AI Machine Learning Kit – Course Overview
This course is designed to introduce learners to the fundamentals of Artificial Intelligence (AI) and Machine Learning (ML) through practical, hands-on activities using the Weeemake AI Lens. Starting with basic concepts, students gradually explore vision-based AI applications such as face recognition, object detection, and color tracking. The course emphasizes creativity and real-world problem-solving by guiding learners to build intelligent systems like smart security solutions, AI-powered robots, and automated waste classifiers.
Through engaging lessons and projects, students will:
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Understand how AI and ML work
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Learn to use AI hardware (AI Lens) and software (mBlock)
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Experiment with pre-trained AI models
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Build their own AI-enabled robots and applications
Whether for classroom education or STEM workshops, this course builds a solid foundation in modern AI technologies, preparing students for a future where intelligent machines are part of everyday life.
Curriculum
- 6 Sections
- 17 Lessons
- 10 Weeks
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- 🔹 Section 1 – Introduction to AIOT & Basic ComponentsGoal: Introduce learners to the ELF AIOT K210 development board, its peripheral devices, and the basic use of an LCD display and camera, setting the foundation for AI-powered projects.4
- 🔹 Section 2 – Basic AI Perception & RecognitionGoal: Develop essential AI perception skills by exploring image, color, tag, and voice recognition, enabling learners to implement fundamental AI features in interactive applications.6
- 🔹 Section 3 – Mobile Robotics BasicsGoal: Teach the fundamentals of mobile robotics control and basic vision-based object tracking, combining mechanical movement with AI perception.3
- 🔹 Section 4 – Advanced Mecanum Robotics & VisionGoal: Master multi-directional mecanum drive control and vision-based autonomous navigation for more complex robotic movement and object following.3
- 🔹 Section 5 – Advanced AI Vision ApplicationsGoal: Implement advanced AI vision algorithms for face detection/tracking and autonomous patrol, simulating security and monitoring applications.3
- 🔹 Section 6 – AI Model Development & OptimizationGoal: Introduce learners to AI model training, the theoretical principles behind machine intelligence, and methods to optimize AI performance for real-world applications.4
Instructor
