Quality Core Tools Training Course

This instructor-led, live training in Kenya (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—specifically focusing on Machine Learning and Deep Learning—within the automotive sector. It guides learners in identifying technologies that can be effectively applied across various in-car scenarios, ranging from basic automation and image recognition to complex autonomous decision-making processes.

This guided, live training in Kenya (available online or on-site) targets advanced-level data scientists, AI specialists, and automotive AI developers who aim to construct, train, and optimize AI models for autonomous driving applications.

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

• Grasping the core principles of AI and deep learning as they apply to autonomous vehicles.
• Applying computer vision methods for real-time object identification and lane adherence.
• Employing reinforcement learning to facilitate decision-making processes in self-driving systems.
• Combining sensor fusion techniques to enhance perception and navigation capabilities.
• Developing deep learning architectures to forecast and interpret driving situations.

AUTOSAR (AUTomotive Open System ARchitecture) represents a global partnership among automotive manufacturers, suppliers, and tool developers, dedicated to standardizing the 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 who aim to design, develop, and integrate software using both AUTOSAR Classic and Adaptive platforms, with a specific emphasis on ADAS (Advanced Driver Assistance Systems).

Upon completing this training, participants will be equipped to:

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

Course Format

• Interactive lectures and discussions.
• Practical exercises using industry-standard AUTOSAR tools.
• Project-based learning that simulates real-world automotive use cases.

Course Customization Options

• For customized training arrangements for this course, please get in touch with us.

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.