Artificial Intelligence (AI) in Automotive Training Course

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

Upon completion, participants will be equipped to:

• Grasp the core principles of AI and deep learning as they apply to autonomous vehicles.
• Apply computer vision techniques for real-time object detection and lane-keeping functions.
• Leverage reinforcement learning to drive decision-making processes within self-driving systems.
• Combine sensor fusion methods to enhance environmental perception and navigation accuracy.
• Develop deep learning models capable of forecasting and interpreting complex driving scenarios.

This instructor-led live training in Brazil (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:

• Understand the basic principles of AlphaFold.
• Learn how AlphaFold works.
• Learn how to interpret AlphaFold predictions and results.

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

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

• Install and configure AUTOSAR.
• Establish a workflow.
• Navigate the AUTOSAR environment with ease.
• Work efficiently.

This instructor-led, live training (available online or onsite) targets intermediate-level embedded software developers and automotive engineers who intend to use 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 and automotive engineers seeking to understand and configure the AUTOSAR OS (based on OSEK/VDX) and the COM Stack to ensure 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 COM Stack layers, including the PDUR and communication services
• Explain protocol stacks (CAN, LIN, FlexRay, Ethernet) and AUTOSAR's integration 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 Brazil (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 Brazil (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:

• Grasp the fundamental concepts of computer vision in autonomous vehicles.
• Develop 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 Brazil (online or in-person) targets beginner-level professionals eager to explore the ethical dilemmas and legal structures governing autonomous vehicles.

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

• Grasp 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 regarding accidents involving autonomous vehicles.
• Evaluate the equilibrium between innovation and public safety within autonomous driving legislation.
• Discuss real-world case studies encompassing ethical dilemmas and legal disputes.

This instructor-led, live training in Brazil (available online or on-site) is designed for 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 Brazil (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 Brazil (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 Brazil (online or onsite) is designed for intermediate-level engineers, automotive professionals, and IoT specialists who want 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 guided, live training session in Brazil (online or in-person) is tailored for intermediate-level network engineers and automotive IoT developers aiming to comprehend and apply V2X communication technologies for autonomous vehicles.

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

• Grasp the core concepts underlying V2X communication.
• Evaluate V2V, V2I, V2P, and V2N communication models.
• Deploy V2X protocols like DSRC and C-V2X.
• Construct simulations for connected vehicle environments.
• Navigate cybersecurity and privacy issues within V2X networks.