Quality Core Tools Training Course

This instructor-led, live training in France (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 course explores the application of AI, with a focus on Machine Learning and Deep Learning, within the automotive industry. It aids in identifying technologies suitable for various in-vehicle scenarios, ranging from basic automation and image recognition to autonomous decision-making processes.

This instructor-led live training in France (online or onsite) is designed for advanced data scientists, AI specialists, and automotive AI developers seeking to construct, 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.

AUTOSAR (AUTomotive Open System ARchitecture) represents a global collaborative effort among automotive manufacturers, suppliers, and tool vendors to establish standardized software architectures for automotive electronic control units (ECUs).

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

Upon completing this training, participants will be capable of:

• Comprehending the architectures of AUTOSAR Classic and Adaptive platforms and identifying their primary distinctions.
• Developing and configuring automotive software components using AUTOSAR-compliant tools.
• Integrating and testing ADAS software components within AUTOSAR Adaptive environments.
• Applying best practices for safety, security, and performance optimization in automotive systems.

Format of the Course also allows for the evaluation of participants.

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

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

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

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

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

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

Upon completion of this training, participants will be capable of:

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

Gaining a comprehensive understanding of the AUTOSAR layered architecture and basic software modules (BSW).

Designing and implementing the AUTOSAR Operating System (OS) and communication stack (COM stack).

Utilizing CANoe or comparable tools for simulation, testing, and diagnostics within an AUTOSAR environment.

This instructor-led training session, available both online and onsite, is designed for intermediate-level embedded software developers and automotive engineers seeking to master the configuration of AUTOSAR OS (rooted in OSEK/VDX standards) and the COM Stack. The course focuses on establishing robust task scheduling and communication protocols within automotive ECUs.

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

• Grasp the AUTOSAR OS architecture and its scheduling policies
• Develop and manage tasks, events, alarms, and counters effectively
• Detail and configure COM Stack layers, encompassing PDUR and essential communication services
• Explain protocol stacks (including CAN, LIN, FlexRay, and Ethernet) and AUTOSAR's interface mechanisms
• Utilize industry-standard tools such as Vector DaVinci or ETAS ISOLAR to configure OS and COM modules
• Simulate and verify task execution and communication flows in AUTOSAR-based ECUs

This instructor-led, live training in France (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 France (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.

This instructor-led, live training in France (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.

This instructor-led, live training in France (online or onsite) is aimed at intermediate-level professionals who wish to gain a comprehensive understanding of EV powertrain architectures, battery chemistry, battery management systems (BMS), and the factors affecting energy efficiency in electric vehicles.

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

• Comprehend the structure and function of EV powertrains.
• Analyze various battery chemistries and their applications in EVs.
• Apply battery management techniques to enhance performance and safety.
• Assess energy efficiency across different EV configurations.

This instructor-led, live training in France (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.

This instructor-led, live training in France (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 France (online or onsite) is designed for intermediate-level engineers, automotive professionals, and IoT specialists who want 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.

This instructor-led, live training in France (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.