(*)- Analyzing and Understanding Practical AI Problems (k4)
Students can comprehend and break down current practical AI problems or challenges and determine appropriate methods for computational or mathematical solutions.
- Implementing and Testing Published AI Algorithms (k4)
Students are able to implement published AI algorithms, improve upon their structure or performance, and test them against specific datasets or problems.
- Conducting Comparative Analysis of AI Approaches (k5)
Students can compare and critically evaluate the results of various AI approaches, algorithms, or models, drawing conclusions about their effectiveness and limitations in different contexts.
- Synthesizing and Presenting Research Findings (k6)
Students are able to effectively present their research progress and results through oral presentations, clear coding practices, and detailed written reports summarizing their methodology, findings, and conclusions.
- Documenting and Communicating Technical Work (k5)
Students can comprehensively document their source code, data analyses, and results in a written format that accurately reflects the research process, ensuring reproducibility and clarity for others.
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(*)Students possess practical knowledge of current AI problems and techniques for addressing them, including understanding and implementing published algorithms and applying computational or mathematical approaches. They are also familiar with best practices for analyzing, improving, testing AI solutions, and effectively communicating and documenting research findings through reports and presentations.
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