Graduatehttps://www.youtube.com/watch?v=yHoZ9U8bHIQEvery FallFundamentals of AI and Deep LearningThis course provides students with an understanding of the fundamental concepts of artificial intelligence and machine learning and explores applications of these concepts to real world problems. We will review the topics of design of intelligent agents, logic and symbolic reasoning, probabilistic reasoning and decision making, knowledge representation, problem solving techniques, and deep learning. The students will be assigned to apply AI and machine learning techniques in various areas of their interest like cybersecurity, robotics, advanced electronics, software verification, database validation, data cleaning and imputation, product design, environmental engineering, healthcare, drug discovery, etc. Upon completion of the course students should be able to develop solutions to concrete problems and create models and tools based on AI and deep learning techniques.
There are no formal requirements for this class although students should be familiar with basic concepts in logic, probability theory and statistics, linear algebra, and have some programming skills (e.g., Python).
A typical project for the course could explore one of the following:
- Develop an AI application in a programming language (e.g., Python) or utilizing an existing software tool (e.g., neural net software, statistical packages such as R, Bayesian network tools, data mining, etc.)
- Critical review of an existing application, explaining its design and demonstrating its capabilities and shortcomings.
- Research a relevant topic and demonstrate how AI concepts can be applied.BioengineeringCloud EngineeringCybersecurityEngineering Artificial IntelligenceRoboticsSoftware
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