Applied Artificial Intelligence
Timeline
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January 17, 2022Experience start
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January 22, 2022Project Scope Meeting
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February 19, 2022Mid-term review
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March 26, 2022Experience end
Timeline
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January 17, 2022Experience start
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January 22, 2022Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
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February 19, 2022Mid-term review
Students will review their progress with company and the course instructor.
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March 26, 2022Experience end
Experience scope
Categories
Information technology Data analysisSkills
communication research data analysisThe purpose of this project is to provide students with an opportunity to apply existing Machine Learning algorithms to wide application area. In the lecture, students are introduced to the use of classical artificial intelligence techniques and the latest deep learning algorithms, which they would be able to apply to a project in your organization.
Classical artificial intelligence techniques include knowledge representation, heuristic algorithms, rule-based systems, probabilistic reasoning, fuzzy systems, neural networks, and genetic algorithms.
Deep learning algorithms include Convolutional Neural Networks (CNNs), Long Short Term Memory Networks (LSTMs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs).
By working with the students group, companies are able to testify their business idea, gather & analysis raw data, develop & verify AI algorithms & prototypes.
Students
Deliverables will depend on the project and employer type. In general, they will be prototypes, analysis reports, etc.
Project timeline
-
January 17, 2022Experience start
-
January 22, 2022Project Scope Meeting
-
February 19, 2022Mid-term review
-
March 26, 2022Experience end
Timeline
-
January 17, 2022Experience start
-
January 22, 2022Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
-
February 19, 2022Mid-term review
Students will review their progress with company and the course instructor.
-
March 26, 2022Experience end
Project Examples
Requirements
Student projects may include but are not limited to:
- Identify problems that are amenable to solution by AI methods, and which AI methods may be suited to solving a given problem
- Formalize a given problem in the language/framework of different AI methods
- Implement basic AI algorithms
- Apply basic AI knowledge and algorithms to solve problems
- Design simple software to experiment with various AI concepts and analyze results
Additional company criteria
Companies must answer the following questions to submit a match request to this experience:
A representative of the company will be available to answer questions from students in a timely manner for the duration of the project.
A representative of the company will be available for a pre-selection discussion with the administrator of the course to review the project scope.
The company will be able to share sample data with students for the development of algorithms.
Timeline
-
January 17, 2022Experience start
-
January 22, 2022Project Scope Meeting
-
February 19, 2022Mid-term review
-
March 26, 2022Experience end
Timeline
-
January 17, 2022Experience start
-
January 22, 2022Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
-
February 19, 2022Mid-term review
Students will review their progress with company and the course instructor.
-
March 26, 2022Experience end