Time and Location: MWF 1:30-2:20 PM, CSE2 G10

Canvas: Used for gradebook, Panopto and Zoom links

Ed Discussion: Used for announcements, questions, course discussion, reaching the staff

Gradescope: Used for assignment submission

Lecture slides are posted here prior to lecture.

Schedule and Meeting Policies
Lecture for this course is Monday, Wednesday, and Friday, 1:30-2:20pm. Students are strongly encouraged to attend in person. However, lectures will be recorded and available via Panopto on Canvas. Students who are feeling unwell are asked to stay home and review the recorded material.
Office hours will be frequent and posted via the schedule tab of this webpage. Any necessary Zoom links will be available via Canvas. Schedule updates, modifications, and details will be available via the schedule tab of this webpage.
Textbook
The strongly recommended text book for this course is Artificial Intelligence: A Modern Approach, by Stuart Russell & Peter Norvig, Prentice-Hall, 4th (or 3rd) Edition (2020) [R&N]. Regular reading assignments from this text will be recommended. PDF of 3rd edition. Another useful resource is Richard Sutton & Andrew Barto, Reinforcement Learning: An Introduction Second Edition, MIT Press. 2018 (limited chapters freely available online) [S&B].

Assignments and Grading

• 40%: 4 Written Homeworks

  • 10% per homework

• 40%: 4 Programming Projects

  • 10% per project

• 20%: 3 In-Class Quizzes

  • 6.67% per quiz

The final overall percentage (after weighting) will then be converted to a 4.0 scale. There will be no curve. Any extra credit points earned are added as points to the final overall percentage. Overall percentage scores will be translated into course grades as described in the following table (though the precise scale may be adjusted very slightly depending on the final distribution). Grades for scores below 60% will be determined by the instructors on a case-by-case basis. (In particular, we reserve the right to pass students whose percentages would fall below 2.0 if we continued the table above.)

97.5%: 4.0  

95.5%: 3.9  

93.5%: 3.8  

91.5%: 3.7  

89.5%: 3.6  

87.5%: 3.5  

85.5%: 3.4  

83.5%: 3.3  

81.5%: 3.2  

79.5%: 3.1  

77.5%: 3.0  

75.5%: 2.9  

73.5%: 2.8  

71.5%: 2.7  

69.5%: 2.6  

67.5%: 2.5  

65.5%: 2.4  

63.5%: 2.3

61.5%: 2.2  

Deadlines, late days, and regrades

Deadlines are primarily there to help the class run smoothly, such as turning in assignments and project deliverables on time. However, at times things are not in our control. To account for that we provide you with 8 late days that can be used at your discretion for any homework or programming project. A maximum of 4 late days can be used for any 1 assignment. Weekends count as 1 day, so if an assignment is due on 11:59pm on Friday, it can be extended to 11:59pm on Sunday with one late day. After exhausting your late days, each submission will lose 25% credit for every extra day it is late. A Regrade can be requested up to 2 days after the graded assignment was first returned to you. After that, no regrades will be possible.

Programming in Python

We will use Python for the programming projects. Python is a powerful general-purpose programming language with excellent libraries. Project 0 will provide a brief jump-start into working in Python.

Here are some Python related resources:

• www.learnpython.org "Whether you are an experienced programmer or not, this website is intended for everyone who wishes to learn the Python programming language."

• Python online tutorial

Plagiarism, Collaboration, and use of ChatGPT (or any other LLM)

Plagiarism and Collaboration: Course assignments are designed to teach material through independent application of concepts and algorithms learned in class. Towards this effort, we have a strict collaboration policy. Students are encouraged to talk through concepts with each other, but all code must be your own! You should not be looking at anyone else's code when completing your assignments. We will run all assignments through plagiarism software. Additionally, you may use online resources to understand concepts, but not to directly complete the written or coding portions of your assignments. This includes Stack Overflow and ChatGPT. 

ChatGPT, like a personalized tutor, is a valuable resource to learn the material of this course. You are strongly encouraged to use it to clarify any questions you may have or learn about related concepts discussed in class. It is also very helpful for unfamiliar syntax--how do I swap two dimensions of this array? However, appropriate use of ChatGPT is no different than how you should treat your fellow students under the collaboration policy. You can use ChatGPT to help work through problems, but you cannot ask it to do the problem for you. You can ask how to accomplish some coding operation (e.g., syntax) but you cannot ask it to implement, for example, Minimax Search, and copy and paste the solution. Emphasizing the guidance of above: if you ever find yourself copy-and-pasting anything from anywhere, you have very likely violated the collaboration policy. We will compare all student solutions to ChatGPT generated solutions. If we detect plagiarism in your assignments, you will get a 0 on the assignment and will be reported to the university. **It is much better to turn in an incomplete assignment than to turn in code that is not your own!**

Course Conduct

Diversity and respectful conduct: This course welcomes all students of all backgrounds. The computer science and computer engineering industries have a significant lack of diversity. This is due to a lack of sufficient past efforts by the field toward even greater diversity, equity, and inclusion. The Allen School seeks to create a more diverse, inclusive, and equitable environment for our community and our field. You should expect and demand to be treated by your classmates and course staff with respect. If any incident occurs that challenges this commitment to a supportive, diverse, inclusive, and equitable environment, please let me know so the issue can be addressed.

Accommodations

Disability, Religious, and Family Accommodations: If you have any questions about disability or religious accommodations, please refer to university policies regarding disability accommodations or religious accommodations. Feel free to also contact me (Jeff) for any reason.

Anonymous Feedback

If you have any additional feedback you would like to share, please use this anonymous feedback form.