Zirlen AI

Generative AI – From Foundations to Real-World Applications

Course Overview

This AI course provides a strong foundation in artificial intelligence concepts, tools, and real-world applications.
Learners gain practical exposure to machine learning, data-driven decision-making, and modern AI use cases. Designed by industry experts, the course balances theory with hands-on learning.
It equips participants with the skills needed to apply AI confidently in business and technology roles. A comprehensive 30-hour course on Generative AI designed for learners ranging from beginners to intermediate level, with practical case studies, hands-on exercises, and real-world applications.

Course Duration & Timing

Duration: 30 Hours
Format: Lectures + Hands-on Labs + Case Studies + Mini Projects

Course Modules

This course covers:

  • Fundamentals of Generative AI
  • Large Language Models (LLMs)
  • Prompt Engineering
  • AI Tools (ChatGPT, APIs, etc.)
  • Real-world use cases across industries
  • Ethical and business implications

Module 1: Introduction to Generative AI (2 Hours)

Topics:

  • What is AI vs ML vs Generative AI
  • History and evolution (GANs → Transformers)
  • Applications overview

Case Study:

  • How AI writes content (blog/article generation workflow)

Hands-on:

  • Using a basic AI tool to generate text

Module 2: Foundations of LLMs (4 Hours)

Topics:

  • Transformers architecture (conceptual)
  • Tokens, embeddings, attention mechanism
  • Training vs inference

Case Study:

  • How GPT models generate human-like responses

Hands-on:

  • Tokenization demo
  • Prompt-response experiments

Module 3: Prompt Engineering (4 Hours)

Topics:

  • Zero-shot, Few-shot, Chain-of-thought
  • Prompt structure & optimization
  • Controlling output (tone, style, format)

Case Study:

  • Improving chatbot responses using better prompts

Hands-on:

  • Rewrite prompts for:
    • Marketing copy
    • Code generation
    • Customer support replies

Module 4: Generative AI Tools & APIs (4 Hours)

Topics:

  • Using AI platforms (Chat interfaces, APIs)
  • API basics (requests, responses)
  • Integrating AI into apps

Case Study:

  • Building a simple AI-powered content generator

Hands-on:

  • Call an API to generate:
    • Text
    • Summaries
    • Emails

Module 5: Text Generation Use Cases (4 Hours)

Topics:

  • Content creation (blogs, ads)
  • Chatbots & assistants
  • Code generation

Case Studies:

  1. AI for marketing campaigns
  2. AI coding assistants for developers

Mini Project:

  • Build a chatbot for a business scenario

Module 6: Image & Multimedia Generation (3 Hours)

Topics:

  • Diffusion models (conceptual)
  • Text-to-image generation
  • Video & audio generation basics

Case Study:

  • AI-generated product designs for e-commerce

Hands-on:

  • Generate images from prompts
  • Modify images with AI tools

Module 7: Industry Applications (4 Hours)

Topics + Case Studies:

  1. Healthcare
  • AI for medical documentation
  • Case: Automating patient reports
  1. Finance
  • Fraud detection assistance
  • Case: AI-generated financial summaries
  1. Education
  • Personalized learning
  • Case: AI tutor systems
  1. Customer Support
  • AI chatbots replacing tier-1 support

Module 8: Ethics, Risks & Limitations (2 Hours)

Topics:

  • Bias & hallucinations
  • Data privacy concerns
  • Responsible AI usage

Case Study:

  • When AI gives wrong or harmful outputs

Discussion:

  • AI regulation and future risks

Module 9: Advanced Concepts (2 Hours)

Topics:

  • Fine-tuning vs prompt engineering
  • Retrieval-Augmented Generation (RAG)
  • AI agents & automation workflows

Case Study:

  • AI-powered knowledge base assistant

Module 10: Capstone Project (3 Hours)

Choose One Project:

  1. AI-powered chatbot for a business
  2. Content generation platform
  3. AI assistant for students
  4. Resume & cover letter generator

Deliverables:

  • Working prototype
  • Presentation
  • Use-case explanation

Assessment & Evaluation

  • Quizzes (after each module)
  • Hands-on assignments
  • Final capstone project (40%)

Tools & Technologies Covered

  • Chat-based AI tools
  • API integrations
  • Prompt engineering frameworks
  • No-code / low-code AI tools

Learning Outcomes

By the end of the course, learners will:

  • Understand how Generative AI works
  • Write effective prompts
  • Build simple AI-powered applications
  • Apply AI to real-world problems
  • Evaluate ethical implications

Bonus (Optional Add-ons)

  • Resume-building with AI
  • Interview preparation using AI
  • Building your AI portfolio
  • Turn this into a presentation (PPT)
  • Create detailed lesson plans + slides for each module
  • Add real datasets and coding exercises
  • Customize it for college / corporate training