Overview

Updated in May 2025. This course now 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. Embark on a transformative journey through modern machine learning, computer vision, and generative AI with this comprehensive course. Explore industry-leading techniques like image classification, object detection, and cutting-edge generative models powered by KerasCV and Stable Diffusion. Gain hands-on experience with tools and frameworks that make these advanced topics approachable and actionable. The course begins with the fundamentals of pre-trained models and transfer learning, empowering you to implement and fine-tune image classifiers in Python. From there, dive into object detection, mastering dataset formats, augmentation techniques, and loss functions while leveraging KerasCV for efficient fine-tuning. Next, delve into generative AI with Stable Diffusion, uncovering its architecture, mechanics, and codebase. Learn to create stunning visuals and understand how these models condition on prompts, offering insights into the frontier of AI-driven creativity. Additional modules provide guidance on Python coding, environment setup, and learning strategies, ensuring that learners of all levels can succeed. This course is designed for learners interested in deep learning, computer vision, and AI creativity. A basic understanding of Python and machine learning is recommended. Whether you're a developer, researcher, or enthusiast, this intermediate-level course will elevate your skills and open new horizons in AI innovation.

Syllabus

Welcome

In this module, we will introduce you to the structure of the course and provide you with the tools necessary to succeed. We will guide you through understanding the course layout and show you how to access all course materials and code through GitHub and Bitly links.

Image Classification, Fine-Tuning and Transfer Learning

In this module, we will explore key concepts in image classification, focusing on pre-trained models and transfer learning. You'll learn how to implement and fine-tune these models using Python, while reinforcing your skills with practical exercises.

Object Detection

In this module, we will dive deep into object detection, covering essential concepts and hands-on practices. You’ll learn how to use pre-trained models, enhance them with transfer learning, and handle datasets in popular formats like COCO and Pascal VOC.

Generative AI with Stable Diffusion

In this module, we will introduce you to Stable Diffusion, focusing on its capabilities and real-world applications in generative AI. We’ll walk you through practical exercises on generating images, as well as optional deep dives into the inner workings of diffusion models and their architecture.

Setting Up Your Environment (Appendix/FAQ by Student Request)

In this module, we will guide you through setting up your Python environment using Anaconda and installing the critical libraries necessary for machine learning. This will ensure you have the proper tools and setup to begin your journey in the course.

Extra Help With Python Coding for Beginners (Appendix/FAQ by Student Request)

In this module, we will support beginners in learning Python by offering tips, explaining coding concepts, and guiding you through practical applications of TDD. You will also gain clarity on the use of Jupyter Notebooks in machine learning projects.

Effective Learning Strategies for Machine Learning (Appendix/FAQ by Student Request)

In this module, we will provide effective strategies for progressing through machine learning courses. You'll learn the best sequence to build your skills, helping you understand how different topics, such as text and image data handling, connect throughout your learning journey.

Appendix / FAQ Finale

In this module, we will conclude the course by showing you where to find valuable free deep learning resources and discount coupons, ensuring your learning continues with accessible tools and materials at a reduced cost.