VDA 6.3 German Automotive Standard Training Course

This instructor-led, live training in the UAE (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.

This instructor-led live training in the UAE (online or onsite) is designed for advanced data scientists, AI specialists, and automotive AI developers seeking to build, train, and optimize AI models for autonomous driving applications.

Upon completion, participants will be able to:

• Grasp the fundamentals of AI and deep learning as they apply to autonomous vehicles.
• Deploy computer vision techniques for real-time object detection and lane following.
• Apply reinforcement learning for decision-making processes in self-driving systems.
• Integrate sensor fusion methods to enhance perception and navigation.
• Construct deep learning models to predict and analyze various driving scenarios.

AUTOSAR (AUTomotive Open System ARchitecture) represents a global collaborative effort among automotive manufacturers, suppliers, and tool vendors to standardize the software architecture used in automotive electronic control units (ECUs).

This instructor-led live training, available either online or onsite, is tailored for intermediate to advanced automotive software developers looking to design, develop, and integrate software utilizing both AUTOSAR Classic and Adaptive platforms, with a specific emphasis on ADAS (Advanced Driver Assistance Systems).

Upon completion of this training, participants will be equipped to:

• Comprehend the architectures of AUTOSAR Classic and Adaptive platforms and identify their primary distinctions.
• Create and configure automotive software components using AUTOSAR-compliant tools.
• Integrate and validate ADAS software components within AUTOSAR Adaptive environments.
• Implement best practices concerning safety, security, and performance optimization for automotive systems.

Format of the Course

• Interactive lectures and discussions.
• Practical exercises using industry-standard AUTOSAR tools.
• Project-based learning alongside simulations of automotive use cases.

Course Customization Options

• For customized training arrangements, please reach out to us.

This instructor-led, live training in the UAE (online or onsite) is primarily designed for engineers who wish to utilize AUTOSAR for designing automotive components.

Upon completion of this training, participants will be able to:

• Install and configure AUTOSAR.
• Establish a workflow.
• Navigate the AUTOSAR environment with ease.
• Operate efficiently.

This instructor-led, live training (available online or on-site) is designed for intermediate-level embedded software developers and automotive engineers who want to leverage the AUTOSAR Classic Platform to develop, integrate, and test standardized software components for electronic control units (ECUs).

By the end of this training, participants will be able to:

Install and configure AUTOSAR development tools (such as DaVinci Developer, EB Tresos, or ETAS ISOLAR-A/B).

Comprehend the AUTOSAR layered architecture and its basic software (BSW) modules.

Design and implement the AUTOSAR operating system (OS) and communication stack (COM stack).

Utilize CANoe or similar tools for simulation, testing, and diagnostics within an AUTOSAR environment.

This instructor-led live training in the UAE (online or onsite) is tailored for automotive engineers aiming to utilize AUTOSAR for the design of automotive motor controllers.

Upon completion of this training, participants will be equipped to:

• Comprehend the AUTOSAR architecture and its underlying methodology.
• Gain the skills necessary to design motor controllers utilizing AUTOSAR standards.

This instructor-led, live training (available online or onsite) is designed for intermediate-level embedded software developers and automotive engineers who wish to understand and configure AUTOSAR OS (based on OSEK/VDX) and the COM Stack to enable reliable task scheduling and communication in automotive ECUs.

By the end of this training, participants will be able to:

• Understand the AUTOSAR OS architecture and scheduling policies
• Implement and manage tasks, events, alarms, and counters
• Describe and configure the COM Stack layers, including PDUR and communication services
• Explain protocol stacks (CAN, LIN, FlexRay, Ethernet) and how AUTOSAR interfaces with them
• Configure OS and COM modules using industry tools (Vector DaVinci or ETAS ISOLAR)
• Simulate and validate task and communication flow in an AUTOSAR-based ECU

This instructor-led, live training in the UAE (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.

This instructor-led live training in the UAE (online or onsite) targets intermediate-level AI developers and computer vision engineers seeking to build robust vision systems for autonomous driving applications.

Upon completion 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.

This instructor-led, live training in the UAE (online or onsite) is designed for beginner-level professionals interested in exploring the ethical dilemmas and legal frameworks surrounding autonomous vehicles.

Upon completing this training, participants will be capable of:

• Comprehending the ethical implications of AI-driven decision-making within autonomous vehicles.
• Analyzing global legal frameworks and policies that govern self-driving cars.
• Investigating liability and accountability issues arising from autonomous vehicle accidents.
• Assessing the equilibrium between innovation and public safety in autonomous driving legislation.
• Engaging in discussions on real-world case studies involving ethical conflicts and legal disputes.

This instructor-led live training is designed for intermediate-level professionals who seek a thorough understanding of EV powertrain architectures, battery chemistry, Battery Management Systems (BMS), and the factors affecting energy efficiency in electric vehicles.

By the end of this training, participants will be able to:

• Understand the structure and function of EV powertrains.
• Analyze different battery chemistries and their applications in EVs.
• Implement battery management techniques to enhance performance and safety.
• Evaluate energy efficiency in various EV configurations.

This instructor-led, live training in the UAE (online or onsite) is designed for 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.

This instructor-led live training in the UAE (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 in the UAE (online or onsite) targets intermediate-level engineers, automotive professionals, and IoT specialists who aim to comprehend the significance of sensors in self-driving cars. The curriculum covers LiDAR, radar, cameras, and sensor fusion techniques.

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

• Grasp 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.

This instructor-led, live training in the UAE (online or onsite) targets intermediate-level network engineers and automotive IoT developers who aim to understand and implement V2X communication technologies for autonomous vehicles.

By the conclusion 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.