• Course Type
    Data science with AI
  • 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
  • Delivery Mode
    Online/Offline
  • Trainer
    Hrishikesh Jadhao
  • Duration
    3 Months
  • Who can enroll?
  • • Software Developers
  • • Data Analysts & Data Scientists
  • • AI / ML Engineers
  • • IT Professionals & Solution Architects
  • • Engineering / Computer Science Students
  • • Product Managers & Automation Leads

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.

Why Learn Agentic AI?

Syllabus Modules

• 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

Get
Certificate

GEN AI & AGENTIC AI
Call Now Button

    Get In Touch With Us

      Details To Get Download Link