| (*)Students have advanced practical research skills in AI, including the ability to independently analyze, improve, and compare algorithms or solve theoretical AI problems. They have experience in handling real-world AI challenges, from algorithm implementation to data analysis, and learn how to effectively communicate their results through code, written reports, and presentations.
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(*)- Analyzing and Understanding AI Algorithms (k5)
Students are able to analyze and understand published AI algorithms, identifying their strengths, limitations, and areas for improvement.
- Implementing and Improving AI Models (k5)
Students can implement AI algorithms computationally, improve them by applying new techniques or optimizations, and test their performance on relevant datasets.
- Comparing and Evaluating AI Techniques (k5)
Students are capable of comparing different AI models or algorithms, using metrics and statistical methods to evaluate their performance in various scenarios.
- Solving Theoretical Problems in AI (k5)
Students are able to solve more theoretical AI problems mathematically, using logical reasoning and mathematical tools to explore AI concepts and models.
- Presenting Results and Writing Reports (k6)
Students can effectively communicate their findings, writing a comprehensive report that details their approach, results, and conclusions, as well as presenting their work to an audience.
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(*)Students acquire knowledge of advanced AI algorithms and methods, gaining a deeper understanding of their application, strengths, and limitations. They learn to solve real-world AI problems and present their research through written reports and presentations, while gaining hands-on experience in improving and evaluating existing algorithms.
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