Artificial Intelligence (AI) in Automotive Training Course

This instructor-led, live training in Turkey (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 live, instructor-led training in Turkey (online or onsite) is intended for advanced data scientists, AI specialists, and automotive AI developers who aim to construct, train, and optimize AI models for autonomous driving applications.

Upon completing this training, participants will be capable of:

• Grasping the core principles of AI and deep learning as applied to autonomous vehicles.
• Deploying computer vision methods for real-time lane tracking and object identification.
• Applying reinforcement learning to enhance decision-making processes in self-driving systems.
• Employing sensor fusion strategies to improve navigation and environmental perception.
• Developing deep learning models to forecast and evaluate driving situations.

This instructor-led, live training in Turkey (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.

AUTOSAR (AUTomotive Open System ARchitecture) is a global consortium of automotive manufacturers, suppliers, and tool vendors that establishes 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 using AUTOSAR Classic and Adaptive platforms, with a specific emphasis on ADAS (Advanced Driver Assistance Systems).

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

• Comprehend AUTOSAR Classic and Adaptive architectures and identify their key distinctions.
• Develop and configure automotive software components using AUTOSAR-compliant tools.
• Integrate and test ADAS software components within AUTOSAR Adaptive environments.
• Apply industry best practices for safety, security, and performance optimization in automotive systems.

Course Format

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

Customization Options

• For customized training requests regarding this course, please contact us to arrange.

This instructor-led live training in Turkey (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 (online or onsite) is designed for intermediate-level embedded software developers and automotive engineers who want to use 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).

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

Design and implement the AUTOSAR 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 both online and onsite, is designed for intermediate-level embedded software developers and automotive engineers who aim to understand and configure the AUTOSAR OS (based on OSEK/VDX) and the COM Stack. The course focuses on enabling reliable task scheduling and communication within automotive ECUs.

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

• Grasp the AUTOSAR OS architecture and its scheduling policies
• Implement and manage tasks, events, alarms, and counters
• Describe and configure 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-standard tools such as Vector DaVinci or ETAS ISOLAR
• Simulate and validate task and communication flows in an AUTOSAR-based ECU

This instructor-led, live training in Turkey (online or onsite) targets 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 Turkey (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 Turkey (online or onsite) is designed for beginners who want 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 Turkey (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.
• 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 Turkey (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 Turkey (online or onsite) targets 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 Turkey (online or onsite) is aimed at intermediate-level engineers, automotive professionals, and IoT specialists who wish 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 Turkey (online or on-site) is designed for intermediate-level network engineers and automotive IoT developers aiming to comprehend and deploy V2X communication technologies for autonomous vehicles.

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

• Gaining a solid grasp of the core concepts of V2X communication.
• Analyzing V2V, V2I, V2P, and V2N communication models.
• Implementing V2X protocols, including DSRC and C-V2X.
• Creating simulations for connected vehicle environments.
• Managing cybersecurity and privacy challenges within V2X networks.