Master the Future of Intelligent Automation
Generative AI, Prompt Engineering, and Agentic AI
Become an expert in Generative AI, prompt engineering, and autonomous AI agents with hands-on projects, real-world applications, and globally recognized certification — designed to launch high-impact AI careers.
Unlock the power of Generative AI, prompt engineering, and autonomous agents with our expert-led, job-focused program. Master tools like OpenAI APIs, LangChain, and Pinecone through hands-on projects. Learn to build generative AI systems, multi-agent workflows, and scalable automation.
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Key Highlights
70+ live interactive session over the course of 6 months
Exclusive access to our Career Portal
220+ hrs of Live interactive Sessions
Live sessions with NIIT Faculy and Industry Expert
24/7 Support
Industry-Curated Curriculum
50+ Industry level Projects & Assesments
100% Job Assitance*
Course content
Module 1: Foundations for Python, AI, and Data Exploration
- What is Python?
- Importance of Python in AI
- Introduction to Artificial Intelligence Types of AI: Narrow, General, and Agentic
- Data Types and Structures
- Ethical Considerations in AI
- Introduction to Data Exploration Techniques (Basic Visualization)
- Introduction to SQL (Basic Queries) Overview of Excel for Data Handling
Module 2 :Python Programming and Data Acquisition
- Python Programming Fundamentals: Variables, Loops, Functions
- Working with Lists, Dictionaries, and Sets
- SQL Fundamentals: Basic Queries and Data Manipulation
- Excel Fundamentals: Data Entry, Formulas, and Functions
- Advanced Excel: PivotTables, Charts, and Advanced Functions
- Data Visualization Techniques (Introduction)
- Data Acquisition Strategies and APIs
Module 3: Advanced Python and AI Foundations
- Object-Oriented Programming in Python
- Numerical Computation with NumPy
- Data Manipulation with Pandas
- Introduction to Machine Learning Concepts
- Neural Networks Overview
- Cloud Computing Basics (AWS, Azure, GCP)
- Basic Data Visualization with Matplotlib and Seaborn
Module 4: Agentic AI Essentials and Frameworks
- Introduction to Agentic AI
- Agentic AI vs. Generative AI vs. Traditional AI
- Building Blocks of Agentic AI
- Autonomous Agents and Human-in-the-Loop Systems
- Single and Multi-Agent Systems
- Agentic AI Frameworks Overview
- Ethical and Responsible AI Practices
Module 5: Agentic AI Architectures and Design Patterns
- Agentic AI Architecture Components
- Perception, Cognitive, and Action Modules
- Agentic AI Design Patterns (Reflection, Tool Use, Planning)
- ReAct and ReWOO Patterns
- Multi-Agent Collaboration Designs
- Security and Scalability Considerations
Module 6: LangChain and AI Pipelines
- LangChain Components: Document Loaders and Text Splitting
- Embeddings and Vector Databases
- LangChain Expression Language (LCEL)
- Building AI Pipelines with LCEL
- Deployment with Langserve
- Workflow Automation Basics
Module 7: Building AI Agents with LangGraph
- LangGraph Fundamentals
- State and Memory Management
- State Schema and Reducers
- Human-in-the-Loop Integration
- Long-Term Memory Implementation
- Agent Deployment Strategies
Module 8: Agentic RAG and Phidata Agents
- Agentic RAG vs. Traditional RAG
- Agentic RAG Architecture
- Adaptive RAG Applications
- Phidata Components: Agents, Tools, Knowledge
- Vector Databases and Embeddings
- Developing Agents with Phidata
Module 9: Multi-Agent Systems and Observability
- Multi-Agent System Concepts
- Collaborative Workflows with CrewAI
- LangGraph for Multi-Agent Designs
- AI Observability with Langfuse and Langsmith
- Tracing and Evaluation Techniques
- AgentOps Implementation
- Deployment and Monitoring Best Practices
Module 10: Cloud-Based Agentic AI Deployment
- Deploying AI Models with AWS Bedrock
- Azure OpenAI and GCP Vertex AI
- Serverless AI Agent Deployment
- Retrieval-Augmented Generation (RAG)
- AI Agent Governance on Cloud
- Scaling AI Solutions
Skills to Master
Python Programming
Data Cleaning and Preprocessing
AI Pipeline Development
Agentic AI Architecture Design
Implementing AI Design Patterns
Building and Deploying AI Agents
Multi-Agent System Development
Agentic RAG Implementation
Cloud-Based AI Deployment
AI Observability and Monitoring
Data Visualization
Communication and Data Storytelling
SQL and Data Exrtractions from Various Databases
Building Visuals from Scratch
Ethical AI Practices
Proficiency in Agentic AI
Tools to master
Master key tools for Agentic AI development, including Python, data manipulation with NumPy and Pandas, and advanced visualization with Matplotlib and Plotly. Learn to build AI pipelines with LangChain, manage agents with LangGraph, and deploy with Docker, while leveraging frameworks like Phidata and CrewAI for advanced agent systems.












Roles You’ll Be Qualified For
Artifical Intelligence / Machine Learning Engineer
Natural Language Processing (NLP) Engineer
AI Specialist
AI Product Specialist/Engineer
Recommendation Systems Engineer
AI Solutions Architect
Machine Learning Operations (MLOps) Engineer
Prompt Engineer
Career Services
Mock Interview Preparation
Priority Access to Career Services
1 : 1 Career Mentorship
Job Board -- Resume Building
100% Placement Assurance*
Soft-Skill Training
Portfolio Building
Certificate of Completion
🎓 Certification Sample
Get a glimpse of the professional certificate you’ll receive upon course completion. Issued by Workpreneur Academy, it validates your expertise in AI, Machine Learning, and Data Science, and showcases your skills to employers worldwide.
Testimonials from Industry Leaders
Course Queries Answered
What prior experience do I need to join this course?
No advanced experience is required! A basic understanding of Python and AI concepts is helpful, but our course is beginner-friendly and designed to support learners at all levels.
Do I get a certificate after completing the course?
Absolutely. Upon successful completion, you’ll receive a globally recognized certification from Workpreneur Academy, showcasing your expertise in Generative AI and Agentic AI.
What is the structure and duration of the program?
This is an 28-week intensive, step-by-step program. Each week covers a progressive topic, starting from AI and data science foundations to advanced subjects like Generative AI, Reinforcement Learning, and MLOps. It includes real-world projects, collaborative exercises, and case studies.
What is Agentic AI, and why is it important?
Agentic AI refers to autonomous AI systems capable of reasoning, planning, and executing tasks independently. It's one of the most in-demand and future-facing skills in the AI landscape.
What kind of support is provided during the course?
You’ll have 24/7 support, 1:1 personalized mentorship, Study Material, Recordings with industry experts like G. Tanuj (Generative AI/ML Engineer), and live sessions for doubt clearing, feedback, and career guidance.