CodeAgents Mastery

Agentic AI Engineer Roadmap

Batch: 2026-Q2

www.codeagents.in

Program Vision

Master the complete spectrum of AI—from core literacy to building and deploying autonomous, multi-agent systems. This curriculum is designed for engineers moving from simple prompt engineering to complex Agentic Architectures.

Phase 01: AI Literacy & Setup

AI Decoded (AI vs ML vs DL vs GenAI), Supervised/Unsupervised Learning models, Deep Learning (ANN, DNN, CNN), Professional Environment setup (Gemini, OpenAI, Virtual Envs), and Billing reality checks.

Phase 02: GenAI & Prompt Engineering

Foundation Models internals, LLM Mechanics (Tokens, Parameters, Temperature), Zero-shot/One-shot/Few-shot methodologies, Prompting Principles, and Introduction to RAG & Guardrails.

Phase 03: Professional Orchestration

LangChain Essentials (LCEL, Chunking, Embeddings), LangServe deployment, LangGraph Fundamentals (Nodes, Edges, State, Checkpointers), Subgraphs, and Human-in-the-Loop (HITL) patterns.

Phase 04: Multi-Agent Frameworks

CrewAI (Agents, Tasks, Tools), Microsoft AutoGen (Conversation Patterns, Code Safety), Agno/Phidata (Data Insights), and Agentic RAG (Adaptive RAG, LlamaIndex).

Phase 05: Agentic Ops & Observability

LangSmith for Traceability, AgentOps, Langfuse monitoring, Platform Comparison, and Enterprise-grade Security Guardrails/Safety protocols.

Phase 06: No-Code & Market Mastery

N8N Visual Architecture, Lovable.ai, Julius AI, Wispr Flow, NotebookLM research workflows, Custom GPTs, and Market Tool Strategy.

Phase 07: Private AI & Data Sovereignty

Ollama (Local LLM Execution), HuggingFace Hub Mastery, and PII Masking (Building Secure Agents for Redacting Sensitive Personal Data).