Generative AI Workshop

Hands-on Generative AI Workshop

The Generative AI Workshop is designed to help students, faculty members, researchers and professionals understand how modern Generative AI systems work and how they can be applied to real-world problems.

The workshop combines conceptual understanding with hands-on activities covering Large Language Models, prompt engineering, AI applications, Retrieval Augmented Generation, LLM APIs and practical GenAI development.

What is Generative AI?

Generative AI refers to AI systems capable of generating new content such as text, code, images, summaries, explanations and other forms of content based on user instructions and context.

Participants learn the foundations behind modern Generative AI applications and how Large Language Models can be used to build useful AI-powered solutions.

Core Generative AI Concepts

The workshop introduces the key concepts required to understand and work with modern GenAI systems.

• Generative AI fundamentals
• Large Language Models (LLMs)
• Tokens and context
• Foundation models
• Prompt engineering
• AI applications
• Retrieval Augmented Generation (RAG)
• LLM APIs

Large Language Models (LLMs)

Participants are introduced to the role of Large Language Models in Generative AI applications and learn how LLMs process instructions, context and information to generate responses.

Prompt Engineering

Prompt engineering is an important skill for working effectively with Generative AI systems. Participants learn how to design clear instructions and structured prompts for different tasks.

• Prompt structure and instructions
• Zero-shot prompting
• Few-shot prompting
• Role and context prompting
• Structured outputs
• Prompt refinement and testing

Building Generative AI Applications

The workshop moves beyond simple chatbot usage and introduces participants to building practical Generative AI applications using LLMs and APIs.

Participants can work with practical examples such as question answering, summarization, document analysis, content generation, knowledge assistants and other AI-powered workflows.

Retrieval Augmented Generation (RAG)

Participants learn how RAG can connect Generative AI applications with external knowledge sources so that applications can retrieve relevant information before generating responses.

• RAG fundamentals
• Documents and knowledge sources
• Embeddings and semantic search
• Vector databases
• Retrieval and generation workflow
• Building knowledge-grounded AI applications

LLM APIs & AI Integration

Participants learn how APIs can be used to integrate Large Language Models into applications and workflows. Practical demonstrations can include API requests, structured responses and application-level integration.

Generative AI for Education

The workshop can include education-focused examples demonstrating how Generative AI can support teaching, learning and academic activities.

• AI-assisted learning
• Content and lesson preparation
• Question generation
• Summarization and explanation
• Research assistance
• Knowledge assistants

Generative AI for Research

Faculty members and researchers can explore how Generative AI can support information analysis, literature-oriented workflows, document processing, summarization and research productivity.

Hands-on Generative AI Development

A key component of the workshop is practical learning. Participants work through examples and exercises that demonstrate how Generative AI concepts can be translated into working applications.

Learning Outcomes

After completing the workshop, participants should be able to:

• Explain the fundamentals of Generative AI
• Understand the role of Large Language Models
• Design effective prompts
• Work with LLM-based applications
• Understand Retrieval Augmented Generation
• Use LLM APIs in practical applications
• Identify suitable Generative AI use cases
• Build or prototype practical GenAI applications

Generative AI Use Cases

The workshop can be customized around use cases relevant to the participating institution or organization.

• Education and teaching
• Academic research
• Student learning
• Software development
• Document analysis
• Knowledge assistants
• Content generation
• Business productivity

Tools & Technologies

Depending on the workshop format and depth, participants may work with:

• Python
• Google Colab
• Large Language Models
• LLM APIs
• OpenAI APIs
• Prompt engineering tools
• RAG frameworks
• Vector databases
• Python-based AI libraries

Generative AI Workshop Formats

Generative AI programmes can be customized according to the audience, objectives and available duration.

• 1-Day Generative AI Workshop
• 2-Day Hands-on Generative AI Workshop
• Generative AI Faculty Development Programme
• Student Generative AI Workshop
• Generative AI Training for Professionals
• Customized Generative AI Programme for Colleges

Who Should Attend?

• Engineering and technology students
• Computer science students
• Faculty members
• Researchers
• Academic professionals
• Working professionals
• Technology and software teams

Prerequisites

The introductory Generative AI workshop does not require prior experience with Generative AI. Basic computer knowledge is sufficient for introductory sessions.

For hands-on application development sessions, basic Python or programming knowledge can be helpful.

Workshop Infrastructure

For hands-on programmes, the institution should generally provide:

• Individual laptop or computer for participants
• Reliable internet connectivity
• Projector or large display
• Microphone and speaker / PA system
• Suitable classroom or computer laboratory

Generative AI Workshops in Amravati, Nagpur & Vidarbha

NXTGEN Intelligence Academy conducts customized Generative AI workshops and training programmes for colleges, universities and organizations across Amravati, Nagpur and the Vidarbha region.

Programmes can be organized at the institution's campus and customized according to the audience, duration, academic discipline and learning objectives.