CE-AIAP-1000 - AI Applications in Engineering
Course Description
In this course, engineers will learn to apply AI tools that empower a new approach to complex problems: human experts and AI models working synergistically to make predictions, detect anomalies, and optimize systems. This course includes explorations of improving simulations using neural networks, and use of natural language processing (NLP) for requirements gathering and documentation. Case studies from the high tech industries and more will highlight benefits of AI systems for predictive maintenance and improving safety. Students will also tackle challenges arising from data quality issues and integrating these new tools with existing systems.
Please note that there are two required textbooks for this course that are not included in the cost of registration:
- Artificial Intelligence for Business: Innovation, Tools and Practices, by Ana Landeta Echeberria (ISBN: 978-3030882402)
- Essential Math for AI: Next-Level Mathematics for Efficient and Successful AI Systems, by Hala Nelson (ISBN: 978-1098107635)
Learning objectives
By the end of this course, students will be able to:
- Design simulations that incorporate neural nets and other AI models to improve accuracy
- Evaluate NLP techniques for efficient communication and documentation
- Develop strategies for responding to challenges in AI implementation, such as those arising from poor data quality, bias or the need to integrate new tools with existing systems
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