Generative AI Fundamentals for Beginners

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

10 weeks, 1 hour a week
Sessions

Self-Paced
Level

Beginner
Subtitles

English

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Overview

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Dive into the world of Generative AI and gain a strong foundation in its concepts, tools, and applications. You will understand how AI models generate text, images, audio, and video, and how these technologies are transforming industries. This course equips you with practical knowledge, from neural networks to large language models, enabling you to harness AI effectively in real-world projects. The course starts with the fundamentals, introducing AI, machine learning basics, and the distinction between traditional and generative AI. Through guided demos, you will experiment with neural networks, image generation, and AI audio/video tools, building hands-on experience while visualizing complex AI processes in action. Next, you will explore advanced AI concepts including Large Language Models, transformers, embeddings, and prompt engineering. Step-by-step exercises and live demos allow you to apply these techniques across text, image, audio, and video AI, reinforcing both conceptual understanding and practical skills. This course is ideal for beginners, aspiring AI professionals, and creative technologists seeking to understand and apply generative AI. No advanced programming skills are required, though basic familiarity with computers and data concepts will help. Difficulty level: Beginner. By the end of the course, you will be able to understand key generative AI concepts, build and interact with AI models, create text, image, audio, and video outputs, and apply prompt engineering techniques to optimize AI-generated results for real-world use cases.

Syllabus

Introduction to Generative AI
- In this module, we will explore the core concepts that form the foundation of Generative AI. We will examine the relationship between Artificial Intelligence, Machine Learning, and generative models while understanding how generative AI differs from traditional AI systems. We will also trace the evolution of Generative AI and its transformative impact across industries.
Neural Networks - The Foundation
- In this module, we will build a strong understanding of neural networks as the foundation of modern AI systems. We will explore how neural networks process information, learn from data, and improve through training techniques such as backpropagation and optimization. We will also reinforce key concepts through interactive demonstrations and practical examples.
Large Language Models (LLMs)
- In this module, we will explore the technologies that power modern Large Language Models and conversational AI systems. We will examine transformers, tokenization, embeddings, and the mechanisms that enable models to understand and generate human-like language. We will also experience practical demonstrations that reveal how LLMs process, interpret, and generate text.
AI Image Generation
- In this module, we will discover how AI systems transform text prompts into realistic and creative visual content. We will explore the technologies behind image generation, including diffusion models, Variational Autoencoders, and Generative Adversarial Networks. We will also participate in demonstrations that showcase image creation, editing, and prompt-driven generation techniques.
AI Audio and Video Generation
- In this module, we will explore how Generative AI creates audio, music, speech, and video content. We will examine the technologies powering text-to-speech systems, AI music generation, video synthesis, and deepfake creation. We will also review practical demonstrations that highlight the growing capabilities of AI-driven multimedia production.
AI Training and Fine-Tuning
- In this module, we will learn how AI models are trained, refined, and optimized for specific applications. We will explore the pre-training process, fine-tuning techniques, and the critical role that data quality plays in model performance. We will also compare different model sizes to understand their strengths, limitations, and practical trade-offs.
Prompt Engineering Mastery
- In this module, we will master the techniques required to communicate effectively with AI systems through prompts. We will explore foundational and advanced prompting strategies that improve output quality, accuracy, and consistency. We will also learn how prompt design differs across text, image, audio, and video generation tasks.
AI Limitations and Challenges
- In this module, we will examine the challenges, risks, and ethical considerations associated with Generative AI technologies. We will explore issues such as hallucinations, bias, fairness, technical constraints, and safety concerns that impact AI adoption. We will also review demonstrations that highlight responsible AI practices and mitigation strategies.
Industry Use Cases for Generative AI Demos
- In this module, we will discover how Generative AI is being applied to solve real-world business challenges and improve operational efficiency. We will explore practical demonstrations involving meeting transcription, email generation, and marketing content creation. We will also assess the value and impact of AI-powered solutions across different industries.
The Future of Generative AI
- In this module, we will explore the future of Generative AI and the opportunities it creates for individuals and organizations. We will examine the path toward Artificial General Intelligence, emerging industry trends, and evolving career prospects in the AI ecosystem. We will conclude the course with key takeaways and actionable next steps for continued learning and growth.