Autonomous Vehicles (AVs) Training in Bangkok

This live, instructor-led session in Bangkok, offered online or onsite, is targeted at entry-level professionals seeking to examine the ethical tensions and legal landscapes associated with autonomous vehicles.

Once finished, attendees will have the capability to:

• Appreciate the ethical consequences of AI-controlled decisions in autonomous driving.
• Review worldwide legal structures and policies regulating self-driving cars.
• Explore liability and accountability issues following autonomous vehicle accidents.
• Assess the trade-off between technological progress and public safety in driving laws.
• Examine practical examples involving ethical conflicts and legal disputes.

This live, instructor-led program, delivered online or on-site, in Bangkok, is tailored for novice professionals and hobbyists aiming to comprehend the foundational principles, technical architectures, and use cases of autonomous vehicles.

Upon completing this training, attendees will be able to:

• Comprehend the critical parts and functional logic of autonomous vehicles.
• Examine the contribution of AI, sensor technology, and real-time data handling in self-driving systems.
• Review the varying degrees of vehicle autonomy and their practical applications in the field.
• Scrutinize the ethical, legal, and regulatory dimensions of autonomous transportation.
• Develop practical familiarity with autonomous vehicle simulation platforms.

This live, instructor-led training in Bangkok (online or onsite) is designed for mid-level network engineers and automotive IoT developers aiming to comprehend and deploy V2X communication technologies for autonomous vehicles.

Upon completion, participants will be equipped to:

• Grasp the core principles underlying V2X communication.
• Evaluate V2V, V2I, V2P, and V2N interaction models.
• Deploy V2X standards including DSRC and C-V2X.
• Create simulations for connected vehicle ecosystems.
• Navigate cybersecurity and privacy considerations within V2X networks.

This live, instructor-led training in Bangkok (delivered online or on-site) is tailored for intermediate-level engineers, automotive experts, and IoT professionals aiming to grasp the critical role of sensors in self-driving cars. The course covers LiDAR, radar, cameras, and sensor fusion techniques.

By the conclusion of this program, participants will be able to:

• Differentiate between the various sensor types utilized in autonomous vehicles.
• Process sensor data to enable real-time perception and decision-making.
• Deploy sensor fusion techniques to enhance vehicle accuracy and safety profiles.
• Optimize sensor positioning and calibration to improve autonomous driving performance.

This instructor-led, live training in Bangkok (online or onsite) is designed for advanced safety engineers and automotive professionals aiming to develop comprehensive safety strategies for autonomous vehicles. It emphasizes hazard analysis, functional safety assessments, and compliance with global standards.

By the end of the program, participants will be able to:

• Identify and evaluate safety risks linked to autonomous driving systems.
• Perform hazard analysis and risk assessments using established industry standards.
• Implement safety validation and verification methods for AV systems.
• Apply functional safety standards, including ISO 26262 and SOTIF.
• Create risk mitigation strategies to address AV safety issues.

This instructor-led, live training in Bangkok (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.

This instructor-led, live training available in Bangkok (delivered online or on-site) is specifically designed for intermediate-level AI developers and computer vision engineers seeking to build reliable vision systems for autonomous driving contexts.

By the conclusion of this program, participants will be equipped to:

• Comprehend the essential theories of computer vision in the context of autonomous vehicles.
• Construct algorithms for object detection, lane identification, and semantic segmentation.
• Merge vision technologies with other autonomous vehicle components.
• Deploy deep learning strategies for sophisticated perception tasks.
• Measure the efficacy of computer vision models in practical, real-world conditions.

This instructor-led live training (online or onsite) in Bangkok is tailored for advanced-level robotics engineers and AI researchers seeking to implement advanced path planning algorithms to boost autonomous vehicle performance.

Following this training, participants will be able to:

• Comprehend the theoretical basis of sophisticated path planning algorithms.
• Apply algorithms like RRT*, A*, and D* for real-time navigation tasks.
• Optimize path planning processes for effective obstacle avoidance and dynamic environment adaptation.
• Fuse path planning algorithms with sensor inputs to enhance accuracy.
• Assess algorithm performance in real-world practical contexts.

This instructor-led, live training in Bangkok (available online or onsite) is designed for advanced data scientists, AI specialists, and automotive AI developers looking 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.