Generative AI Course in Jaipur – Learn GenAI, LLMs & Prompt Engineering
Build practical future-ready AI skills with Groot Academy’s Generative AI Course in Jaipur. Learn Generative AI fundamentals, Large Language Models, prompt engineering, AI content generation, image and video generation concepts, retrieval augmented generation, AI agents, application development, APIs, deployment and responsible AI through hands-on practice and projects.
What You Will Learn
- Generative AI fundamentals and real-world applications
- Large Language Models and transformer concepts
- Prompt engineering and prompt optimization
- AI-powered text, content, image and video workflows
- Embeddings and vector database fundamentals
- Retrieval Augmented Generation concepts
- Building AI chatbots and knowledge assistants
- AI agents and workflow automation concepts
- Python and APIs for Generative AI applications
- Generative AI deployment, ethics and live projects
Related Courses
Expand your learning with our Artificial Intelligence Course in Jaipur, Machine Learning Course in Jaipur, Data Science Course in Jaipur and Python Programming Course in Jaipur.
Practical Learning and Career Preparation
Create practical projects through Live Project Training, explore Internship Programs and review our Placement Assistance opportunities.
Frequently Asked Questions
Who can join this Generative AI course?
Students, graduates, developers, working professionals and beginners interested in AI can build their understanding through the structured curriculum.
Will I learn prompt engineering and LLM concepts?
Yes. The course covers prompt engineering, Large Language Model concepts, transformers, embeddings and practical AI application workflows.
Are practical Generative AI projects included?
Yes. The curriculum includes chatbot, RAG, AI assistant, content automation and end-to-end Generative AI capstone projects.
Curriculum
- 15 Sections
- 150 Lessons
- 4 Weeks
- Introduction to Generative AI10
- 1.1Introduction to Generative AI
- 1.2How Generative AI Works
- 1.3Generative AI vs Traditional AI
- 1.4Types of Generative AI Models
- 1.5Real-World Applications of Generative AI
- 1.6Generative AI Industry and Career Opportunities
- 1.7Understanding Generative AI Use Cases
- 1.8Generative AI Tools and Ecosystem
- 1.9Benefits and Limitations of Generative AI
- 1.10Setting Up Your Generative AI Learning Environment
- AI and Machine Learning Fundamentals10
- 2.1Introduction to Artificial Intelligence
- 2.2Introduction to Machine Learning
- 2.3Supervised and Unsupervised Learning Overview
- 2.4Introduction to Deep Learning
- 2.5Artificial Neural Networks Basics
- 2.6Training AI Models
- 2.7Understanding Datasets
- 2.8Features and Labels
- 2.9Model Evaluation Concepts
- 2.10AI and Machine Learning Fundamentals Practice
- Python for Generative AI10
- Large Language Models10
- Transformer Architecture10
- Prompt Engineering Fundamentals10
- Advanced Prompt Engineering10
- 7.1Prompt Optimization Techniques
- 7.2Structured Output Prompts
- 7.3JSON and Data Extraction Prompts
- 7.4Content Generation Prompts
- 7.5Research and Analysis Prompts
- 7.6Code Generation Prompts
- 7.7Image Generation Prompts
- 7.8Multi-Step Prompt Workflows
- 7.9Prompt Testing and Iteration
- 7.10Advanced Prompt Engineering Project
- Generative AI for Content10
- 8.1AI Text Generation Fundamentals
- 8.2Blog and Article Generation
- 8.3Social Media Content Generation
- 8.4Marketing Copy Generation
- 8.5Email Content Generation
- 8.6Content Summarization
- 8.7Content Rewriting and Editing
- 8.8Translation and Localization Concepts
- 8.9Building AI Content Workflows
- 8.10AI Content Generation Project
- Image and Video Generative AI10
- 9.1Introduction to AI Image Generation
- 9.2Understanding Text-to-Image Models
- 9.3Writing Effective Image Prompts
- 9.4Image Styles and Composition
- 9.5Image Editing Concepts
- 9.6Introduction to AI Video Generation
- 9.7Text-to-Video Concepts
- 9.8AI Video Workflow Concepts
- 9.9Responsible Use of Generated Media
- 9.10Generative Media Project
- Embeddings and Vector Databases10
- 10.1Introduction to Embeddings
- 10.2Understanding Semantic Search
- 10.3Creating Text Embeddings
- 10.4Similarity Search Concepts
- 10.5Introduction to Vector Databases
- 10.6Storing and Retrieving Embeddings
- 10.7Document Chunking Strategies
- 10.8Metadata and Filtering Concepts
- 10.9Vector Search Applications
- 10.10Embeddings and Search Project
- Retrieval Augmented Generation10
- AI Chatbots and Assistants10
- 12.1Introduction to AI Chatbots
- 12.2Designing Conversational Experiences
- 12.3User Input and Context Handling
- 12.4Conversation Memory Concepts
- 12.5Building a Knowledge Assistant
- 12.6Document-Based Chatbots
- 12.7Customer Support Chatbot Concepts
- 12.8Multilingual Assistant Concepts
- 12.9Chatbot Testing
- 12.10AI Chatbot Project
- AI Agents and Automation10
- Generative AI Application Development and Deployment10
- 14.1Planning a Generative AI Application
- 14.2Working with Generative AI APIs
- 14.3API Authentication and Security
- 14.4Backend Integration Concepts
- 14.5Creating a Simple User Interface
- 14.6Managing Environment Variables
- 14.7Testing Generative AI Applications
- 14.8Deployment Fundamentals
- 14.9Monitoring AI Applications
- 14.10Generative AI Deployment Project
- Responsible Generative AI and Live Projects10
- 15.1Introduction to Responsible Generative AI
- 15.2AI Bias and Fairness
- 15.3Privacy and Data Protection
- 15.4Hallucinations and Reliability
- 15.5Copyright and Intellectual Property Concepts
- 15.6AI Safety and Security Basics
- 15.7Evaluating AI Outputs
- 15.8Building a Responsible AI Workflow
- 15.9End-to-End Generative AI Application
- 15.10Final Generative AI Capstone Project
