Teach a Machine to See the World. Then Show It Yours.
Join a 4-week immersive experience in real-world computer vision and AI — led by Dr. Nir Regev, Ph.D. EE, 27 year industry veteran and a university professor.
Limited live cohort seats. Self-paced track available.
👨🏫 What You'll Learn
Across 4 hands-on sessions, students will explore how machines “see” images, detect objects, and learn from personalized data — all using real industry tools.
🧠 Session 1: Seeing with AI
Train a convolutional neural network (CNN) to classify images from CIFAR-10 — like cars, planes, and dogs.
🎯 Session 2: Teach It Your World
Use transfer learning to fine-tune a pretrained model (like MobileNet) on images you upload — pets, foods, shoes, anything.
📦 Session 3: Object Detection
Run object detection on your own photos using YOLOv5 — drawing boxes around people, animals, vehicles, and more.
🎥 Session 4: Real-Time Vision
Apply your model to a video clip and create an annotated video output with bounding boxes and labels.
✅ All projects are built in Google Colab (no install needed).
🎓 Who This Is For
High school students (Grades 9–12) or college freshmen
Must know Python basics (lists, loops, functions)
Passionate about AI, machine learning, robotics, or engineering
Ready to build real projects — not just watch videos
Lower grades gifted students can apply as well
🚀 Two Ways to Join
Elite Live Cohort (15 students only) Tuition: $2,500
Engaging Instruction: Participate in small, interactive sessions led by Dr. Regev.
Live Zoom Sessions: Enjoy 8 hours of live instruction, all recorded for your convenience and future reference.
Personalized Project Feedback: Receive tailored insights and improvements on your projects.
1-on-1 Review: Benefit from dedicated time for individual feedback and guidance.
Private Group Chat: Connect with Dr. Regev and fellow participants for continuous support and discussion.
Boost Your Credentials: Earn a certificate of completion and an optional letter of recommendation to enhance your professional profile.
Self Paced Track (waitlist)
Tuition: $497
Access All the Essentials: Dive into the same curriculum as traditional learners, complete with recordings to revisit complex concepts at your convenience.
Hands-On Learning: Engage with a structured 4-week curriculum that includes exciting challenge projects to solidify your understanding.
Connect with Peers: Join our private asynchronous student community to collaborate, share ideas, and grow together.
Boost Your Credentials: Upon completion, earn a recognized certificate.
What My Students Are Saying
Course: AI in Radar Signal Processing
Note: This is a review from roughly halfway through the course.
In the course "AI in Radar Signal Processing," Dr. Regev is able to take a complicated cutting edge topic, deliver the background concepts and mathematics quickly yet thoroughly, and then delve into real applications with example code. I work professionally in the automotive radar space and I know that there are many difficult problems still to solve because it's still a new burgeoning technology. The course helped refresh some of the basics, and gave me real applicable mathematical tools to help solve some of these difficult problems using artificial neural networks and other machine learning techniques. I would highly recommend this course for those looking to add some versatile tools to their toolbox if they are working with radar or other similar technologies.
Regards,
—Lucas Wells
I have been working on radar signal processing and target tracking since the second semester of my undergraduate studies, and I am fortunate to study under one of the world's leading experts in these fields. This course provided me with a quick and effective restart in understanding radar systems, particularly in the area of mmWave radar technology.
The mathematical depth and the clear code illustrations are simply perfect, making it an essential resource for anyone looking to advance their skills. If you are an aspiring radar engineer or work in any radar-related field, this course is exactly what you need.
UNQUESTIONINGLY ATTEND THIS COURSE.
—Dayananda B N, Graduate Student, National Institute of Technology Karnataka
Dr. Regev’s AI in Radar Signal Processing course was transformative. The depth of knowledge, paired with real-world applications, helped me grasp complex concepts with ease and helped me with the current projects I’m engaged in. I highly recommend this to anyone serious about advancing their radar signal processing and AI skills.”
—Prem Kumar, Senior Technical Lead in Mercedes Benz, India
The "AI in Radar Signal Processing" course has been a valuable learning experience so far. Dr. Regev breaks down complex topics into manageable concepts, combining the right level of theory with practical examples. The use of example code has been particularly helpful in understanding how AI techniques like neural networks can be applied to real-world radar challenges. This course has already given me new ideas to explore in my work and helped reinforce key radar fundamentals. I’d recommend it to anyone working in radar or looking to expand their skills in this area.
—Pooja Patil, Technical Project Manager for 4D High Resolution Imaging Radar, Greenwave
Dr. Regev's excellent course is well-structured, offering in-depth detail for anyone working in the field. The content is comprehensive, offering valuable theoretical and practical knowledge in radar signal processing. I am very excited to apply the skills I've gained from this course to more advanced radar signal processing projects. I highly recommend this course to both professionals and students interested in radar signal processing and AI.
—Michael Nelson, EE Student at Cal Poly Pomona
Taking the AI in Radar course has been an incredible experience. The content is cutting-edge, focusing on the practical applications of AI to enhance radar systems. Dr. Regev breaks down complex topics into easy-to-understand modules, with very helpful example code . The modules thus far have significantly deepened my understanding of how AI can transform radar technology. I highly recommend this course for anyone looking to advance their knowledge in this evolving field or even looking to recollect radar processing.
—Jakob Herrera, EE Student at Cal Poly Pomona
