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Cutting-Edge Agentic AI 2026

Generative AI & Agentic AI
Build Autonomous Multi-Agent Systems & Production GenAI.
Get Placed in Top MNCs.

Master Generative AI & Agentic AI with LangGraph, CrewAI, AutoGen, Multi-Agent Systems, OpenAI/Claude APIs & autonomous task automation. 1-on-1 Mock Interview SessionsDedicated Support.

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100+ Hours Live Hands-on
18+ AI Tools Modern Stack
Production Capstone Labs
1-on-1 Mock Interview SessionsDedicated Support Support
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& Real Data
100% Career Guidance & Interview Prep
Generative AI & Agentic AI Certification Course Student Working on AI Projects
LangGraph
LangGraph
CrewAI
CrewAI
AutoGen
AutoGen
LangChain
LangChain
OpenAI GPT-4o
OpenAI GPT-4o
Anthropic Claude
Anthropic Claude
ChromaDB
ChromaDB
Docker
Docker
🖥️Live Interactive Coding
👤AI Principal Mentors
📋Enterprise Capstones
💼Career Mentorship Assurance

Start Your Career in Generative AI & Agentic AI

Get personalized curriculum & free 1-on-1 counseling.

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◆ Enterprise-Aligned Curriculum

Complete Generative AI & Agentic AI Curriculum — Foundations to Enterprise Scale

Engineered in collaboration with principal engineers from leading product and Fortune 500 AI teams.

01

GenAI Foundations, Transformer Architectures & LLM APIs

⏱ In-Depth Module
⚡
  • Transformer Architecture: Multi-Head Attention, Encoders, Decoders & Tokenization
  • Working with State-of-the-Art APIs: OpenAI, Anthropic Claude, Google Gemini & Groq
  • Advanced Prompt Engineering: Few-Shot, Chain-of-Thought (CoT), Tree-of-Thought (ToT)
→
02

Agentic Architectures, LangChain & Tool Use Execution

⏱ In-Depth Module
⚡
  • ReAct Pattern: Combining Reasoning and Action in iterative agentic loops
  • LangChain v0.3 Core: Runnables, LCEL (LangChain Expression Language)
  • Custom Tool Creation: Web search (Tavily), database querying, Python REPL tools
→
03

Stateful Multi-Agent Workflows with LangGraph

⏱ In-Depth Module
⚡
  • Why LangGraph: Escaping DAG limitations with cyclic graphs & state management
  • State Definition: TypedDict, Channels, Reducers and State schema validation
  • Nodes and Conditional Edges: Deterministic vs Dynamic Router transitions
→
04

Local Open-Source LLMs & Multimodal Agent Intelligence

⏱ In-Depth Module
⚡
  • Running Local LLMs with Ollama and vLLM (Llama 3.3, DeepSeek-R1, Qwen 2.5)
  • Quantization Formats: GGUF, AWQ, GPTQ for consumer GPU efficiency
  • Multimodal Agents: Vision-Language Models (VLMs), OCR & Diagram Interpretation
→

Detailed Module-by-Module Breakdown

Click each module below to explore technical topics, coding labs, and tools covered.

Module 01

GenAI Foundations, Transformer Architectures & LLM APIs

16 Hours

Master the inner mechanics of transformers, self-attention mechanisms, and API architectures for GPT-4o, Claude 3.5 Sonnet, and open-weights models.

Core Topics & Competencies:

  • ✔ Transformer Architecture: Multi-Head Attention, Encoders, Decoders & Tokenization
  • ✔ Working with State-of-the-Art APIs: OpenAI, Anthropic Claude, Google Gemini & Groq
  • ✔ Advanced Prompt Engineering: Few-Shot, Chain-of-Thought (CoT), Tree-of-Thought (ToT)
  • ✔ Structured Outputs: Enforcing JSON Schemas with Pydantic & Instructor
  • ✔ Function Calling: Equipping LLMs with external programmatic tools
  • ✔ Tokenization, Cost Calculations & Latency Benchmarking
💻 Hands-on Capstone Lab:

Building a High-Speed Structured Research & Extraction Bot with Pydantic and GPT-4o.

Python 3.11OpenAI APIAnthropic ClaudePydanticInstructor
Module 02

Agentic Architectures, LangChain & Tool Use Execution

18 Hours

Transition from passive prompt-response chains to dynamic autonomous agent loops with reasoning engines.

Core Topics & Competencies:

  • ✔ ReAct Pattern: Combining Reasoning and Action in iterative agentic loops
  • ✔ LangChain v0.3 Core: Runnables, LCEL (LangChain Expression Language)
  • ✔ Custom Tool Creation: Web search (Tavily), database querying, Python REPL tools
  • ✔ Agent Memory Architectures: Short-term message history vs Persistent entity memory
  • ✔ Plan-and-Solve Agents: Task decomposition and sequential execution
  • ✔ Error Handling & Graceful Fallbacks in Non-Deterministic AI Loops
💻 Hands-on Capstone Lab:

Autonomous Technical Due Diligence Agent with Web Scraping, Code Execution & PDF Output.

LangChainTavily APIPython REPLChromaDBLCEL
Module 03

Stateful Multi-Agent Workflows with LangGraph

20 Hours

Architect complex, cyclical agent workflows with state machines, human-in-the-loop checkpoints, and branching.

Core Topics & Competencies:

  • ✔ Why LangGraph: Escaping DAG limitations with cyclic graphs & state management
  • ✔ State Definition: TypedDict, Channels, Reducers and State schema validation
  • ✔ Nodes and Conditional Edges: Deterministic vs Dynamic Router transitions
  • ✔ Human-in-the-Loop (HITL): Breakpoints, approval gates, state modification
  • ✔ Time-Travel & Checkpointing: MemorySaver, SQLite, and PostgreSQL persistence
  • ✔ Hierarchical Agent Teams: Supervisor patterns and sub-graph agent orchestration
💻 Hands-on Capstone Lab:

Enterprise Multi-Agent Customer Support Swarm with Human Approval Breakpoints and PostgreSQL State.

LangGraphLangChainPostgreSQLFastAPIUvicorn
Module 04

Role-Playing Agent Swarms with CrewAI & Microsoft AutoGen

18 Hours

Orchestrate specialized multi-agent teams with delegated responsibilities, inter-agent debates, and shared goal alignment.

Core Topics & Competencies:

  • ✔ CrewAI Architecture: Agents, Tasks, Tools, and Hierarchical Crews
  • ✔ Defining Expert Personas: Role, Goal, Backstory & Temperature calibration
  • ✔ Task Delegation & Inter-Agent Communication Protocols
  • ✔ Microsoft AutoGen: ConversableAgent, GroupChat, and GroupChatManager
  • ✔ Code Generation & Sandboxed Docker Execution with AutoGen
  • ✔ Comparative Analysis: When to choose LangGraph vs CrewAI vs AutoGen
💻 Hands-on Capstone Lab:

Full-Cycle Autonomous Software Engineering Crew (Product Manager, Architect, Coder, QA Engineer).

CrewAIAutoGenDockerGitOllama
Module 05

Local Open-Source LLMs & Multimodal Agent Intelligence

14 Hours

Run powerful open-source foundation models locally on edge workstations with private data isolation.

Core Topics & Competencies:

  • ✔ Running Local LLMs with Ollama and vLLM (Llama 3.3, DeepSeek-R1, Qwen 2.5)
  • ✔ Quantization Formats: GGUF, AWQ, GPTQ for consumer GPU efficiency
  • ✔ Multimodal Agents: Vision-Language Models (VLMs), OCR & Diagram Interpretation
  • ✔ Audio & Voice Agents: Whisper API, Text-to-Speech & Real-time WebRTC Agent Loops
  • ✔ Private RAG with Local Vector Stores for High-Security Enterprise Compliance
💻 Hands-on Capstone Lab:

Air-Gapped Private Document Auditing Agent using Ollama, DeepSeek-R1 and Local ChromaDB.

OllamavLLMDeepSeek-R1Llama 3.3Whisper
Module 06

Enterprise Agent Deployment, Guardrails, Evaluation & Security

16 Hours

Productionize, monitor, secure and evaluate multi-agent applications for enterprise scalability.

Core Topics & Competencies:

  • ✔ Agent Security: Prompt Injection defense, Jailbreak prevention & Guardrails
  • ✔ Implementing NeMo Guardrails and Llama Guard for safety compliance
  • ✔ Agent Observability & Tracing: LangSmith, Langfuse, OpenInference
  • ✔ Evaluation Metrics for Agents: Success rate, tool call accuracy, cost per task
  • ✔ Containerization with Docker & Kubernetes Deployment for Auto-Scaling
  • ✔ Cost Optimization: Prompt caching, token throttling & model routing gateways
💻 Hands-on Capstone Lab:

Full Production Multi-Agent Microservice deployed with Docker, FastAPI, LangSmith Tracing & NeMo Guardrails.

LangSmithNeMo GuardrailsDockerKubernetesFastAPI

Tools & Frameworks You Will Master

Gain hands-on proficiency in the exact modern tech stack used across Fortune 500 tech teams.

LangGraph
LangGraph
CrewAI
CrewAI
AutoGen
AutoGen
LangChain
LangChain
OpenAI GPT-4o
OpenAI GPT-4o
Anthropic Claude
Anthropic Claude
ChromaDB
ChromaDB
Docker
Docker
LAUNCHPAD PRO

Build Experience That Gets You Interview-Ready

Real project work. Agile exposure. Mentor feedback. A portfolio you can talk about in interviews.

Live Project Work
Agile + Jira Workflow
Team Collaboration
Mentor Code &
Project Reviews
Resume + Interview
Prep
Completion Certificate
Explore LaunchPad Pro → See What You'll Work On →
LaunchPad Pro Student Experience
Hands-on • Mentor-led

Already trained. Now build proof of your skills.

Turn learning into practical experience you can discuss with confidence.

  • Work on live enterprise projects
  • Build a real-world portfolio
  • Use Agile workflows & Jira
  • Get mentor feedback
  • Practice with mock interviews
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Frequently Asked Questions

Everything you need to know about the Generative AI & Agentic AI Certification Course, batches, prerequisites & Career Mentorship assurance.

What is the difference between Generative AI and Agentic AI?

Generative AI produces content (text, code, images) based on user prompts in a single turn. Agentic AI goes further by autonomously reasoning, breaking high-level objectives into tasks, using external tools (web search, databases, APIs, code execution), correcting its own errors, and collaborating in multi-agent swarms without constant human intervention.

What prerequisites are required for this course?

Basic proficiency in Python programming (loops, functions, OOP basics) and an understanding of APIs is recommended. No prior machine learning PhD or heavy math is required; we teach GenAI and Agentic architectures from the ground up.

Which agentic frameworks are covered in hands-on labs?

You will master the industry standard frameworks: LangChain v0.3, LangGraph for cyclic graph workflows, CrewAI for role-playing agent crews, Microsoft AutoGen for conversational swarms, and Ollama for running local open-weights models.

Does 4Achievers provide Career Guidance & Interview Prepfor Generative AI & Agentic AI?

Yes! 4Achievers provides 1-on-1 Mock Interview SessionsDedicated Support, dedicated mentor portfolio reviews, mock agent architecture interviews, and interview drives across our 500+ tech hiring partners seeking GenAI and Agentic AI engineers.

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