University of Minnesota
CSci 5512: Artificial Intelligence II
CSci 5512 Syllabus

CSci 5512

Artificial Intelligence II

Fall 2021

Meeting time and place: Lecture (001): 9:45 A.M. - 11:00 A.M. Tuesday/Thursday Keller Hall 3-230.


The current plan is for all office hours to be done over zoom.
Name James Parker
Email jparker (at) cs (dot) umn (dot) edu
Office HoursPlease see "Office Hours" on the class homepage (below).
Class homepage

TAs: The TAs are primarily in charge of grading and office hours. Their names, contact information, and office hours are posted in the "Office Hours" page on the class homepage.

Text: Russel and Norvig, Artificial Intelligence A Modern Approach Pearson, 4rd edition. Older additions should also be fine. There may also be other resources linked to the class web page.

COVID-19, Face-Coverings, Symptoms, and Vaccination: The University of Minnesota currently requires all students, staff, and faculty to wear masks when indoors regardless of vaccination status. On August 24, 2021, the University launched a vaccine attestation process for faculty and staff, and on August 27, 2021, launched a vaccine requirement process for students - see the Get the Vax 2.0 initiative. Please stay at home if you experience symptoms of COVID-19 or have a positive COVID-19 test result and consult with your healthcare provider about an appropriate course of action. For COVID-19 excused absences, I will work with you to find the best course of action for missed work and/or class experiences. Please see bottom for additional details.

UNITE Additional Information: With uncertainty regarding COVID for Fall 2021 - and in order to reduce the possibility of students exposed to COVID or those who test positive for COVID from attending class meetings and potentially exposing other students, faculty and staff - both Live Streaming Video and same-day Streaming Video Archives of class meetings are available to students registered in the on-campus section of this course for the length of the semester. Additional information at the bottom.

Class Website: There are two websites associated with this course: canvas and a public cse website. Canvas is primarily used to submit homework, see grades and see announcements. The public cse webpage will have the schedule and any resources used in lecture. Please check the schedule frequently for any changes due to the pacing of the class. Important announcements will also be sent out through email (Labeled with "[CSci5512]" in the title).

Prerequisites: Before taking this course, you should have:

  • Basic knowledge of computer programming.
  • Knowledge of common data structures (graphs and trees).
  • Solid understanding of statistics (probabilities and random variables).
  • Solid understanding of mathematics (calculus, especially derivatives and integration).

General Course Description: This course covers Artificial Intelligence (AI) that deals with uncertainty or learning. We will cover: a brief review of uncertainty and probability, Bayesian networks, Markov models, decision trees/networks, neural networks and reinforcement learning.


For all graded work, please address any concerns within two weeks of receiving the grade. We will not change grades after two weeks. Here is the amount each of the items will contribute to your overall grade:

Homework (5 of them)                              50%
Midterm 1 (Thursday, Oct. 21)                     15%
Midterm 2 (Tuesday, Nov. 30)                      15%
Project (Wednesday, Dec. 22)                      20%

Course Content and Components:

  • Readings/Lecture: Approximately 30 pages from the textbook or other papers.
  • Homework: There will be 5 homework assignments (10% of the grade each). These may include some (pyton) programming. Late submissions are reduced by 15% for every day late (no credit after a week). Homework must be done individually.
  • Project: The project should involve one of the following: (1) conduct an experiment, (2) do a literature review or (3) prove theoretical results. I encourage you to pick a topic that is personally interesting to you. Artificial intelligence is a broad field and you can frame the topic of your choice in this way. If you wish to do the project in a group, you must first receive the instructor's consent.
  • Examinations: There will be two midterm exams (15% of the grade each). Dates for these are listed on the schedule. Exams are open book and notes. The exams will be conducted in class and will last the whole class period (1 hour and 15 minutes).

Grading for this course is on an absolute scale, so that the performance of others in the class will not negatively affect your grade. Final grades will be assigned based the following scale:

      93.0% -- 100.0%   A
      90.0% --  93.0%   A-
      87.0% --  90.0%   B+
      83.0% --  87.0%   B
      80.0% --  83.0%   B-
      77.0% --  80.0%   C+
      73.0% --  77.0%   C
      70.0% --  73.0%   C-
      67.0% --  70.0%   D+
      60.0% --  67.0%   D
       0%   --  60.0%   F
For S/N grading, a satisfactory grade (S) requires a weighted score of 70 or above.

Scholastic conduct: Homework and exams are individual assessments (unless explicitly stated otherwise). This means your discussions about the questions can only cover the general approaches necessary to solve the problem. You should never share your work or see another student's answer to any part of the problem. It is also not allowed to work so closely together that your answers appear very similar, even if nothing was ever explicitly shared. If you have any questions about what is and is not allowable in this class, please ask the course instructor.

Disability Accommodations: We desire to make learning rewarding and fun for all students and make every attempt to accommodate anyone who has a desire to learn. If you require special classroom or test-taking accommodations, you need to contact the University Disability Services and also notify the instructor as soon as possible at the start of the semester (no later than 3 weeks prior to the first examination).

COVID-19 Additional Information: People who are not vaccinated are at high risk for getting and spreading SARS-CoV-2, the virus that causes COVID-19. New variants of the virus spread more easily and quickly, particularly among young adults, which may lead to more cases of COVID-19 among college students this fall. An increase in the number of COVID-19 cases will strain healthcare resources and lead to more hospitalizations and potentially deaths. The best defenses against contracting COVID-19 and spreading the virus to others are vaccination and masking. On August 23, 2021, the U.S. Food and Drug Administration (FDA) fully approved the Pfizer COVID-19 vaccine. This means that the University of Minnesota requires students to be vaccinated for COVID-19 and students must complete this Student COVID-19 Immunization Vaccination Form by Oct. 8, 2021. Exemptions may be requested for religious or medical reasons. For resources about the vaccination and how to schedule an appointment, please refer to the University’s Get the Vax 2.0 initiative. When indoors, you are currently required to wear a face covering (mask) to protect the entire community of students, faculty members, and staff. Please wear your mask so that it covers both your nose and mouth. This will maintain a culture of safety to help protect all members of the community, and especially those who are immunocompromised and/or who are caretakers of others (e.g., young children) who are not yet vaccinated. Even though vaccinations are highly protective and required on campus, breakthrough infections do occur; therefore, indoor masking continues to be an important part of our layers of safeguard to keep the community safe and is one of our most important tools for ensuring sustained in-person learning. Both the CDC and MDH recommend that we ask ourselves every day if we have any COVID symptoms (including fever or chills, cough, shortness of breath or difficulty breathing, new loss of taste or smell, muscle aches or sore throat) and that if so we stay home and get tested, even if we're already vaccinated. I commit to doing my part to keep you and your colleagues safe by doing this, and I expect that you will too. If you experience COVID-19 symptoms or symptoms of any potentially infectious respiratory illness, you should stay home or in your residence hall room and not come to class or to campus. Please consult your healthcare provider about an appropriate course of action, and consult the M-test program for COVID testing resources. Absences related to COVID-19 symptoms, testing, or exposure, for yourself or your dependents, are excused absences and I will work with you to find the best course of action for missed work and course content. The above policies and guidelines are subject to change, since the University regularly updates pandemic guidelines in response to guidance from health professionals and in relation to the prevalence of the virus in our community.

UNITE Additional Information: - Access the Live Streaming Videos through the UNITE Media Portal with your University of Minnesota Internet I.D. and password (this is what you use to access your University of Minnesota email account); - Access the Streaming Video Archives through the UNITE Media Portal or within the Canvas course site for this course, typically available within an hour after the end of each class meeting; The University of Minnesota holds the copyright to this media - your access is strictly limited to your enrollment in this course. Accessing the media through either the UNITE Media Portal or within the Canvas course site obligates the student to the UNITE media agreement posted in both the UNITE Media Portal and the Canvas course site. Violation of the agreement will result in immediate loss of access to ALL UNITE media, with escalation of incident to the CSE Dean’s Office and the University Office of General Counsel. DO NOT ask the instructor or teaching assistants for technical or troubleshooting assistance with these streaming video archives – use the UNITE Troubleshooting FAQ or “Submit a Trouble Report to UNITE” link found on all pages within the UNITE Media Portal.

UNITE Technical FAQ:
UNITE Streaming Video Access for On-Campus Students:
UNITE Media Portal: