Artificial Intelligence (AI) in Automotive Training Course

This live, instructor-led training in Argentina—available online or onsite—targets senior robotics engineers and AI researchers aiming to implement sophisticated path planning algorithms to boost autonomous vehicle performance.

By the end of this training, participants will be capable of:

• Understanding the theoretical foundations of advanced path planning algorithms.
• Deploying 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 to enhance accuracy.
• Evaluating the performance of different algorithms in practical scenarios.

This instructor-led, live program in Argentina (available online or onsite) is designed for advanced data scientists, AI specialists, and automotive AI developers seeking to build, train, and optimize AI models for autonomous driving applications.

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

• Understand the foundational concepts of AI and deep learning within the scope of autonomous vehicles.
• Apply computer vision techniques for real-time object detection and lane tracking.
• Utilize reinforcement learning to facilitate decision-making in self-driving systems.
• Integrate sensor fusion methods to improve perception and navigation capabilities.
• Construct deep learning models for the prediction and analysis of driving situations.

This instructor-led live training in Argentina (online or on-site) targets biologists who wish to understand the functioning of AlphaFold and utilize its models to guide 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 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.