COMP3308/COMP3608 Artificial Intelligence
Week 13 Tutorial exercises Revision and Preparation for the Exam
I. Unit of study survey
Please complete the unit of study evaluation survey. We really, really need you to do this – important decisions are based on your scores and comments:
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• The survey is part of the faculty teaching quality process – we have a minimum standard based on your scores. Courses with low scores are investigated by the Head of School and courses with high scores are commended.
• There is also a requirement for a minimum response rate, so please complete the survey!
• We put a lot of effort in this course and would like to know what you think about it. In particular:
• We prepared a lot of resources – detailed lecture slides with examples, tutorial exercises with solutions, additional practice questions for the exam. Do not take this for granted – it is not done in all courses.
• We hope you found the assessment tasks appropriate, interesting and worth doing. We certainly did writing them.
• There were big changes this semester – new assignments and moving the assignments to Grok. Everything had to be prepared from scratch as the requirements are different.
• Do you think we were responsive to your questions and feedback? Did we answer your questions well? (on Ed, during the tutorials, by email, etc.) How useful was the feedback that we provided to you? (e.g. on the assessment tasks, Ed, during the tutorials)
In summary, we would like to know what was beneficial for you in this course and what was not, what went well and what didn’t.
The survey is anonymous. To complete it:
1) click on: https://student-surveys.sydney.edu.au/students/ 2) fill in your Unikey details
3) complete the survey and remember to press “Submit” Thank you for doing this!
II. Tutorial questions
Go to Canvas/sample-exam-and-practice-questions and download 2 documents: 1) Sample exam questions
2) Bayesian Network Practice Questions (prepared by Broom)
There is another document with excellent questions on search (prepared by Broom) Weeks_2-3_Practice – please review it at home, in preparation for the exam.
1. We will start with Question 1, part 1a) from the Bayesian Network document: inference in Bayesian networks using enumeration.
Note: Do the rest of these questions at home – they are long but very educational.
2. Now we will continue with the questions from the Sample Exam Questions document. At the lecture we did Questions 1, 2, 4, 8 and 9. Start with Question 3 (minimax and alpha-beta) and do the remaining questions:
COMP3308/3608 Artificial Intelligence, s1 2022
Question 1 Search (lecture)
Question 2 Search (lecture)
Question 3 Minimax and alpha-beta (tutorial) Question 4 ML-short answers (lecture)
Question 5 Mashrooms (classification) (tutorial) Question 6 1R (tutorial)
Question 7 Clustering (tutorial)
Question 8 Backpropagation (lecture)
Question 9 K-Nearest Neighbor (lecture)
If you prefer another order, please tell your tutor.
What were the most difficult topics this semester? Do you have any questions? Ask your tutor!
We hope that you found this course useful. Use your AI knowledge and skills – there are so many applications – almost everywhere! There are already some great success stories, but there will be many more in the future – you can be part of them – you can contribute to them or lead them!
Best wishes from all of us – the whole teaching team: Christopher, Nick, James, Danielle, Shelley, Stephen, Cameron, Vincent and Irena.
COMP3308/3608 Artificial Intelligence, s1 2022
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