Artificial Intelligence (AI) in Automotive Training Course

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

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

• Understand the core theories behind advanced path planning algorithms.
• Deploy algorithms such as RRT*, A*, and D* for real-time navigation tasks.
• Optimize path planning to manage obstacle avoidance in dynamic environments.
• Merge path planning algorithms with sensor data to improve accuracy.
• Measure the effectiveness of various algorithms in practical applications.

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

By the end of this program, participants will be equipped to:

• Understand the foundational concepts of AI and deep learning within the context of autonomous vehicles.
• Implement computer vision techniques to enable real-time object detection and lane following.
• Utilize reinforcement learning to drive decision-making in self-driving systems.
• Integrate sensor fusion methods to enhance perception and navigation.
• Develop deep learning models for the prediction and analysis of driving scenarios.

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.

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.