Artificial Intelligence (AI) in Automotive Training Course

This instructor-led, live training in Bulgaria (online or onsite) is designed for advanced-level robotics engineers and AI researchers seeking to implement sophisticated path planning algorithms to optimize autonomous vehicle performance.

Upon completing this training, participants will be capable of:

• Understanding the theoretical foundations of advanced path planning algorithms.
• Implementing algorithms such as RRT*, A*, and D* for real-time navigation.
• Optimizing path planning for obstacle avoidance and dynamic environments.
• Integrating path planning algorithms with sensor data for enhanced accuracy.
• Evaluating the performance of various algorithms in practical scenarios.

This live, instructor-led training in Bulgaria (conducted online or onsite) targets advanced data scientists, AI experts, and automotive developers aiming to build, train, and optimize AI models for autonomous driving.

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

• Comprehend the foundational concepts of AI and deep learning within the autonomous vehicle domain.
• Implement computer vision solutions for real-time object detection and lane tracking.
• Apply reinforcement learning strategies to drive decision-making in self-driving systems.
• Employ sensor fusion techniques to enhance perception and navigation capabilities.
• Create deep learning models for the prediction and analysis of driving scenarios.

This instructor-led, live training in Bulgaria (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:

• Grasp the fundamental principles of AlphaFold.
• Learn how AlphaFold operates.
• Master the interpretation of AlphaFold predictions and results.

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

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

• Install and configure AUTOSAR.
• Establish a development workflow.
• Navigate the AUTOSAR environment with ease.
• Work more 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 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 able to:

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

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

Design and implement the AUTOSAR OS and communication stack (COM stack).

Utilize CANoe or comparable 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 or automotive engineers who aim to understand and configure AUTOSAR OS (based on OSEK/VDX) and the COM Stack to facilitate reliable task scheduling and communication within automotive ECUs.

Upon completing 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 (Vector DaVinci or ETAS ISOLAR)
• Simulate and validate task and communication flows in an AUTOSAR-based ECU

Delivered as an instructor-led, live training in Bulgaria (online or onsite), this course 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 Bulgaria (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 Bulgaria (online or onsite) is designed for beginner-level professionals interested in exploring 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 Bulgaria (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 Bulgaria (online or onsite) targets beginner-level professionals and enthusiasts eager to grasp the fundamental concepts, technologies, and applications of autonomous vehicles.

Upon completing this training, participants will be capable of:

• Gaining insight into the key components and operational principles of autonomous vehicles.
• Exploring the role of AI, sensors, and real-time data processing in self-driving systems.
• Assessing various levels of vehicle autonomy and their real-world applications.
• Evaluating the ethical, legal, and regulatory aspects of autonomous mobility.
• Acquiring hands-on experience with autonomous vehicle simulations.

This instructor-led, live training in Bulgaria (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 Bulgaria (online or onsite) is designed for intermediate-level engineers, automotive professionals, and IoT specialists who wish to gain insight into the role of sensors in self-driving cars. The curriculum covers LiDAR, radar, cameras, and sensor fusion techniques.

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

• Identify and understand the various types of sensors utilized 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 Bulgaria (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:

• Grasp 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.