Cambridge

Compass House, Cambridge, united kingdom, CB24 9AD

Vision Park is within easy reach of Cambridge city centre and has the advantage of excellent links with the M11 and A14. Trains from London Kings Cross arrive every 30 minutes, with a 15 minute journey by taxi to the Park. Histon Railway Station is on the boundary of Vision Park, which provides high quality, frequent local transport from St Ives to Cambridge. Guided Bus Vision Park lies alongside the Cambridgeshire Guided Bus which offers fast and frequent buses from Histon to Huntingdon (50 minutes), St Ives (15) and Cambridge city centre (15). Onboard, there is air conditioning, free WiFi and power for your laptop and mobile devices. Please see www.thebusway.info for further information.

Explore Our Courses

Ethics and Legal Aspects of Autonomous Driving

 14 Hours
This instructor-led, live training in Cambridge (online or onsite) is aimed at beginner-level professionals who wish to explore the ethical dilemmas and legal frameworks surrounding autonomous vehicles. By the end of this training, participants will be able to:
  • Understand the ethical implications of AI-driven decision-making in autonomous vehicles.
  • Analyze global legal frameworks and policies regulating self-driving cars.
  • Examine liability and accountability in the event of autonomous vehicle accidents.
  • Evaluate the balance between innovation and public safety in autonomous driving laws.
  • Discuss real-world case studies involving ethical dilemmas and legal disputes.
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Introduction to Autonomous Vehicles: Concepts and Applications

 14 Hours
This instructor-led, live training in Cambridge (online or onsite) is aimed at beginner-level professionals and enthusiasts who wish to understand the fundamental concepts, technologies, and applications of autonomous vehicles. By the end of this training, participants will be able to:
  • Understand the key components and working principles of autonomous vehicles.
  • Explore the role of AI, sensors, and real-time data processing in self-driving systems.
  • Analyze different levels of vehicle autonomy and their real-world applications.
  • Examine the ethical, legal, and regulatory aspects of autonomous mobility.
  • Gain hands-on exposure to autonomous vehicle simulations.
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Vehicle-to-Everything (V2X) Communication for Autonomous Cars

 21 Hours
This instructor-led, live training in Cambridge (online or onsite) is aimed at intermediate-level network engineers and automotive IoT developers who wish to understand and implement V2X communication technologies for autonomous vehicles. By the end of this training, participants will be able to:
  • Understand the fundamental concepts of V2X communication.
  • Analyze V2V, V2I, V2P, and V2N communication models.
  • Implement V2X protocols such as DSRC and C-V2X.
  • Develop simulations for connected vehicle environments.
  • Address cybersecurity and privacy challenges in V2X networks.
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Sensor Technologies in Autonomous Vehicles

 21 Hours
This instructor-led, live training in Cambridge (online or onsite) is aimed at intermediate-level engineers, automotive professionals, and IoT specialists who wish to understand the role of sensors in self-driving cars, covering LiDAR, radar, cameras, and sensor fusion techniques. By the end of this training, participants will be able to:
  • Understand the different types of sensors used in autonomous vehicles.
  • Analyze sensor data for real-time vehicle perception and decision-making.
  • Implement sensor fusion techniques to improve vehicle accuracy and safety.
  • Optimize sensor placement and calibration for enhanced autonomous driving performance.
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Autonomous Vehicle Safety and Risk Assessment

 21 Hours
This instructor-led, live training in Cambridge (online or onsite) is aimed at advanced-level safety engineers and automotive safety professionals who wish to develop comprehensive safety strategies for autonomous vehicles, including hazard analysis, functional safety assessments, and compliance with international standards. By the end of this training, participants will be able to:
  • Identify and assess safety risks associated with autonomous driving systems.
  • Conduct hazard analysis and risk assessment using industry standards.
  • Implement safety validation and verification methods for AV systems.
  • Apply functional safety standards, such as ISO 26262 and SOTIF.
  • Develop risk mitigation strategies for AV safety challenges.
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Multi-Sensor Data Fusion for Autonomous Navigation

 21 Hours
This instructor-led, live training in Cambridge (online or onsite) is aimed at advanced-level sensor fusion specialists and AI engineers who wish to develop multi-sensor fusion algorithms and optimize real-time navigation in autonomous systems. By the end of this training, participants will be able to:
  • Understand the fundamentals and challenges of multi-sensor data fusion.
  • Implement sensor fusion algorithms for real-time autonomous navigation.
  • Integrate data from LiDAR, cameras, and RADAR for perception enhancement.
  • Analyze and evaluate fusion system performance under various conditions.
  • Develop practical solutions for sensor noise reduction and data alignment.
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Computer Vision for Autonomous Driving

 21 Hours
This instructor-led, live training in Cambridge (online or onsite) is aimed at intermediate-level AI developers and computer vision engineers who wish to build robust vision systems for autonomous driving applications.By the end of this training, participants will be able to:
  • Understand the fundamental concepts of computer vision in autonomous vehicles.
  • Implement algorithms for object detection, lane detection, and semantic segmentation.
  • Integrate vision systems with other autonomous vehicle subsystems.
  • Apply deep learning techniques for advanced perception tasks.
  • Evaluate the performance of computer vision models in real-world scenarios.
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Advanced Path Planning Algorithms for Autonomous Vehicles

 21 Hours
This instructor-led, live training in Cambridge (online or onsite) is aimed at advanced-level robotics engineers and AI researchers who wish to implement sophisticated path planning algorithms to enhance autonomous vehicle performance.By the end of this training, participants will be able to:
  • Understand the theoretical foundations of advanced path planning algorithms.
  • Implement algorithms such as RRT*, A*, and D* for real-time navigation.
  • Optimize path planning for obstacle avoidance and dynamic environments.
  • Integrate path planning algorithms with sensor data for enhanced accuracy.
  • Evaluate the performance of various algorithms in practical scenarios.
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AI and Deep Learning for Autonomous Driving

 21 Hours
This instructor-led, live training in Cambridge (online or onsite) is aimed at advanced-level data scientists, AI specialists, and automotive AI developers who wish to build, train, and optimize AI models for autonomous driving applications. By the end of this training, participants will be able to:
  • Understand the fundamentals of AI and deep learning in the context of autonomous vehicles.
  • Implement computer vision techniques for real-time object detection and lane following.
  • Utilize reinforcement learning for decision-making in self-driving systems.
  • Integrate sensor fusion techniques for better perception and navigation.
  • Build deep learning models to predict and analyze driving scenarios.
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Last Updated:

Provisional Upcoming Courses (Contact Us For More Information)

Ethics and Legal Aspects of Autonomous Driving

2025-05-29 09:30
14 hours
Cambridge

Multi-Sensor Data Fusion for Autonomous Navigation

2025-06-16 09:30
21 hours
Cambridge

Introduction to Autonomous Vehicles: Concepts and Applications

2025-06-26 09:30
14 hours
Cambridge

Multi-Sensor Data Fusion for Autonomous Navigation

2025-07-14 09:30
21 hours
Cambridge

Vehicle-to-Everything (V2X) Communication for Autonomous Cars

2025-07-28 09:30
21 hours
Cambridge

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