Mastering ChatGPT and Generative AI Tools is a hands-on, practical training program designed to help learners understand, use, and customize modern generative AI technologies for real-world applications. This course goes beyond basic AI usage and provides a structured understanding of how generative models work, how ChatGPT is built and trained, and how organizations deploy large language models (LLMs) across platforms.

The course begins with a strong foundation in Artificial Intelligence, Machine Learning, and Generative AI—covering key concepts such as supervised and unsupervised learning, deep learning basics, and the differences between traditional AI and generative models. Learners then dive deep into ChatGPT, exploring how transformer-based models work, how they are trained, and the ethical and safety considerations involved in deploying AI responsibly.

As the course progresses, participants gain hands-on experience using ChatGPT for text generation, prompt design, and practical use cases such as content creation, summarization, and automation. The curriculum expands beyond ChatGPT to cover generative AI models and platforms from Azure, AWS, and NVIDIA, giving learners a broad, cloud-agnostic perspective on the generative AI ecosystem.

Advanced modules focus on customization and fine-tuning—teaching learners how to design effective prompts, fine-tune models for specific use cases, and understand the architecture behind LLM-powered applications. Learners are also introduced to advanced techniques such as Retrieval-Augmented Generation (RAG), LLM agents, and modern copilots, enabling them to build intelligent, context-aware AI solutions.

By the end of the course, learners will have a clear understanding of how generative AI works, how to apply ChatGPT and related tools effectively, and how to design advanced AI-driven solutions—making this course ideal for professionals, developers, and organizations looking to adopt generative AI strategically and responsibly.

This course is designed for beginners to intermediate learners who want to understand and use ChatGPT and modern Generative AI tools effectively. No advanced technical background is required. However, the following will help learners get the most out of the course:

• Basic computer and internet usage skills.

• Familiarity with using web applications and productivity tools.

• Interest in Artificial Intelligence, automation, or Generative AItechnologies.

• Willingness to experiment with prompts and AI tools.

• Optional (but helpful):

• Basic understanding of cloud platforms such as Azure or AWS

• Introductory knowledge of programming concepts (not mandatory)

• Curiosity about how AI models are trained and deployed

This course is suitable for professionals, students, creators, analysts, developers, and business users looking to build practical skills in Generative AI.

By the end of this course, you will be able to:

• Understand core concepts of Artificial Intelligence, Machine Learning, and Generative AI

• Explain how ChatGPT and large language models work, including transformers and attention mechanisms

• Use ChatGPT effectively for text generation, summarization, and automation

• Design clear and effective prompts for different business and creative use cases

• Compare Generative AI models across Azure, AWS, and NVIDIA platforms

• Apply prompt customization and fine-tuning concepts to tailor AI outputs

• Understand the architecture of LLM-powered applications

• Implement Retrieval-Augmented Generation (RAG) for context-awarAI responses

• Explore advanced RAG techniques and LLM agents

• Use copilots such as Windows Copilot to enhance productivity

• Identify ethical considerations, limitations, and responsible use ofGenerative AI

• Apply Generative AI tools to real-world workflows, projects, and business scenarios

Learning ChatGPT and Generative AI tools prepares learners for a wide range of emerging roles that focus on AI-assisted productivity, automation, and intelligent application usage. After completing this course, learners will be better prepared for positions such as:

• Generative AI Specialist

• AI Productivity Specialist

• Prompt Engineer

• Business Analyst (AI-Enabled Workflows)

• Content Strategist / AI Content Specialist

• Automation Analyst / Workflow Automation Specialist

• Digital Operations Analyst

• AI Support Analyst / AI Tools Specialist

• Product or Operations Associate (AI-Augmented Tools)

• Junior AI Engineer / LLM Application Assistant

Module 1: Introduction to AI and Generative AI

• Overview of Artificial Intelligence and Machine Learning

• Definition and history of AI

• Supervised vs. unsupervised learning

• Deep learning fundamentals

Module 2: Introduction to Generative AI

• What is Generative AI?

• Differences between Generative AI and traditional AI

• Applications and use cases

Module 3: Understanding ChatGPT

• How ChatGPT works

• Transformer architecture and attention mechanism

• Model training process: data collection and fine-tuning

• Safety, limitations, and ethical considerations

• Using ChatGPT for text generation

• Setting up ChatGPT and API access

• Basic prompt structure and input formatting

• Practical use cases

Module 4: Generative AI Models and Platforms

• Overview of enterprise and cloud-based Generative AI models

• Azure AI models and services

• AWS Generative AI models and services

• NVIDIA AI models and GPU-based acceleration

• Comparison of Generative AI platforms

Module 5: Customization, Transformation, and Fine-Tuning

• Prompt engineering and prompt customization techniques

• Fine-tuning large language models for specific use cases

• Understanding LLM application architecture

• Designing scalable LLM-powered applications

Module 6: Advanced Generative AI Use Cases

• Retrieval-Augmented Generation (RAG)

• Advanced RAG architectures

• LLM agents and autonomous workflows

• Windows Copilot and modern copilots

• Real-world enterprise and productivity use cases