Electronic Control Unit (ECU) - Theoretical Vector Training Course

This live, instructor-led training in Czech Republic (online or onsite) is designed for advanced robotics engineers and AI researchers looking to implement refined path planning algorithms to improve autonomous vehicle performance.

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

• Understand the core theoretical principles behind advanced path planning algorithms.
• Apply algorithms like RRT*, A*, and D* for real-time navigation tasks.
• Optimize path planning strategies for obstacle avoidance and dynamic environments.
• Combine path planning with sensor data to enhance accuracy.
• Evaluate algorithm performance in real-world scenarios.

This instructor-led, live training in Czech Republic (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.

This instructor-led, live training in Czech Republic (online or on-site) 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.
• Set up a workflow.
• Navigate smoothly in the AUTOSAR environment.
• Work 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 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 able to:

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

Gain an understanding of the AUTOSAR layered architecture and its basic software modules (BSW).

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 (available online or onsite) is designed for intermediate-level embedded software developers and automotive engineers who want to understand and configure AUTOSAR OS (based on OSEK/VDX) along with the COM Stack to ensure reliable task scheduling and communication within automotive ECUs.

Upon completing this training, participants will be able to:

• Gain insight into the AUTOSAR OS architecture and its 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 interacts with them
• Configure OS and COM modules using industry-standard tools (Vector DaVinci or ETAS ISOLAR)
• Simulate and validate task and communication flows in an AUTOSAR-based ECU

This guided, live training session in Czech Republic (online or in person) targets advanced safety engineers and automotive safety experts aiming to create thorough safety strategies for autonomous vehicles. The curriculum covers hazard analysis, functional safety assessments, and adherence to international standards.

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

• Recognizing and evaluating safety risks linked to autonomous driving systems.
• Performing hazard analysis and risk assessment in accordance with industry standards.
• Applying safety validation and verification techniques for autonomous vehicle (AV) systems.
• Utilizing functional safety standards, including ISO 26262 and SOTIF.
• Creating risk mitigation strategies to address safety challenges in AVs.

This instructor-led, live training in Czech Republic (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:

• Gain a solid understanding of 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 Czech Republic (online or onsite) is targeted at engineers and scientists who wish to learn and apply DSP implementations to efficiently handle different signal types and gain better control over multi-channel electronic systems.

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

• Set up and configure the necessary software platform and tools for Digital Signal Processing.
• Understand the concepts and principles that are foundational to DSP and its applications.
• Familiarize themselves with DSP components and employ them in electronics systems.
• Generate algorithms and operational functions using the results from DSP.
• Utilize the basic features of DSP software platforms and design signal filters.
• Synthesize DSP simulations and implement various types of filters for DSP.

This instructor-led, live training in Czech Republic (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 Czech Republic (online or onsite) is designed for intermediate-level professionals seeking a comprehensive understanding of EV powertrain architectures, battery chemistry, battery management systems (BMS), and the factors that influence 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 Czech Republic (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, available in Czech Republic (online or onsite), is designed for 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 Czech Republic (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 Czech Republic (online or onsite) targets intermediate network engineers and automotive IoT developers aiming to understand and apply V2X communication technologies for autonomous vehicles.

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

• Grasp the core principles of V2X communication.
• Evaluate V2V, V2I, V2P, and V2N communication models.
• Deploy V2X protocols including DSRC and C-V2X.
• Creating simulations for connected vehicle ecosystems.
• Resolving cybersecurity and privacy issues within V2X networks.