Electronics Testing Methods provides a comprehensive exploration of various testing techniques essential for ensuring the reliability and performance of electronic systems. Participants will engage in hands-on projects that simulate real-world testing scenarios, fostering an in-depth understanding of methodologies used in the industry. The course emphasizes interactive learning, allowing participants to apply theoretical knowledge in practical settings, thereby enhancing their problem-solving skills and technical expertise.
Through a blend of lectures, collaborative projects, and individual assignments, learners will delve into critical aspects of electronics testing. The curriculum is designed to equip participants with the necessary tools to assess electronic components and systems effectively. By the end of the course, participants will have the opportunity to publish their findings in Cademix Magazine, showcasing their work to a broader audience.
Fundamentals of Electronics Testing
Types of Testing: Functional, Structural, and Environmental
Test Equipment and Instrumentation
Design for Testability (DFT) Principles
Automated Testing Techniques
Signal Integrity Testing
Fault Diagnosis and Troubleshooting
Reliability Testing and Analysis
Case Studies of Electronics Testing in Industry
Final Project: Comprehensive Testing Plan for a Selected Electronic System

Power Management Systems focuses on the intricacies of designing and implementing efficient power management solutions in electronic devices. This course equips participants with the knowledge and skills necessary to optimize energy consumption, enhance system reliability, and improve overall performance in embedded systems. Through hands-on projects, learners will engage in practical applications that reinforce theoretical concepts, preparing them for immediate contributions in the field.
The curriculum emphasizes real-world applications, encouraging participants to explore innovative techniques and methods in power management. By collaborating on projects and publishing findings in Cademix Magazine, learners will not only gain expertise but also build a professional portfolio. The course culminates in a final project that requires participants to design a comprehensive power management system, integrating various techniques learned throughout the program.
Introduction to Power Management Systems
Energy Harvesting Techniques
Battery Management Systems
Power Conversion and Regulation
Dynamic Voltage Scaling
Load Management Strategies
Power Efficiency Metrics and Analysis
Design for Low Power Consumption
Simulation Tools for Power Management
Final Project: Designing a Power Management System for an Embedded Application

Edge AI Hardware Fundamentals delves into the essential components and methodologies that underpin the development and deployment of artificial intelligence at the edge of networks. Participants will engage with hands-on projects that emphasize practical applications, enabling them to design and implement AI solutions that operate efficiently on localized hardware. This course is structured to provide a comprehensive understanding of the intersection between AI algorithms and embedded systems, focusing on real-world scenarios that professionals encounter in the field.
Throughout the program, learners will explore the intricacies of hardware design, data processing, and AI model optimization for edge devices. By collaborating on projects, participants will not only gain technical expertise but also have the opportunity to contribute their findings to Cademix Magazine, fostering a culture of knowledge sharing and innovation. The course culminates in a final project that challenges participants to create a functional edge AI application, integrating the skills and concepts acquired during the training.
Introduction to Edge AI Concepts
Overview of Embedded Systems Architecture
Hardware Components for Edge AI Applications
Data Acquisition and Preprocessing Techniques
AI Model Selection and Optimization Strategies
Deployment of AI Models on Edge Devices
Real-Time Data Processing and Analytics
Power Management and Efficiency in Edge AI
Case Studies of Edge AI Implementations
Final Project: Development of an Edge AI Solution