The focus is on Artificial Intelligence with AI concepts, AI areas, AI techniques, AI algorithms, and applying these to AI problems.
Learning Objectives
For grade E, the student must be able to:
- describe Artificial Intelligence (AI) and its applications
- describe AI concepts
- describe and apply AI areas
- describe and apply AI techniques
- describe and apply AI algorithms and AI methods
- implement AI techniques and AI algorithms to solve limited problems
- in cooperation with another student devise and solve a sophisticated but well-delimited problem, involving an AI area, an AI technique, and AI algorithm and an AI method
- reflect on others AI material as well as own produced material.
For a higher grade, the student must furthermore be able to create a detailed description of an individual solution to a sophisticated problem, by applying an AI technique, motivate the choice of AI area, and compare the selected area and technique with other existing, related AI methods and AI techniques. These skills must be demonstrated via a written exam.
To learn the different AI areas the course is divided into modules with lectures, tasks, assignment, seminars, laboratories, and quizzes.
Lectures
Most of the lectures will be given physically. Please check the calendar for each lecture to make sure that these are given either in Electrum, Kista or online via Zoom. The lectures are not mandatory but they provide vital information that is useful for the tasks, labs, and assignments.
Commonly lectures are not recorded! However, when recorded lectures, these will be available via Canvas.
The lectures present the following topics:
- Introduction to AI and its applications, vision, and future
- Searching, planning, and scheduling
- Intelligent rules-based systems, Decision-support systems, expert systems, and knowledge-based systems including reasoning strategies and heuristics, software development
- Software agents, intelligent agents, and multi-agent systems
- Machine learning
- Neural networks and deep learning
- Natural language processing
Tasks (Pass / Fail)
For each AI topic, see lectures above, there is a task of writing a short description of the AI area and providing five questions together with answers.
Peer-review (Pass / Fail)
For the AI topics, peer-reviews of the other students' descriptions of the AI area will be made after the descriptions have been handed in.
Seminars
The seminars follow the lectures. During the seminars, the current AI area is discussed with techniques and problems. Also, the questions and answers, that the students have provided for the task of the AI area, are discussed. The lectures, seminars with questions, answers, and tasks shall prepare the students for the quizzes. For tasks and quizzes, see below. The seminars are not mandatory but they provide answers to questions that the students may have about the areas, tasks, and the main assignment.
Laboratories (Pass / Fail)
The laboratory consists of practical programming tasks. These tasks are for imparting theoretical knowledge.
Quizzes (Pass / Fail)
Online quizzes are provided for each topic. The quizzes contain:
1) closed-questions with answer alternatives and
2) open questions.
The open question can only be answered after the closed questions are correctly answered. The number of tests for the 1) closed questions with answer alternatives is unlimited whereas the 2) the open question can only be answered once.
- Correct answers on both quizzes lead to a pass on this part.
- A failure in any of the quizzes leads to fail on this part and requires to retake this part during the written exam.*)
*) To clarify this part: the written exam includes one part where questions about the different AI topics are asked (that is the AI topics presented during the course), see the topics in the lecture section above.
The student only needs to take the questions for the AI topics that failed during the course. When this is done, the student will receive the grade E. However, to get a higher grade the second part of the written exam must be taken, for more information see the written exam below.
Main project
Course participants will undertake a main project, performed in groups of two students. In the main project, the students must choose an AI area, and implement a solution using an AI technique. The project must be novel, and either different from any existing work or significantly extending an existing work.
The project is presented at a seminar at the end of the course. At that time, the students give an oral presentation (with slides), and demonstrate the execution of a working prototype. Consequently, the prototype must work, and must give results that are reasonable and expected.
In case the presentation or demonstration fails, the students will have two weeks to improve the prototype, after which time the students give an improved presentation and demonstration. Further improvements have, up to now, never been necessary.
Written Exam (A-F)
The written exam includes two parts:
- the first part with all the AI topics that are presented during the course, see lectures above. The part is graded with a pass or fail and gives an E on the written exam. Observe that this part only needs to be taken, if and only if, any, some, or all of the quizzes for the different AI tasks failed. The students only take the questions that correspond to the failed quizzes.
- the second part is about an AI problem to be solved. The solution is to provide and, in detail, describe the select AI technique and tool(s), that must be correct for solving the particular AI problem.
Grading
Main Project (INL1), 4 credits, mandatory
Examination (TEN1), 3.5 credits, including the following (for E=mandatory and Higher grade):
- Assignments (marked pass or fail), mandatory
- Lab work (marked pass or fail), mandatory
- Peer-review (marked pass or fail), mandatory
- On-line quizzes (marked pass or fail), mandatory
- Optional written exam for a higher grade than E (marked fail/E, D, C, B, or A)
All mandatory parts must be passed for a final grade. A student that has passed all mandatory parts, but not the optional written exam, will get grade E.
CHATGPT or other GPTs
Under no circumstance is CHATGPT or other GPTs allowed during this AI course. If students are asked to compare with the outcome of CHATGPT or another GPT, they will get this assignment under the tasks. Otherwise, the use of CHATGPT or other GPTs will be considered cheating and/or misleadning and will be reported.
