Quality Core Tools Training Course

This instructor-led, live training in Italy (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 program explores the application of AI—with a specific focus on Machine Learning and Deep Learning—within the automotive industry. It aims to identify technologies that can be (potentially) utilized across various automotive scenarios, ranging from basic automation and image recognition to autonomous decision-making processes.

This instructor-led, live training in Italy (online or onsite) is aimed at advanced-level 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) is a global collaborative effort involving automotive manufacturers, suppliers, and tool providers, dedicated to standardizing the software architecture for automotive Electronic Control Units (ECUs).

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

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

• Comprehending the architectures of AUTOSAR Classic and Adaptive, along with their principal distinctions.
• Developing and configuring automotive software components utilizing AUTOSAR-compliant tools.
• Integrating and testing ADAS software components within AUTOSAR Adaptive environments.
• Applying 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 accompanied by the simulation of automotive use cases.

Customization Options

• For customized training requests, please contact us to arrange details.

This instructor-led, live training in Italy (online or on-site) 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.
• Enhance operational efficiency.

This instructor-led, live training (available online or on-site) is designed for intermediate-level embedded software developers and automotive engineers aiming to utilize the AUTOSAR Classic Platform for developing, integrating, and testing standardized software components for electronic control units (ECUs).

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

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

Utilizing CANoe or comparable 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 looking to master the configuration of AUTOSAR OS (based on OSEK/VDX) and the COM Stack. The course focuses on establishing 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 the PDUR and communication services
• Explain protocol stacks (CAN, LIN, FlexRay, Ethernet) and AUTOSAR interfaces
• 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 Italy (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 Italy (online or onsite) is designed for intermediate 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:

• Grasp the core concepts of computer vision within autonomous vehicles.
• Develop algorithms for object detection, lane identification, and semantic segmentation.
• Integrate vision systems with other autonomous vehicle components.
• Utilize deep learning methods for advanced perception tasks.
• Assess the performance of computer vision models in real-world contexts.

This instructor-led, live training in Italy (online or onsite) is tailored for beginner-level professionals seeking to delve into 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 Italy (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 Italy (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 Italy (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 Italy (online or onsite) is designed for intermediate-level engineers, automotive industry professionals, and IoT specialists who wish to understand the role of sensors in self-driving cars, covering 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 Italy (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.