Quality Core Tools Training Course

This instructor-led, live training in Argentina (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—particularly Machine Learning and Deep Learning—within the automotive sector. It equips participants with the knowledge to identify technologies that can be applied across various scenarios in vehicles, ranging from basic automation and image recognition to advanced autonomous decision-making.

This instructor-led, live training in Argentina (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) represents a global collaborative initiative among automotive manufacturers, suppliers, and tool developers to establish a standardized software architecture for automotive electronic control units (ECUs).

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

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

• Grasp the architectures of AUTOSAR Classic and Adaptive platforms, along with their primary distinctions.
• Create and configure automotive software components using tools that comply with AUTOSAR standards.
• Integrate and test ADAS software components within AUTOSAR Adaptive environments.
• Implement best practices concerning safety, security, and performance optimization for automotive systems.

Format of the Course

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

Course Customization Options

• For those interested in a customized training program for this course, please reach out to us to arrange the details.

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

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

• Install and configure AUTOSAR.
• Establish a workflow.
• Navigate the AUTOSAR environment with ease.
• Enhance efficiency in their work.

This instructor-led, live training (online or onsite) is designed for intermediate-level embedded software developers and automotive engineers who want to leverage the AUTOSAR Classic Platform to create, integrate, and test standardized software components for electronic control units (ECUs).

By the conclusion 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 modules (BSW).

Design and implement the AUTOSAR Operating System (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 (online or onsite) is designed for intermediate-level embedded software developers or automotive engineers who want to understand and configure AUTOSAR OS (based on OSEK/VDX) and the COM Stack to enable reliable task scheduling and communication in automotive ECUs.

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

• Grasp the AUTOSAR OS architecture and 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 how AUTOSAR interfaces with them
• Configure OS and COM modules using industry tools (Vector DaVinci or ETAS ISOLAR)
• Simulate and validate task and communication flow in an AUTOSAR-based ECU

This instructor-led, live training in Argentina (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 Argentina (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 Argentina (available online or on-site) is designed for beginner-level professionals keen on exploring the ethical dilemmas and legal frameworks associated with autonomous vehicles.

By the conclusion 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 Argentina (online or onsite) is intended for intermediate-level professionals seeking a thorough understanding of EV powertrain architectures, battery chemistry, battery management systems (BMS), and the factors influencing energy efficiency in electric vehicles.

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

• Grasp the structure and function of EV powertrains.
• Analyze various battery chemistries and their applications in EVs.
• Apply battery management techniques to improve performance and safety.
• Assess energy efficiency across different EV configurations.

This instructor-led, live training in Argentina (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 Argentina (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 Argentina (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 Argentina (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.