Pricing For Summer Program 2024 Goes Up April 20
Overview
This course will do an intense dive into the latest computer vision and AI techniques as related to robotics, and then use their newfound knowledge to program the trajectory of a heavy duty mobile robot based upon what it sees in real-time. This course is highly recommended for students interested in exploring a career in robotics.
Description
- OpenCV computer vision library- ROS Robot Operating System
- Train an AI model using Transformers, (the T in GPT)
- Learn the differences between traditional AI techniques like CNNs and RNNs, vs the more recent breakthrough Transformer technology
- Deep dive and usage of Fiduciary positioning markers for mobile robotics
- Deep Learning frameworks applied to computer vision
- 3D image acquisition and representation
- 3D image understanding and algorithms
- Python
- C++
- Linux
- GPUs
PrerequisitesBasic knowledge of python, algebra, computer science is necessary to participate in this session. If you are registering as part of Genesis Track, then these topics will be covered sufficiently before this session begins.
Social Distancing Policy
We have worked hard to create a safe setup that minimizes risk:
Masks are now optional
Reasonable social distancing will be encouraged and unnecessary huddling will be discouraged
We recommend each student bring their own water bottle.
What To Bring
- Each student must bring his/her own Mac, Windows, or Linux laptop with sufficient free disk space and administrative rights to install the virtual machines and associated software.
- A USB-C to USB adapter if your laptop contains only the new USB-C ports
Advanced Robotics and AI Lab - 3D Computer Vision, GPT and Deep Learning
RETURN & REFUND POLICY
100% will be refunded if cancellation request is received by 11:59PM Pacific time on May 10, 2024 - no questions asked.
In the unlikely event of a new COVID-19 lockdown for Mountain View being announced within 30 days before the session starts, you will be able to change from in-person to zoom attendance, or if that is not preferable, 80% will be refunded.