AI for Design and Optimization
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AI for Design and Optimization
This course is part of AI for Mechanical Engineers Specialization
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What you'll learn
Learn the fundamentals of artificial intelligence (AI) relevant to engineering design and optimization processes
Enhance engineering design creativity and optimize strategies by applying AI techniques
Learn to discern appropriate applications of AI to ensure effective integration into workflows
Learn to interpret outputs generated by AI models accurately
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There are 3 modules in this course
Artificial intelligence and machine learning are revolutionizing design processes, optimizing strategies, and fostering innovation across industries. "AI for Design and Optimization” offers you the knowledge to harness the power of AI to enhance your own design and optimization capabilities. Mastering key skills such as discerning appropriate AI applications, interpreting model outputs, staying abreast of AI advancements, and effectively communicating the role of AI in projects is essential to effectively leverage these technologies in your practices. You will delve into the fundamentals of AI and their practical application in design and optimization, exploring advanced techniques like generative design, evolutionary algorithms, and topology optimization. This unique curriculum provides a comprehensive introduction to utilizing AI to enhance design creativity and streamline processes.
In module 1, you will be introduced to artificial intelligence (AI) and machine learning (ML), along with the essential vocabulary necessary to effectively communicate with relevant stakeholders. You will explore various applications of AI/ML in design and optimization, and understand the challenges associated with implementing these technologies in these fields.
What's included
4 videos6 readings1 assignment2 ungraded labs
4 videos•Total 34 minutes
- Introduction to Key Concepts•7 minutes
- Machine Learning Algorithms•6 minutes
- Deep Learning and Neural Network•10 minutes
- Introduction of AI/ML in Design and Optimization•12 minutes
6 readings•Total 60 minutes
- Course Syllabus•10 minutes
- Help Us Learn About You!•10 minutes
- Introduction to Jupyter Labs on Coursera•10 minutes
- K-Nearest Neighbors Implementation•10 minutes
- DNN Implementation•10 minutes
- Overfitting and Underfitting of ML•10 minutes
1 assignment•Total 30 minutes
- Module 1 Assignment•30 minutes
2 ungraded labs•Total 120 minutes
- K-Nearest Neighbor - Programming Exercise•60 minutes
- Neural Networks - Programming Exercise•60 minutes
In module 2, you will delve into the principles, tools, and applications of generative design across various industries. You will learn to unlock the power of generative design to revolutionize your approach to creativity and problem-solving. Generative design is a cutting-edge approach that harnesses the capabilities of AI and computational algorithms to explore design solutions.
What's included
3 videos1 reading1 assignment1 ungraded lab
3 videos•Total 19 minutes
- Generative Design Principles•8 minutes
- Introduction to Algorithms and Techniques•4 minutes
- Generative Adversarial Networks•6 minutes
1 reading•Total 10 minutes
- GAN in Pytorch Implementation•10 minutes
1 assignment•Total 30 minutes
- Module 2 Assignment•30 minutes
1 ungraded lab•Total 60 minutes
- Generative Adversarial Networks- Programming Exercise•60 minutes
In module 3, you will explore a range of AI-driven optimization algorithms and their applications across diverse industries. You will learn how to apply AI in optimizing complex systems and processes. Optimization lies at the heart of many decision-making processes, and AI technologies offer powerful tools to enhance efficiency, effectiveness, and innovation.
What's included
5 videos6 readings1 assignment2 ungraded labs
5 videos•Total 41 minutes
- Overview of Optimization Problems•6 minutes
- Introduction to Optimization Algorithms•12 minutes
- Introduction of Topology Optimization•6 minutes
- ML for Topology Optimization•8 minutes
- Case Studies•9 minutes
6 readings•Total 60 minutes
- Case Studies: Thermal Insulation Optimization•10 minutes
- Thermal Insulation Optimization•10 minutes
- Case Studies: Battery Fast-Charging Optimization•10 minutes
- Battery Fast-Charging Optimization Implementation•10 minutes
- End of Course Survey•10 minutes
- References•10 minutes
1 assignment•Total 30 minutes
- Module 3 Assignment•30 minutes
2 ungraded labs•Total 120 minutes
- Thermal Insulation Optimization - Programming Exercise•60 minutes
- Battery Charging Optimization - Programming Exercise•60 minutes
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Reviewed on May 20, 2026
Highly useful for mechanical engineering master's students
Reviewed on Oct 1, 2025
Nice overview of AI application for design engineers
Reviewed on Nov 11, 2025
An amazing course, I got to learn a lot about optimisation than what I knew.
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