 7View Details

Portfolio Mastery

Synthesize all learning concepts into production-grade multi-agent capstones with full execution architectures.

Master Capstones

Coming Soon

Synthesize all learnings into enterprise-grade portfolio platforms with full architectural and execution specs.

Architect a multi-agent platform resolving real-world business demandsDocument system architecture, data topologies, and evaluationsDeploy and present system performance characteristics

Final Capstones: 5Explore Capstones