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Introduction to Generative AI Course
edu Kanea > Courses > AI for Everyone > Introduction to Generative AI Course

AI for Everyone Business & Management

Last Update: Aug 08, 2025

Introduction to Generative AI Course

  • Free
  • 16 Lesson

About Course

Course Summary

The “Introduction to Generative AI” course is designed to equip participants with a solid understanding of generative AI, its core principles, and practical applications. Targeted at AI enthusiasts, data scientists, business professionals, and other stakeholders, the course covers foundational concepts of generative models, including large language models (LLMs), prompt engineering, and chatbots. Through a blend of theoretical lessons, hands-on exercises, and real-world projects, participants will gain the skills to leverage generative AI in diverse domains such as content creation, problem-solving, and innovation. The course also explores the infrastructure and technologies behind generative AI, alongside its capabilities and limitations, preparing participants to integrate these technologies into their professional workflows.

Course Objectives

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

  • Explain the basic concepts of generative AI.

  • Describe the capabilities and limitations of generative AI for solving business problems.

  • Describe the infrastructure and technologies for building generative AI applications.

  • Experience real-world projects illustrating applications of generative AI.

Target Audience

  • Business leaders

  • Operational managers

  • Technical professionals

  • Innovation and strategy teams

  • Entrepreneurs and startups

  • Educators and researchers

  • Policy makers and regulators

Course Structure

The course is divided into four modules, each focusing on a critical aspect of generative AI. Each module includes detailed lessons, practical exercises, and a quiz to reinforce learning.

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What Will You Learn?

  • You’ll learn the fundamentals of generative AI, including large language models, prompt engineering, and infrastructure. Gain hands-on experience with tools like Hugging Face, build a chatbot, and explore real-world applications while understanding ethical considerations and future trends in generative AI.

Course Content

Foundations of Generative AI
Module 1 serves as the cornerstone of the "Introduction to Generative AI" course, laying the groundwork for understanding generative AI’s principles, evolution, and significance. This module is designed to equip participants with a clear conceptual framework, distinguishing generative AI from other AI paradigms and highlighting its transformative potential across industries. Participants will explore the historical context, key algorithms, and ethical considerations, preparing them to dive deeper into technical and practical aspects in later modules. Through a combination of theoretical lessons and interactive exercises, learners will build a solid foundation to understand how generative AI works and why it matters. Learning Objectives: Define generative AI and differentiate it from discriminative models. Trace the historical development of generative AI. Understand the core algorithms powering generative AI. Recognize real-world applications and ethical challenges.

  • Lesson 1: What is Generative AI?
  • Lesson 2: History and Evolution of Generative AI
  • Lesson 3: Key Algorithms and Models
  • Lesson 4: Applications and Ethical Considerations
  • Foundations of Generative AI.

Large Language Models (LLMs) and Prompt Engineering
Overview Module 2 delves into the world of Large Language Models (LLMs), a cornerstone of modern generative AI, and the art of prompt engineering to maximize their effectiveness. Participants will explore the architecture, training processes, and practical applications of LLMs, such as GPT, BERT, and LLaMA. The module emphasizes prompt engineering as a critical skill for optimizing LLM outputs, covering basic and advanced techniques. Through hands-on exercises, learners will gain practical experience in crafting prompts and designing LLM-based applications like chatbots. The module also addresses the limitations of LLMs, preparing participants to use these models responsibly and effectively in real-world scenarios. Learning Objectives: Understand the architecture and training of LLMs. Master the basics of prompt engineering to control LLM outputs. Apply advanced prompt engineering techniques to solve complex problems. Explore practical applications of LLMs and their limitations.

Infrastructure and Technologies for Generative AI
Infrastructure and Technologies for Generative AI Overview: Module 3 focuses on the technical backbone required to build, train, and deploy generative AI applications. Participants will explore the hardware, software frameworks, and APIs essential for creating scalable and efficient generative AI systems. Through hands-on exercises, learners will gain practical experience with popular tools like Hugging Face and cloud platforms, as well as learn to integrate APIs for real-world applications. The module also covers critical considerations like scalability, cost, security, and privacy, culminating in a case study that guides participants through the process of building a generative AI application. This module bridges theoretical knowledge with practical implementation, preparing participants to deploy generative AI solutions effectively. Learning Objectives: Understand the role of hardware (GPUs, TPUs) in training generative AI models. Explore software frameworks and deployment platforms for generative AI. Learn to integrate generative AI APIs into custom applications. Design and outline a generative AI application with attention to scalability and security.

Real-World Applications and Projects
Overview Module 4 brings generative AI to life by focusing on its practical applications through real-world scenarios and hands-on projects. Participants will explore how generative AI is transforming industries like content creation, business operations, and customer service, while gaining practical experience by developing their own projects. The module covers case studies, tools, and emerging trends, culminating in a hands-on project where learners build a functional chatbot. By engaging with real-world use cases and forward-looking opportunities, participants will solidify their understanding of generative AI’s potential and limitations, preparing them to apply these skills in their professional domains. Learning Objectives: Apply generative AI to content creation tasks like writing and graphic design. Design generative AI solutions for business challenges, such as automation and analytics. Build and deploy a functional chatbot using generative AI tools and APIs. Explore future trends and propose innovative generative AI projects.

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Free access this course
  • All Levels
  • 0 Total Enrolled
  • 20 hours45 minutes Duration
  • Aug 8, 2025 Last Updated

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