Diana Certified AI Autonomous Vehicle Engineer

Categories: Diana AI
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About Course

Schedule: MON – FRI 4 hours (Time: 9 AM to 1 PM & 2 PM to 6 PM ) |SAT/SUN 8 hours (9 AM to 6 PM)

What Will You Learn?

  • Introduction to Autonomous Vehicles: Understand the fundamentals, history, and evolution of autonomous vehicle technology.
  • Sensor Technologies: Learn about the various sensors used in autonomous vehicles, including LIDAR, RADAR, cameras, and ultrasonic sensors.
  • Perception and Environment Modeling: Study techniques for object detection, classification, and tracking to create an accurate model of the vehicle's surroundings.
  • Localization and Mapping: Gain insights into algorithms for determining a vehicle's precise location and building real-time maps (SLAM - Simultaneous Localization and Mapping).
  • Path Planning and Decision Making: Explore methods for route planning, obstacle avoidance, and making driving decisions in complex environments.
  • Control Systems: Understand the principles of vehicle dynamics and the design of control systems for steering, acceleration, and braking.
  • Machine Learning and AI in Autonomous Vehicles: Apply machine learning algorithms and neural networks for perception, decision-making, and predictive analytics.
  • Simulation and Testing: Learn to use simulation tools and frameworks for developing, testing, and validating autonomous driving systems.
  • Safety and Redundancy: Study the safety protocols, redundancy measures, and fail-safe mechanisms crucial for autonomous vehicle operations.
  • Regulatory and Ethical Considerations: Understand the legal, ethical, and regulatory aspects of deploying autonomous vehicles in the real world.
  • Hardware and Software Integration: Gain practical skills in integrating hardware components and developing software for autonomous vehicle systems.
  • Hands-On Projects and Capstone: Engage in practical projects and a capstone project to apply theoretical knowledge to real-world autonomous driving scenarios.

Course Modules

Introduction to Autonomous Driving

  • Introduction to Autonomous Driving

Perception in Autonomous Driving

Prediction and Routing

Reinforcement Learning-based Planning and Control

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