Artificial Intelligence (AI) in Automotive Training Course

This instructor-led, live training in Kenya (online or onsite) is designed for advanced-level robotics engineers and AI researchers aiming to implement sophisticated path planning algorithms to improve autonomous vehicle performance.

Upon completing this training, participants will be able to:

• Grasp the theoretical underpinnings of advanced path planning algorithms.
• Apply algorithms like RRT*, A*, and D* for real-time navigation.
• Refine path planning strategies for obstacle avoidance and dynamic settings.
• Merge path planning algorithms with sensor data to improve accuracy.
• Assess the performance of different algorithms in practical scenarios.

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

Upon completing this training, participants will gain the ability to:

• Understand the core fundamentals of AI and deep learning as applied to autonomous vehicles.
• Implement computer vision methods for real-time object detection and lane following.
• Use reinforcement learning to facilitate decision-making in self-driving architectures.
• Integrate sensor fusion strategies to improve perception and navigation performance.
• Construct deep learning models for the prediction and analysis of driving scenarios.

This instructor-led live training in Kenya (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 Kenya (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.
• Operate with high efficiency.

This instructor-led live training (available online or onsite) is designed for intermediate-level embedded software developers and automotive engineers looking to utilize 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).

Gain a clear 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).

Utilize CANoe or similar tools for simulation, testing, and diagnostics within an AUTOSAR environment.

This instructor-led, live training (delivered 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. 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 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-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 Kenya (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 Kenya (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 Kenya (online or onsite) is designed for professionals at the beginner level who wish to explore 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 mechanisms in the event of autonomous vehicle accidents.
• Evaluate the balance between innovation and public safety in autonomous driving regulations.
• Discuss real-world case studies involving ethical dilemmas and legal disputes.

This instructor-led, live training session in Kenya (offered online or onsite) 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 Kenya (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 Kenya (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 Kenya (online or onsite) is designed for intermediate-level engineers, automotive professionals, and IoT specialists who aim to comprehend the role of sensors in self-driving cars, encompassing LiDAR, radar, cameras, and sensor fusion techniques.

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

• Understand the various types of sensors utilized in autonomous vehicles.
• Analyze sensor data for real-time vehicle perception and decision-making.
• Implement sensor fusion techniques to enhance vehicle accuracy and safety.
• Optimize sensor placement and calibration for improved autonomous driving performance.

This instructor-led, live training in Kenya (online or onsite) is designed for intermediate-level network engineers and automotive IoT developers who want to understand and implement V2X communication technologies for autonomous vehicles.

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

• Understand the core 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.