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Generative AI & Agentic AI Development

Agentic AI represents the next frontier in AI-driven applications—systems designed to think, plan, reflect, and take action on behalf of users. Our course empowers learners with comprehensive skills to build intelligent, autonomous, and multi-modal Agentic AI systems. You'll gain hands-on experience with Generative AI LLMs, Retrieval-Augmented Generation (RAG), planning agents, tool integration, and agent orchestration frameworks.

This Generative AI and Agentic AI development course equips you with the hands-on skills to build real-world agentic systems—from standalone agents to complex multi-agent ecosystems.

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Certification: Generative AI and Agentic AI

Most In-Demand and Highly Paid Skills

Learning Paths

Certification (4 Months) | Diploma (6 Months)

10000+ Learners

Trained Students Across The Country

360° Career Support

Resume Building, Interview Prep, and Access to Partner Companies

Course Key Highlights

Immersive Hybrid Learning Experience (Classroom + Online)
Internationally Accredited Certification in Generative & Agentic AI
100+ Hours of Intensive Training and Applied Learning
Industry-Grade Agentic AI Capstone Projects
Expertise in Generative AI Tools (LLMs, Diffusion Models, etc.)
Priority Access to Agentic AI Career Opportunities
Mastery of Advanced Agentic Architectures & Design Patterns
Multi-modal RAG (Retrieval-Augmented Generation) Systems
Agent Deployment & Operational Workflows (AgentOps)
Interactive Sessions with Autonomous AI Agents
Efficient Management of Vector Databases for Scalable AI
Advanced Prompt Engineering & Autonomous Decision-Making
Practical Training in Building Custom AI Agents
Live Troubleshooting & Concept Clarification Sessions
End-to-End Career Enablement & Professional Branding
Personalized Career Mentorship with AI Leaders
Tailored Job Interview Coaching with Industry Experts
Direct Connect to Recruitment Networks of Leading MNCs

Globally Recognized Generative AI Course in India

Step into the dynamic world of Generative AI and Agentic AI Development with India’s most comprehensive and globally accredited training institute. This immersive program covers the full development lifecycle of intelligent, autonomous, and multi-modal Agentic AI systems, utilizing cutting-edge technologies such as Generative AI LLMs, Retrieval-Augmented Generation (RAG), planning agents, tool integration, and agent orchestration frameworks. You'll gain practical expertise in leading frameworks like LangChain, AutoGen, and CrewAI, all thoroughly explored within our specialized curriculum.

Why Choose Our Generative AI Course?

Launch your career in Generative AI and Agentic AI Development with one of India’s top-tier training institutes, renowned for shaping the success of AI professionals across the globe. Our program is backed by a strong legacy of excellence and a team of seasoned trainers with extensive industry experience. The curriculum is meticulously designed to provide you with the technical skills, strategic insights, and hands-on proficiency required to thrive in the fast-evolving AI ecosystem. Whether you're aiming to break into the field or elevate your existing expertise, this course offers the ideal foundation for long-term success in Generative and Agentic AI.

Programming Tools, Libraries & Technologies Covered

Keras
Scikit-Learn
Seaborn
TensorFlow
NLP

Generative AI Tools, Libraries & Technologies Covered

Gamma
Gemini
Gradio
HF
OpenAI

Course Overview

This comprehensive course dives into the core concepts, models, and development practices for both Generative Artificial Intelligence and autonomous Agentic AI systems. From understanding latent spaces to building multi-agent architectures, you will gain the skills to design, develop, and deploy intelligent applications.
  • Defining Generative vs. Discriminative Models
  • Historical Context and Evolution of AI
  • Key Concepts: Latent Space, Sampling, Loss Functions
  • Real-world Applications and Impact
  • Review of Neural Network Basics
  • Autoencoders and their Role in Generation
  • VAE Architecture and Reparameterization Trick
  • Evidence Lower Bound (ELBO) Optimization
  • Applications of VAEs (e.g., Image Generation, Style Transfer)
  • Generator and Discriminator Networks
  • Training Dynamics and Challenges (Mode Collapse)
  • Advanced GAN Architectures (WGAN, CycleGAN, StyleGAN)
  • Practical Uses of GANs (e.g., Image Synthesis, Data Augmentation)
  • Recurrent Neural Networks (RNNs) for Sequence Generation
  • Transformer Architecture and Attention Mechanism
  • GPT Family and Large Language Models (LLMs)
  • Text Generation, Summarization, and Translation
  • Denoising Diffusion Probabilistic Models (DDPMs)
  • Forward and Reverse Diffusion Processes
  • Applications in Image and Audio Generation (e.g., Stable Diffusion)
  • Definition and Characteristics of Intelligent Agents
  • Agent Environments and Percepts
  • Agent Function and Agent Program
  • Perception and Sensors
  • Cognition, Reasoning, and Decision Making
  • Action and Effectors
  • Memory and State Management
  • Reactive Agents (Simple Reflex Agents)
  • Deliberative Agents (Goal-based, Utility-based)
  • Hybrid Agents and Subsumption Architecture
  • Leveraging LLMs for Agentic Reasoning
  • Prompt Engineering for Agent Control
  • Tool Use and Function Calling
  • Short-term Memory (Context Window)
  • Long-term Memory (Vector Databases, Semantic Search)
  • External Knowledge Integration
  • Task Planning and Execution Frameworks
  • Self-Reflection and Metacognition in Agents
  • Iterative Improvement and Learning
  • Concepts of Multi-Agent Interaction
  • Agent Communication Protocols
  • Collaboration vs. Competition in MAS
  • Swarm Intelligence and Emergent Behavior
  • Overview of Frameworks (e.g., LangChain, AutoGen principles)
  • Building Custom Agent Workflows
  • Image and Video Generation Pipelines
  • Text Synthesis and Content Creation Tools
  • Code Generation and Debugging Assistants
  • Agents for Customer Service and Support
  • Agents for Data Analysis and Research
  • Autonomous Decision-Making Systems
  • Cloud-based Deployment (AWS, GCP, Azure)
  • Edge Device Deployment Considerations
  • Monitoring, Logging, and Versioning
  • Metrics for Generative Model Performance
  • Agent Performance Evaluation and Benchmarking
  • Bias and Fairness in Generated Content
  • Misinformation, Deepfakes, and Content Authenticity
  • Intellectual Property and Copyright Challenges
  • Safety and Control of Autonomous Agents
  • Transparency and Explainability (XAI)
  • Privacy and Data Protection in Agent Systems
  • Trends in Generative AI Research
  • Pathways to Artificial General Intelligence (AGI)
  • Human-AI Collaboration and Societal Impact

Enrollment Process

Step 1
Application Submission

Prospective students complete and submit an online application form, providing essential profile details for enrolling in the Course / Training.

Step 2
Application Review and Discovery

After a thorough review of applications by the academics team, qualified candidates receive a call from our experienced counselor who guides them with the details of the Course / Training

Step 3
Enrollment Offer

Successful candidates receive an offer of admission, and upon acceptance, proceed to complete the enrollment process. This includes submitting necessary documents, paying fees, and attending an orientation session to kickstart their educational journey