Topic 4 for me was the most fun topic among all other topics. During Topic 4, we had this opportunity to utilize the knowledge we learned in the other 3 topics. On the other hand, designing a course with team members with different academic backgrounds was a bit challenging. Since AI has received a great deal of attention, we decided to design an introductory course in AI.

 

However, since my academic background is in AI, it was a bit hard to think about the basic requirements and qualifications for an AI course. For me, even in the basic level AI course, the following qualifications need to be satisfied:

1. Programming skills: Python, Java, C++, or other programming languages commonly used in AI development.
2. Mathematics: AI relies heavily on mathematical concepts such as linear algebra, calculus, probability, and statistics.
3. Machine learning:  Understanding the principles of machine learning is essential for understanding how AI models work.
4. Data analysis: AI algorithms require large amounts of data to learn from. Therefore, the students need to have a good understanding of data analysis techniques.

However, during the course, we realized that to understand some basic ideas behind AI, the students are not required to have all the mentioned qualifications. Finally, during the group discussions that we had, I also realized that continuous learning is an important factor!

The students should be willing to continue learning and keep themselves updated with the latest trends in AI.