3D Rendered Datasets in Blender for Beginners

Sorry, this course is closed for enrollment.

Promo Video

Course Summary

In this course you will learn the basics of how to create a 3D rendered, synthetic image dataset with Blender.

You'll also learn how to train an simple convolutional neural network to classify rendered and real images.

Included in this course

• Over 3 hours of complete step-by-step and code-along videos

• Completed Blender files

• Blender Python scripts

• Image Classifier Jupyter Notebooks

• A Tea Mug FBX model

• Complete Training, Validation, and Test images, including real photos we took of the tea mug filled with tea

Not covered

• More advanced annotations (e.g. segmentation, bounding boxes)

• Object detection algorithms (e.g. YOLO)

• Python or Deep learning fundamentals

For more on these topics, check out https://www.immersivelimit.com and the Immersive Limit YouTube channel.

Your Instructor

Adam Kelly

Adam Kelly is an early explorer in the world of synthetic data. His 3D development, deep learning, and programming skills come from practical projects, self-directed learning, and over ten years as a professional software developer.

Since 2015, Adam has been teaching these concepts to students, professionals, companies, and hobbyists on YouTube, Udemy, Unity Learn, and immersivelimit.com.

Adam, along with his wife Kayla co-founded and created Immersive Limit, an online-education source for artificial intelligence, 3D simulation, virtual reality, and augmented reality topics.