Gen AI Online Training
- 70 hours of structured Generative AI training designed for beginner to advanced learners
- Covers Prompt Engineering, Large Language Models (LLMs), RAG, AI Agents, Multimodal AI, and GenAI application development
- Aligned with current industry trends and enterprise AI adoption requirements
- Hands-on exposure to leading AI platforms including ChatGPT, Gemini, Claude, Copilot, and Hugging Face
- Practical implementation of AI-powered chatbots, workflow automation, and intelligent assistants
- Interactive live sessions led by experienced AI practitioners and industry-certified trainers
- Hands-on labs using real-world business use cases, datasets, and enterprise AI workflows
- Capstone project focused on solving real business problems using Generative AI technologies
- Coverage of AI ethics, governance, security, compliance, and responsible AI practices
- Continuous learning support with assessments, practical exercises, and guided project mentoring
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GEN AI Training Program
Gen AI Online Training
This program provides an end-to-end foundation in Generative AI — from understanding foundational models to deploying enterprise-grade AI solutions. The curriculum is built for both technical professionals and business leaders looking to harness the power of Gen AI in real-world contexts.
Course Overview
Duration
70 HoursStudents Enrolled
62+Training Mode
Live Instructor TrainingHands-On Projects
Capstone Projects on Real Time DataTrainer Experience
5+ Years Industry Expert TrainersSession Recordings
Life Time AccessPost-Training Support
3 MonthsWhat You'll Learn
- Understand the architecture and inner workings of large language models (LLMs), including GPT, Gemini, Claude, and open-source alternatives like LLaMA and Mistral
- Master prompt engineering techniques — zero-shot, few-shot, chain-of-thought, and advanced prompting strategies for optimized AI outputs
- Build and deploy AI-powered applications using APIs from OpenAI, Anthropic, Google, and open-source frameworks
- Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases like Pinecone, Weaviate, and ChromaDB
- Fine-tune pre-trained models on custom datasets using techniques like LoRA, PEFT, and instruction tuning
- Develop AI agents and autonomous workflows using tools like LangChain, LlamaIndex, AutoGen, and CrewAI
- Apply Gen AI to real business use cases including content generation, summarization, code assistance, customer service automation, and document intelligence
- Understand AI safety, hallucination mitigation, responsible AI practices, and governance frameworks for enterprise deployment
- Integrate Gen AI into existing enterprise systems via APIs, microservices, and cloud platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI)
- Evaluate, monitor, and optimize Gen AI model performance using benchmarking tools and evaluation frameworks
Pro Tip:This Generative AI course is ideal for IT professionals, data scientists, product managers, and business leaders who want to build, deploy, or leverage AI solutions in their organizations.
Questions about the course? Contact our support team
Certification Value
GEN AI Value in Global Market
Leading global organizations actively hiring Generative AI professionals include Google, Microsoft, Amazon, Meta, Accenture, IBM, Infosys, TCS, Wipro, and hundreds of AI-first startups worldwide.
Course Overview
Overview
Generative AI Certification is designed to validate professional skills in using modern AI tools and frameworks to build intelligent applications and automate business workflows. The program equips learners with practical knowledge of Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and multimodal AI.
Generative AI enables professionals to create text, images, code, and automated workflows using tools such as ChatGPT, Gemini, Claude, and open-source models like Llama and Mistral. With minimal coding and the right prompting techniques, users can build AI-powered assistants, chatbots, document search systems, and productivity solutions that solve real business problems.
This certification-focused training provides hands-on experience with Python, APIs, LangChain, LlamaIndex, vector databases, and deployment tools such as Streamlit and Gradio. Participants learn how to design, develop, and deploy enterprise-ready GenAI applications while applying best practices for responsible AI, data privacy, governance, and model evaluation.
By completing this program, learners gain the industry-relevant skills needed to leverage Generative AI across domains such as software development, customer support, marketing, operations, finance, and education, making them well-prepared for emerging roles in AI and intelligent automation.
Theory Hours: 4 | Lab Hours: 2 | Total: 6 Hours
Topics Covered
- Introduction to AI, ML, and Deep Learning
- Evolution of Generative AI
- Foundation Models and LLMs
- Overview of ChatGPT, Gemini, Claude, and Llama
- Industry applications of GenAIHands-on Labs & Activities
- Compare outputs from multiple LLMs
- Identify hallucinations and biases
- Industry use-case brainstorming activity
Theory Hours: 4 | Lab Hours: 4 | Total: 8 Hours
Topics Covered
- Prompt engineering fundamentals
- Zero-shot, few-shot, and chain-of-thought prompting
- Role prompting and system prompts
- Prompt optimization and evaluation
- Structured outputs and JSON promptingHands-on Labs & Activities
- Prompt engineering challenge
- Build reusable prompt templates
- Generate structured AI outputs
- AI persona simulation exercises
Theory Hours: 4 | Lab Hours: 2 | Total: 6 Hours
Topics Covered
- Overview of AI ecosystems
- AI tools for content, coding, research, and automation
- ChatGPT, Gemini, Copilot, Perplexity
- Image generation tools
- AI workflow integrationHands-on Labs & Activities
- AI-assisted content creation
- AI coding assistant exercises
- Image generation practice
Theory Hours: 3 | Lab Hours: 5 | Total: 8 Hours
Topics Covered
- Python basics for AI
- Working with APIs
- Using OpenAI and Hugging Face APIs
- Environment setup and API management
- Building AI-powered scriptsHands-on Labs & Activities
- Build a text summarizer
- Create a chatbot using APIs
- Hands-on Hugging Face exercises
- Mini AI application development
Theory Hours: 4 | Lab Hours: 4 | Total: 8 Hours
Topics Covered
- Transformers, embeddings, and attention
- Context windows and inference
- Vector databases
- Retrieval-Augmented Generation (RAG)
- Open-source LLM ecosystemHands-on Labs & Activities
- Create embeddings
- Build semantic search
- Simple RAG pipeline implementation
- Hallucination testing exercise
Theory Hours: 4 | Lab Hours: 6 | Total: 10 Hours
Topics Covered
- Building AI chatbots
- Document querying systems
- LangChain and LlamaIndex
- Workflow automation
- Deployment basics with Streamlit/GradioHands-on Labs & Activities
- Build a RAG chatbot
- PDF document querying application
- Deploy a simple AI app
- Workflow automation implementation
Theory Hours: 3 | Lab Hours: 3 | Total: 6 Hours
Topics Covered
- Introduction to AI agents
- Tool calling and orchestration
- Autonomous workflows
- Human-in-the-loop systems
- Enterprise AI agentsHands-on Labs & Activities
- Build a simple AI agent
- Multi-step automation workflow
- AI research assistant implementation
Theory Hours: 2 | Lab Hours: 2 | Total: 4 Hours
Topics Covered
- Introduction to multimodal AI
- Vision-language models
- Speech-to-text systems
- Document AI and OCR
- AI image analysisHands-on Labs & Activities
- Image prompting lab
- Speech-to-text demo
- Document AI practical
Theory Hours: 4 | Lab Hours: 1 | Total: 5 Hours
Topics Covered
- LLM evaluation techniques
- Responsible AI
- Bias and fairness
- Data privacy and compliance
- AI governance frameworksHands-on Labs & Activities
- Prompt evaluation exercise
- AI risk assessment case study
Theory Hours: 1 | Lab Hours: 7 | Total: 8 Hours
Topics Covered
- End-to-end GenAI solution design
- Deployment and presentation
- Documentation and evaluation
- Career pathways and portfolio buildingHands-on Labs & Activities
- Capstone implementation
- Project deployment
- Final presentation and demoTools & Technologies Covered
- ChatGPT
- Gemini
- Claude
- GitHub Copilot
- OpenAI APIs
- Hugging Face
- LangChain
- LlamaIndex
- Streamlit
- Gradio
- Python
- Vector Databases
- Midjourney
- DALL·E
Benefits
-
Lifetime access to session recorded videos for future learning
All recording during the class will be shared with the students for future use.
-
Industry-Recognized Certification Preparation
Comprehensive preparation aligned with Microsoft standards, providing the 30 hours of dedicated training.
-
FREE Doubt Clearing Sessions
Weekly & Monthly doubt clearing sessions free of cost
-
Exam preparation Videos
Get PL-100 exam preparation videos to boost your knowledge on the types of questions you need to prepare for.
-
Study Material
Additional guides/materials to give you sights into latest updates of Power BI
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