Artificial Intelligence (AI) in Automotive Training Course

This live, instructor-led training in Sweden (offered online or on-site) is designed for senior robotics engineers and AI researchers aiming to implement sophisticated path planning algorithms to optimize autonomous vehicle performance.

By the conclusion of this program, participants will possess the ability to:

• Comprehend the theoretical basis of advanced path planning algorithms.
• Apply algorithms like RRT*, A*, and D* for real-time navigation tasks.
• Optimize path planning to navigate obstacle avoidance and dynamic settings.
• Combine path planning algorithms with sensor data to boost precision.
• Measure the effectiveness of various algorithms in real-world practical scenarios.

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

Upon completion, participants will be equipped to:

• Grasp the core principles of AI and deep learning within the autonomous vehicle landscape.
• Apply computer vision methods for real-time object detection and lane-tracking tasks.
• Leverage reinforcement learning to drive decision-making processes in self-driving systems.
• Combine sensor fusion techniques to improve perception accuracy and navigation precision.
• Develop deep learning models capable of predicting and analyzing complex driving scenarios.

This instructor-led, live training in Sweden (online or onsite) is aimed at biologists who wish to understand how AlphaFold works and use AlphaFold models as guides in their experimental studies.

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

• Understand the basic principles of AlphaFold.
• Learn how AlphaFold works.
• Learn how to interpret AlphaFold predictions and results.

This instructor-led live training in Sweden (online or onsite) is primarily aimed at engineers who wish to use 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 looking to leverage the AUTOSAR Classic Platform to develop, integrate, and test standardized software components for electronic control units (ECUs).

Upon completing 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 solid understanding of the AUTOSAR layered architecture and its basic software modules (BSW).

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

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

This instructor-led, live training (online or onsite) is aimed at intermediate-level embedded software developers or 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:

• Grasp 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 Sweden (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 Sweden (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 Sweden (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 Sweden (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.

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

• Understand the structure and function of EV powertrains.
• Analyse 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 Sweden (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 Sweden (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:

• Grasp the core principles and challenges of multi-sensor data fusion.
• Apply sensor fusion algorithms to achieve real-time autonomous navigation.
• Combine data from LiDAR, cameras, and RADAR to improve perception capabilities.
• Assess and evaluate fusion system performance under diverse conditions.
• Create practical solutions for reducing sensor noise and aligning data.

This instructor-led, live training in Sweden (online or onsite) is designed for intermediate-level engineers, automotive professionals, and IoT specialists aiming to grasp the critical role of sensors in self-driving cars, with a focus on LiDAR, radar, cameras, and sensor fusion techniques.

Upon completing this training, participants will be able to:

• Identify and understand the various types of sensors employed in autonomous vehicles.
• Analyze sensor data to support real-time vehicle perception and decision-making processes.
• Apply sensor fusion techniques to enhance vehicle accuracy and safety.
• Optimize sensor placement and calibration to improve overall autonomous driving performance.

This instructor-led, live training in Sweden (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.