Machine Learning: Modern Computer Vision & Generative AI (Udemy.com)
Use KerasCV, Python, Tensorflow, PyTorch, & JAX for Image Recognition, Object Detection, and Stable Diffusion
Created by: Lazy Programmer Inc.
Last updated February 2026
What you will learn
- Computer vision with KerasCV
- How to do image classification / image recognition with a pretrained model and fine-tuning / transfer learning
- How to do object detection with a pretrained model and fine-tuning / transfer learning
- How to generate images with Stable Diffusion in KerasCV
How it compares
Against the other 461 rated Udemy courses in Data Science on CourseDuck:
- Rating4.8 out of 5higher than 94% of them
- Reviews967#157 of 462 by number of reviews
- Length6.5 hoursshorter than 57% of them
- Last updatedFebruary 2026more recently than 66% of them
Course Description
Welcome to "Machine Learning: Modern Computer Vision & Generative AI," a cutting-edge course that explores the exciting realms of computer vision and generative artificial intelligence using the KerasCV library in Python. This course is designed for aspiring machine learning practitioners who wish to explore the fusion of image analysis and generative modeling in a streamlined and efficient manner.
Course Highlights:
KerasCV Library: We start by harnessing the power of the KerasCV library, which seamlessly integrates with popular deep learning backends like Tensorflow, PyTorch, and JAX. KerasCV simplifies the process of writing deep learning code, making it accessible and user-friendly.
Image Classification: Gain proficiency in image classification techniques. Learn how to leverage pre-trained models with just one line of code, and discover the art of fine-tuning these models to suit your specific datasets and applications.
Object Detection: Dive into the fascinating world of object detection. Master the art of using pre-trained models for object detection tasks with minimal effort. Moreover, explore the process of fine-tuning these models and learn how to create custom object detection datasets using the LabelImg GUI program.
Generative AI with Stable Diffusion: Unleash the creative potential of generative artificial intelligence with Stable Diffusion, a powerful text-to-image model developed by Stability AI. Explore its capabilities in generating images from textual prompts and understand the advantages of KerasCV's implementation, such as XLA compilation and mixed precision support, which push the boundaries of generation speed and quality.
Course Objectives:
Develop a strong foundation in modern computer vision techniques, including image classification and object detection.
Acquire hands-on experience in using pre-trained models and fine-tuning them for specific tasks.
Learn to create custom object detection datasets to tackle real-world problems effectively.
Unlock the world of generative AI with Stable Diffusion, enabling you to generate images from text with state-of-the-art speed and precision.
Enhance your machine learning skills and add valuable tools to your toolkit for various applications, from computer vision projects to generative art and content generation.
Join us on this captivating journey into the realms of modern computer vision and generative AI. Whether you're a seasoned machine learning practitioner or just starting, this course will equip you with the knowledge and skills to tackle complex image analysis and creative AI projects with confidence. Explore the cutting-edge possibilities that KerasCV and Stable Diffusion offer, and bring your AI aspirations to life.
Prerequisites: Basic knowledge of machine learning and Python programming. Familiarity with deep learning concepts is beneficial but not mandatory.
Instructor Details
- 4.8 Rating
967 Reviews
Lazy Programmer Inc.
The Lazy Programmer is a seasoned online educator with an unwavering passion for sharing knowledge. With over 10 years of experience, he has revolutionized the field of data science and machine learning by captivating audiences worldwide through his comprehensive courses and tutorials.
Equipped with a multidisciplinary background, the Lazy Programmer holds a remarkable duo of master's degrees. His first foray into academia led him to pursue computer engineering, with a specialized focus on machine learning and pattern recognition. Undeterred by boundaries, he then ventured into the realm of statistics, exploring its applications in financial engineering.
Recognized as a trailblazer in his field, the Lazy Programmer quickly embraced the power of deep learning when it was still in its infancy. As one of the pioneers, he fearlessly embarked on instructing one of the first-ever online courses on deep learning, catapulting him to the forefront of the industry.
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Reviews
By Kim Nguyen on 3/22/2026
This course is my chisel and hammer for tackling computer vision projects. The quizzes highlight the key concepts in the models. Thank you very much for your effort and for bringing these courses down to our level!
By Cristi Dumitru on 12/13/2025
Working in a .NET ecosystem, I’ve recently been involved in building an AI image detection & recognition application. I picked this course because it’s short, gives a high-level overview, and helps build the vocabulary around modern computer vision and generative AI. It delivers on both: clear explanations, practical orientation, and a good mental model to understand what an R&D team is doing without going too deep.
By Shane Giles on 11/17/2025
Good explanations and applicable exercises. It was great to be able to follow along and challenge myself along the way. The repetition of following along helped me reinforce the lessons. I can't wait to apply it to some projects I have at work.
By Rahul Mane on 10/2/2025
The course was very useful to upgrade my skills, the content was fabulous and easy to learn. I really liked this course and would definitely recommend it to my friends and colleagues!
By Naveen Balasubramanian on 2/18/2025
Awesome content! What detailed explanations, glad to have got this course. I recommend all students to get on this. Every minute spent here is worth it. Thanks to the tutor to make it simple enough to understand.
By Alice Ting on 12/31/2024
I have really enjoyed and learned a lot in a short period. My goal was to learn the basics of computer vision from scratch and I am glad to know am on the right track with these lecture videos.
By Ramangouda Patil on 8/4/2024
I loved this course and it made me more confident to use Keras for computer vision. Also, the methods used by the instructor Lazy Programmer is really interesting and easy to understand. I will recommend everyone to take this course.
By Isaac Diaz on 6/16/2024
I enjoyed the course. It was really helpful and I learned a lot of new stuff. I am a software developer without any ML experience but I had the idea in mind to build simple computer vision applications and now I understand it a bit better. :)
By Alpa Kothari on 2/19/2024
It's a nicely designed course. Everything the teacher describing is clearly understandable. Working on some real comprehensive projects to apply computer vision.
By David Wollover on 2/12/2024
Much was great, some frequently explained by referring to other courses as well as skipping some code blocks or instrumental variables, which were readily explained in chat gpt by asking if to add copious explanatory comments. Most, but certainly not all AI ML course instructors are more concerned with taking the time to explain finer details of the code. Early parts on ANN and CNN were excellent in presentation although this was simpler material. In the course was more presenting and explaining than teaching how to code the models, both necessary individually and together sufficient for a solid learning experience. Perhaps sacrifice some optional topics for more time indepth to the course essentials - quantity versus quality.
Quality Score
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Overall Score : 96 / 100

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