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GEN AI & AGENTIC AI

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From Generative Models to Autonomous AI Agents—End-to-End Intelligence.

Course Overview

The Gen AI & Agentic AI – Industry-Oriented Certification Program is a comprehensive, hands-on training program designed to equip learners with both foundational knowledge of Generative AI and advanced skills in building autonomous AI agents. This course bridges the gap between using AI models and engineering intelligent systems that can reason, plan, act, and collaborate to solve real-world business problems.The program starts with core concepts of AI, Large Language Models (LLMs), and prompt engineering, and gradually progresses into agent architectures, memory systems, orchestration frameworks, multi-agent collaboration, and enterprise automation use cases. Learners will gain practical experience using modern tools and frameworks such as OpenAI APIs, LangChain,  CrewAI, vector database sand RAG pipelines.

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Course Type

Data science with AI

Duration

3 Months

Delivery mode

Online / Offline

Trainer

Hrishikesh Jadhao

Pre-requisites

• Basic understanding of programming concepts (Python preferred)
• Fundamental knowledge of AI / ML concepts (helpful but not mandatory)
• Logical thinking and problem-solving mind-set

Who can Enroll?

• Software Developers
• Data Analysts & Data Scientists
• AI / ML Engineers
• IT Professionals & Solution Architects
• Engineering / Computer Science Students
• Product Managers & Automation Leads

Why Learn Agentic AI?

Build autonomous AI agents that can reason, plan, and act

Work with next-generation AI agent frameworks

Apply AI agents to real-world business problems

Design enterprise-grade AI automation solutions

Gain future-ready skills aligned with industry demand

Syllabus Modules

Module 1: Foundations of Generative AI & Agentic AI

• Introduction to Generative AI and Agentic AI
• Evolution of AI systems
• Key differences between traditional AI, GenAI, and Agentic AI
• Industry use cases and applications

• Large Language Models (LLMs)
• Prompt engineering fundamentals
• Reasoning, planning, and decision-making
• Tokens, embeddings, and transformers

• Reactive, deliberative, and hybrid agents
• Single-agent vs multi-agent systems
• Role-based and goal-driven agents
• Agent workflows and orchestration

• OpenAI APIs
• LangChain fundamentals
• AutoGPT, CrewAI, and similar agent frameworks
• Vector databases and memory stores

• Short-term and long-term memory
• Context management strategies
• Retrieval Augmented Generation (RAG)
• Knowledge base integration

• Workflow automation using AI agents
• Data processing and reporting agents
• Customer support and chatbot agents
• Enterprise automation scenarios

• Agent communication protocols
• Coordination and collaboration strategies
• Conflict resolution between agents
• Scalable multi-agent systems

• Agent performance evaluation
• Prompt and workflow optimization
• Logging, monitoring, and debugging
• Reliability and scalability considerations

• Ethical considerations in GenAI and Agentic AI
• Bias, fairness, and transparency
• Data security and privacy
• AI governance and compliance

• End-to-end AI agent project
• Real-world business case implementation
• Deployment considerations
• Project presentation and review

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Certificate

GEN AI & AGENTIC AI

  • Minimum 80% attendance is required to ensure consistent learning and practice.
  • Successful completion of the project / capstone project assigned during the course
  • Mandatory participation in mock tests, practice exams, or internal evaluations conducted by the institute.
  • Completion of all practical assignments, hands-on labs, and exercises covered in the training
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