Introduction to Artificial Intelligence (AI)
Course Description
The objective of this Fusion 360 training course is to enable you to create, modify, and work efficiently with 3D mechanical and product designs. Fusion 360 is a leading cloud-based 3D CAD, CAM, and CAE software used globally in engineering, manufacturing, and product development industries, and this course equips you with the essential skills to start working professionally with it.
The objective of this Fusion 360 training course is to enable you to create, modify, and work efficiently with 3D mechanical and product designs. Fusion 360 is a leading cloud-based 3D CAD, CAM, and CAE software used globally in engineering, manufacturing, and product development industries, and this course equips you with the essential skills to start working professionally with it.
Who This Course Is Aimed At
- Understanding the Fusion 360 workspace and user interface
- Using basic part modeling, editing, and viewing tools
- Organizing model components using assemblies and constraints
- Using reusable components (templates and design libraries)
- Preparing technical drawings and layouts for production
- Adding text, dimensions, and annotations
Learning Delivery & Support
- Understanding the Fusion 360 workspace and user interface
- Using basic part modeling, editing, and viewing tools
- Organizing model components using assemblies and constraints
- Using reusable components (templates and design libraries)
- Preparing technical drawings and layouts for production
- Adding text, dimensions, and annotations
| Module | Title | Topics & Subtopics |
|---|---|---|
| 1 | Intro to AI | AI vs traditional programming, Narrow vs General AI. |
| 2 | AI Foundations | Algorithms, training vs inference, and bias limitations. |
| 3 | AI Systems | Supervised, unsupervised, and reinforcement learning. |
| 4 | Data for AI | Collection, quality, labeling, and ethical use. |
| 5 | AI for Educators | Teaching tools, generative AI, and responsible use. |
| 6 | Machine Learning | Features, labels, model accuracy, and overfitting. |
| 7 | AI Programming | APIs, pre-trained models, and pseudocode logic. |
| 8 | Educational Robotics | Computer vision, perception, and decision-making. |
| 9 | System Integration | Data flow, Edge vs Cloud AI, and safety. |
| 10 | Ethics & Safety | Transparency, explainability, and data privacy. |
| 11 | Learning Projects | Scaffolding AI concepts and curriculum alignment. |
| 12 | Capstone Project | Problem identification, model selection, and reflection. |
Important Notes:
Edutronics reserves the right to make changes to the curriculum and/or admission requirements. Fees, textbooks and any special equipment you will need is detailed by the middle of the year on the “Additional costs schedule” available from your closest campus.
