Hours: 24 hrs
Duration: 7 Weeks
 
Custom course content is created to support the Agentic AI/ Data Analytics / ETL / ChatGPT / Prompt Engineering / NLP / MLL / Data Processing Career Path.
 
Course Learning Outcomes
By the end of this course, learners will:
Understand LLM fundamentals and how agentic systems work
Design and implement retrieval-augmented generation (RAG)
Master prompt engineering techniques for performance and reliability
Build autonomous AI agents using agentic workflows
Architect AI applications using real-world frameworks (LangChain, OpenAI functions)
Complete hands-on labs and a final capstone project using agents
 
Course Content:
 
Week 1: Foundations of AI & LLMs (3.5 hrs)
Topics:
AI/ML/Deep Learning refresher
What are Large Language Models (LLMs)
Transformer architecture basics
Types of LLMs (OpenAI, Claude, Mistral, LLaMA)
LLM capabilities and limitations
Use cases in business: copilots, summarization, recommendation
Lab: Run an LLM via API (OpenAI or Hugging Face)
Quiz: AI/LLM fundamentals
Outcome: Understand LLM architecture and business context
 
🔹 Week 2: Prompt Engineering Essentials (3.5 hrs)
Topics:
Prompt structure: instructions, context, input
Prompting techniques: zero-shot, few-shot, chain-of-thought
System vs. user prompts
Role prompting and format engineering
Evaluation and optimization of prompts
Lab: Create and compare various prompt styles (OpenAI Playground)
Quiz: Prompt design patterns
Outcome: Build optimized prompts for common LLM tasks
 
🔹 Week 3: Retrieval-Augmented Generation (RAG) (3.5 hrs)
Topics:
What is RAG? Why use it?
RAG architecture (vector store + LLM)
Embeddings (OpenAI, Hugging Face, Cohere)
Vector databases (FAISS, Pinecone, Chroma)
Chunking, indexing, retrieval strategies
Lab: Build a basic RAG pipeline with PDF ingestion
Quiz: RAG architecture and benefits
Outcome: Retrieve and answer domain-specific content using RAG
 
🔹 Week 4: Introduction to Agentic AI (3.5 hrs)
Topics:
What are AI Agents?
Autonomous vs. tool-using agents
Agent loop: plan → execute → observe → reflect
Tools & frameworks: LangChain agents, OpenAI tools/functions, AutoGPT
Real-world agent use cases: research, coding, data pipelines
Lab: Build a tool-using agent with LangChain + OpenAI
Quiz: Agent types and workflows
Outcome: Understand and build your first AI agent
 
🔹 Week 5: Agentic Workflows & Orchestration (3.5 hrs)
Topics:
Multi-agent systems and task delegation
Agent memory and tool selection
Integration with APIs, databases, spreadsheets, etc.
Autonomous workflows: task decomposition and execution
Challenges: hallucinations, error handling, guardrails
Lab: Multi-step AI assistant with LangChain or crewAI
Quiz: Workflow comprehension and debugging agent plans
Outcome: Deploy a multi-step workflow with agent coordination
 
🔹 Week 6: Agentic Architectures & Deployment (3.5 hrs)
Topics:
Architectural patterns: RAG + Agent + Tool integration
State management, observability, logging
Containerization and deployment (Streamlit, FastAPI, Docker)
Security, rate limits, API keys, fail-safes
Evaluation strategies (auto-eval, human-in-the-loop)
Lab: Package and deploy your agentic app
Quiz: Architecture and deployment best practices
Outcome: Build and deploy a full-stack AI app
 
🔹 Week 7: Capstone Project + Demos (3.5 hrs)
Project Work:
Choose from:
Agent-based document Q&A system
AI data assistant (SQL + Excel workflows)
Code assistant (AI-powered dev helper)
Strategic decision-maker (SWOT, PEST, ROI agent)
Teams or solo
Includes data ingestion, prompts, agent design, and deployment
Demo & Review: Each team presents their solution
Certificate of Completion issued upon successful project submission
 
** Each module includes project work, MCQ Quiz and a certificate 
 
Career Coaching Sessions:
- Resume support, review, and guidance
- LinkedIn profile review and suggestions
- Interview tips and tricks
- 1 video interview and feedback session
- Career coaching and clarification
- Sample resumes templates
- Job reference and background check support
 
Features:
- Customized course content
- Online and in-person live instructor classes
- Class re-take option
- Live streaming for the remote students
- Video recording capability to catch up the missed class
- Hands-on labs and projects
- Mock certification tests
- Real case studies for the real project experience
- Professional instructors who bring real-life experiences in the classroom
- Interview preparation support
- Internship and staffing support
 
For more info, call us