Quality Core Tools Training Course

This instructor-led, live training in Greece (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 course explores the application of AI—specifically Machine Learning and Deep Learning—within the automotive sector. It aims to identify technologies that can be (potentially) utilized across various automotive scenarios: from basic automation and image recognition to autonomous decision-making.

This instructor-led live training in Greece (online or on-site) is designed for advanced 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.

AUTOSAR (AUTomotive Open System ARchitecture) represents a global collaborative effort among automotive OEMs, suppliers, and tool vendors to establish a standardized software architecture for automotive Electronic Control Units (ECUs).

This instructor-led training session, available online or on-site, targets intermediate to advanced automotive software engineers looking to design, develop, and integrate software using both AUTOSAR Classic and Adaptive platforms, with a specific emphasis on Advanced Driver Assistance Systems (ADAS).

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

• Gaining insight into the architectures of AUTOSAR Classic and Adaptive, along with their primary distinctions.
• Creating and configuring automotive software components using tools compliant with AUTOSAR standards.
• Integrating and validating ADAS software components within AUTOSAR Adaptive environments.
• Implementing best practices regarding safety, security, and performance optimization for automotive systems.

Course Format

• Engaging lectures and interactive discussions.
• Practical exercises utilizing industry-standard AUTOSAR tools.
• Project-based learning accompanied by simulations of automotive use cases.

Customization Options

• For information on arranging custom training for this course, please get in touch with us.

This instructor-led live training in Greece (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 onsite) is designed for intermediate-level embedded software developers and automotive engineers aiming to utilize the AUTOSAR Classic Platform for the development, integration, and testing of standardized software components for electronic control units (ECUs).

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

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

Gain a comprehensive understanding of the AUTOSAR layered architecture and its Basic Software (BSW) modules.

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

Employ CANoe or analogous tools for simulation, testing, and diagnostics within an AUTOSAR environment.

This instructor-led, live training (available online or on-site) is designed for intermediate-level embedded software developers and automotive engineers aiming 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 the COM Stack layers, including PDUR and communication services
• Explain protocol stacks (CAN, LIN, FlexRay, Ethernet) and AUTOSAR's interaction 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 instructor-led, live training in Greece (online or onsite) is targeted at advanced safety engineers and automotive safety professionals looking to develop comprehensive safety strategies for autonomous vehicles, covering hazard analysis, functional safety assessments, and adherence to international standards.

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

• Identify and evaluate safety risks related to autonomous driving systems.
• Perform hazard analysis and risk assessments using industry standards.
• Implement safety validation and verification methods for AV systems.
• Apply functional safety standards, such as ISO 26262 and SOTIF.
• Develop strategies to mitigate risks associated with AV safety challenges.

This instructor-led, live training in Greece (online or onsite) targets intermediate-level AI developers and computer vision engineers who aim to construct robust vision systems for autonomous driving applications.

Upon completing this training, participants will be able to:

• Grasp the fundamental concepts of computer vision within autonomous vehicles.
• Deploy 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 Greece (online or onsite) is designed for beginner-level professionals interested in exploring the ethical dilemmas and legal frameworks governing autonomous vehicles.

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

• Comprehend 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 concerning autonomous vehicle accidents.
• Evaluate the balance between innovation and public safety within autonomous driving laws.
• Discuss real-world case studies involving ethical dilemmas and legal disputes.

This instructor-led, live training in Greece (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 Greece (online or onsite) is designed for beginner-level professionals and enthusiasts who want to understand the fundamental concepts, technologies, and applications of autonomous vehicles.

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

• Comprehend 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 various 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 Greece (online or onsite) is designed for advanced sensor fusion specialists and AI engineers seeking 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 fundamental concepts and challenges of multi-sensor data fusion.
• Implement sensor fusion algorithms for real-time autonomous navigation.
• Integrate data from LiDAR, cameras, and RADAR for enhanced perception.
• Analyze and evaluate the performance of fusion systems under various conditions.
• Develop practical solutions for sensor noise reduction and data alignment.

This instructor-led live training in Greece (online or onsite) targets intermediate-level engineers, automotive professionals, and IoT specialists seeking to understand the function 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 Greece (online or onsite) is designed for intermediate-level network engineers and automotive IoT developers who wish to understand and implement V2X communication technologies for autonomous vehicles.

By the conclusion 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.