- Duration: 22 weeks (6 months)
- Learning Split: 40% theory / 60% practical
Build practical knowledge of the AI and machine learning techniques used to enable autonomous vehicles to perceive their environment, make decisions, and navigate safely. This module covers path planning, object detection, reinforcement learning fundamentals, and simulation environments used in autonomous vehicle development. Participants will apply these concepts to realistic robotics and autonomous-driving challenges.
What You’ll Learn:
- Fundamentals of autonomous vehicle path planning
- Object detection and environmental perception
- AI/ML approaches for autonomous decision-making
- Introduction to reinforcement learning and reward-based learning
- Simulation environments for autonomous vehicle development
- Applying algorithms to real-world robotics problems
- Developing and testing autonomous driving logic in simulation
- Optimizing solutions through competitive coding challenges
Value — What You Gain
Gain practical AI/ML coding experience by applying intelligent algorithms to real autonomous-system challenges rather than working only with theoretical examples or toy datasets. By the end of this module, you’ll understand how AI can be used for perception, planning, and decision-making within an autonomous vehicle.
This foundation prepares you for advanced areas such as autonomous driving, robotics AI, computer vision, reinforcement learning, path planning, simulation, and intelligent vehicle systems.
REGISTRATION PROCESS
Interest Submission
Prospective students (or their institution) submit the registration form either as a physical printout, Google Form, or PDF fillable form.
Eligibility Review
XSPEED Academy reviews each application against the basic program prerequisites.
- Currently enrolled in an engineering / technical diploma program or equivalent
- Genuine interest in motorsport, automotive, or autonomous systems
- Prior experience is not required
- Institutional approval, if registering through a college/university partnership
Seat Confirmation
Once eligibility is confirmed, the applicant receives:
- Confirmation of seat in the upcoming cohort
- Payment / fee instructions or institutional sign-off requirement
- Program start date and orientation details
Fee / Sign-off
Applicant completes payment if self-funded, or the institution confirms sponsorship / enrollment on the student’s behalf.
Team Allocation
Enrolled students are grouped into build teams ahead of Module 1, based on stated module interest, skill background, and team-size requirements.
Orientation Session
A mandatory kickoff session covering:
- Program structure and 22-week schedule
- Lab safety protocols and PPE requirements
- Equipment and lab kit briefing
- Introduction to team members and mentors
Program Commencement
Begins on the scheduled cohort start date.