General information

The course Artificial Intelligence and Automation (AIA-101) is focused on four main topics:

• Linear regressors and classifiers
• Logistic classifiers
• Artificial neural networks (ANNs), and
• Control applications

The course requires previous concepts of programming, control, and microcontrollers. Additionally, it is highly recommended to use a GNU/Linux distribution to follow several videos and tutorials closely; the Ubuntu or Red Hat distributions are good choices for starting engineers.

Rules in the classroom and lab

• Each lecture or lab session starts on time, and students are not allowed to enter the classroom/lab after 10 minutes have passed.
• Taking pictures or recording the whiteboard is not allowed; -10 point in the current unit.
• Lab teams are generated randomly, and modifications are not allowed.
• To pass the course, students must pass at least 50% of the exams. The final grade is calculated based on 40% for theory and 60% for practical skills.
• During the regulation term, students can improve their grades. However, once grades are finalized, they cannot be returned to previous values.
• The students must type lab reports. If the student uses Internet information, the info must be appropriately referenced.
• The lab reports will be checked for plagiarism. If the report contains more than 30% similarity to other sources, the grade will be zero.
• The use of AI tools (such as ChatGPT, Copilot, or similar) is permitted only as support during code setup. However, students must be able to explain and justify their answers during the Question & Answer (Q&A) lab session. If it becomes evident that the student cannot explain their work or answer correctly. The final grade of the lab report may be significantly affected, including the possibility of receiving a zero.
• Grades for lab reports are determined based on the lab report rubric.