IS 603-01 Decision Making Support Systems (Fall 2024)

Information Systems Department
University of Maryland Baltimore County
Baltimore, Maryland 21250
Departmental Office: Room ITE 404, ph. 410-455-3206

Course Description

This course will provide an overview of data-driven decision-making via artificial intelligence (AI) and data science (DS) technologies. The emphasis is on how to use these technologies to solve real-world problems, rather than on the algorithmic or mathematical details of the methods. Students will obtain an understanding of both fundamental concepts and practical insights in data-analytic thinking, as well as a foundation for further study in AI and DS.

Student learning outcomes: By the end of this course, you will be able to:

Explain how artificial intelligence (AI) and data science (DS) technologies can help businesses and other organizations to leverage data to understand customers and make better decisions,
describe the data science process and the fundamental concepts underlying data-analytic methods,
formulate business problems as AI/DS problems,
outline several AI/DS techniques at a conceptual level,
discuss and address ethical issues that arise when performing data-driven decision making, and
make sensible choices regarding practical issues in the application and deployment of AI/DS technologies.

Lecture time and venue: Thursdays 4:30PM - 7:00PM Janet & Walter Sondheim Hall 109

Instructors: Dr. James Foulds and Dr. Shimei Pan
Instructor email: (jfoulds,shimei) [at] umbc [dot] edu.
Instructor office hours: Thursdays 3:30 - 4:30 pm, ITE 447 (Foulds) and ITE 434 (Pan). (Only the instructor giving the lesson will hold the office hour that week. Other times by appointment)

Teaching assistant: Mohammad Saeid Anwar
Teaching assistant email: wy71697 [at] umbc [dot] edu.
Teaching assistant office hours: Fridays 9 - 10 am, (Room TBD, also available on Blackboard Collaborate)

Poll Everywhere: Vote on in-class poll questions at PollEv.com/jamesfoulds863 (Dr. Foulds) and PollEv.com?/shimeipan431 (Dr. Pan) .

Prerequisites

None. This is a core course and does not require any background knowledge in data-driven decision-making.

Required Textbook

Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking, 1st Edition, by Foster Provost and Tom Fawcett is the course textbook. You will need this book for mandatory weekly readings.

Course Requirements and Grading

Homeworks 25% (5 of them, 6.25% each for your best 4 homeworks; the lowest score will be dropped)
Group projects 25%:

Proposal 5% (due 9/26/2024)
Mid-term report 5% (due 11/7/2024)
Group project poster 5% (presented in class 12/5/2024, digital copy of poster due)
Final report 10% (due Wed 12/18/2024, 11:59pm, on Blackboard)

Midterm exam 20% (take-home, 10/24/2024)
Final exam 20% (take home, 12/12/2024)
Poll participation 10%

The project will be done in groups of 3-4. Project proposals are to be submitted and approved by the deadline. All reports will be submitted on Blackboard, and only one member of each project group needs to submit them.

In this course, participation means more than just showing up. It also refers to contributing to everyone's learning, through active engagement in peer instruction exercises abd in-class discussions. Participation grades will be assessed as a percentage of peer instruction questions answered (correctly or not), with a 90% response rate being sufficient for full points.

With respect to final letter grades, UMBC's Catalog states that an A indicates "superior" achievement; B, "good" performance; C, "not satisfactory"; D, "unacceptable"; F, "failure." There is specifically no mention of any numerical scores associated with these letter grades. Below is how grades may be assigned based on your final points, accumulated over the semester. Grades will be assigned using a plus/minus system. It is university policy that A+, D+, and D- are not assigned. We do not grade on a curve, so that everyone in the class has the opportunity to succeed.

Final Grade	Letter Grade	Points when calculating GPA
91 - 100	A	4.0
89 - 90.99	A-	3.7
87 - 88.99	B+	3.3
81 – 86.99	B	3.0
79 - 80.99	B-	2.7
77 – 78.99	C+	2.3
71 – 76.99	C	2.0
69 - 70.99	C-	1.7
60 – 68.99	D	1.0
0 – 59.99	F	0.0

Homework and Exam Policies

Homeworks are due at the beginning of class on the dates specified. Late homeworks will not be accepted unless an extension is approved in advance. Requests for extensions must be made at least three days before the due date.
In the event of class cancellation due to inclement weather, any hard-copy paper assignment or test will be due in the next class meeting. Electronic submissions will still be due on the original due date.

Schedule

Lecture		Summary	Details	Assessment	Required reading
8/29/2024	Week 1 (JF and SP)	Course overview, Data-Analytic Thinking	Course overview, introduction to data-driven decision making and data-analytic thinking		Ch 1, or Dhar, V. (2013). "Data science and prediction". Communications of the ACM. 56 (12): 64–73.
9/5/2024	Week 2 (SP)	Business Problems and Data Science Solutions	Canonical data mining tasks, the data mining process, supervised vs unsupervised learning	HW1 out	Ch 2
9/12/2024	Week 3 (SP)	Introduction to Predictive Modeling	Models, induction, and prediction, finding correlations, attribute selection, tree induction		Ch 3
9/19/2024	Week 4 (SP)	Fitting a Model to Data	Finding “optimal” model parameters, choosing the goal for data mining, objective functions, loss functions, linear models. Sharing project ideas.	HW1 due, HW2 out. Project groups formed by this date	Ch 4
9/26/2024	Week 5 (SP)	Overfitting and its Avoidance	Generalization, fitting and overfitting, complexity control, regularization, hold-out method	Project proposal due	Ch 5
10/3/2024	Week 6 (SP)	Similarity, Neighbors, and Clusters	Calculating similarity, using similarity for prediction, nearest neighbors, clustering	HW2 due, HW3 out	Ch 6
10/10/2024	Week 7(SP)	What is a Good Model?	Evaluating machine learning methods, expected value framework, baselines, various evaluation metrics		Ch 7
10/17/2024	Week 8 (JF)	Visualizing Model Performance	Visualization of model performance under uncertainty, profit curves, cumulative response curves, lift curves, ROC curves	HW3 due, HW4 out	Ch 8
10/24/2024	Week 9	Midterm (take home)
10/31/2024	Week 10 (SP)	Data Science Ethics	Fairness/bias in AI, privacy, accountability, transparency	HW4 due, HW5 out	Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016). Machine bias. ProPublica, May, 23, 2016.
11/7/2024	Week 11 (JF)	Toward Analytical Engineering	Solving business problems with data science, designing solutions based on the data, tools, and techniques available	Project mid-term progress report due	Ch 11
11/14/2024	Week 12 (JF)	Other Data Science Tasks and Techniques	Co-occurrences and associations, link prediction, causal modeling	HW5 due	Ch 12
11/21/2024	Week 13 (JF)	Data Science and Business Strategy	Acquiring competitive advantage via data science, curating data science capability, overview, limits of data science, ethics, next steps		Ch 13 and Ch 14
11/28/2024	Week 14	Thanksgiving Holiday	No class
12/5/2024	Week 15 (JF and SP)	Group Project Presentations		Digital copies of posters due.
12/12/2024	Exam week			Take-home final exam (due 11:59pm Thurs 12/12/2024). Project final report due Wed 12/18/2024 (11:59pm)

The schedule may be subject to change. The summary and details columns are only a guideline of the content likely to be covered, and the dates on which material is covered may shift.

Instructional Methods

Traditional lectures will be augmented with active learning methods, primarily in the form of peer instruction exercises. Research has strongly indicated that active learning improves student outcomes in STEM fields versus traditional lecturing (Freeman et al., 2013). We will be using the Poll Everywhere service for polls and quizzes.

Pre-class reading assignments will be given for each lesson, which are very important for learning, and for making the best use of our limited time together (a partially "flipped classroom" approach). These readings are therefore required.

Software

WEKA

Academic Integrity

UMBC's policies on academic integrity will be strictly enforced (see the University System of Maryland's policy document, UMBC's academic integrity overview page, and the UMBC catalog). In particular, all of your work must be your own. Acknowledge and cite source material in your papers or assignments. While you may verbally discuss assignments with your peers, you may not copy or look at anyone else's written assignment work or code, or share your own solutions. Any exceptions will result in a zero on the assessment in question, and may lead to further disciplinary action. Some relevant excerpts from UMBC's policies, as linked to above, are:

"By enrolling in this course, each student assumes the responsibilities of an active participant in UMBC's scholarly community in which everyone's academic work and behavior are held to the highest standards of honesty. Cheating, fabrication, plagiarism, and helping others to commit these acts are all forms of academic dishonesty, and they are wrong." (UMBC's academic integrity overview)
"Students shall not submit as their own work any work which has been prepared by others." (USM policy document)
"Students shall refrain from acts of cheating and plagiarism or other acts of academic dishonesty." (USM policy document)
"Plagiarism means knowingly, or by carelessness or negligence, representing as one's own, in any academic exercise, the intellectual or creative work of someone else." (student academic conduct policy)
"Cheating means using or attempting to use unauthorized material, information, study aids, or another person’s work in any academic exercise" (student academic conduct policy)

Policy on ChatGPT and other Large Language Models (LLMs)

The use of language models such as ChatGPT for assignments will be strictly regulated. Your work must be your own. While language models can be lightly used as a writing aid, their use must be limited to a small part of any solution and they must not contribute to the substance of your answer. Any use of these tools as a writing aid must be declared in your submission, with an explanation of why the work is your own and why the use does not constitute plagiarism. You must also submit a log of all queries used in your submission. If you have any questions, please check with us.

Diversity Statement on Respect

Students in this class are encouraged to speak up and participate during our meetings. Because the class will represent a diversity of individual beliefs, backgrounds, and experiences, every member of this class must show respect for every other member of this class. (Statement from California State University, Chico’s Office of Diversity and Inclusion).

Accessibility and Disability Accommodations, Guidance and Resources

Accommodations for students with disabilities are provided for all students with a qualified disability under the Americans with Disabilities Act (ADA & ADAAA) and Section 504 of the Rehabilitation Act who request and are eligible for accommodations. The Office of Student Disability Services (SDS) is the UMBC department designated to coordinate accommodations that would create equal access for students when barriers to participation exist in University courses, programs, or activities.

If you have a documented disability and need to request academic accommodations in your courses, please refer to the SDS website at sds.umbc.edu for registration information and office procedures.

SDS email: disAbility@umbc.edu
SDS phone: (410) 455-2459

If you will be using SDS approved accommodations in this class, please contact me (instructor) to discuss implementation of the accommodations. During remote instruction requirements due to COVID, communication and flexibility will be essential for success.

Counseling Center

Diminished mental health can interfere with optimal academic performance. The source of symptoms might be related to your course work; if so, please speak with me. However, problems with other parts of your life can also contribute to decreased academic performance. UMBC provides cost-free and confidential mental health services through the Counseling Center to help you manage personal challenges that threaten your personal or academic well-being.

Remember, getting help is a smart and courageous thing to do -- for yourself and for those who care about you. For more resources get the Just in Case mental health resources Mobile and Web App. This app can be accessed by clicking: counseling.umbc.edu/justincase.

The UMBC Counseling Center is in the Student Development & Success Center (between Chesapeake and Susquehanna Halls). Phone: 410-455-2472. Hours: Monday-Friday 8:30am-5:00pm.

Family Educational Rights and Privacy Act (FERPA) Notice

Please note that as per federal law we are unable to discuss grades over email. If you wish to discuss grades, please come to office hours.

Sexual Assault, Sexual Harassment, and Gender Based Violence and Discrimination

UMBC Policy in addition to federal and state law (to include Title IX) prohibits discrimination and harassment on the basis of sex, sexual orientation, and gender identity in University programs and activities. Any student who is impacted by sexual harassment, sexual assault, domestic violence, dating violence, stalking, sexual exploitation, gender discrimination, pregnancy discrimination, gender-based harassment, or related retaliation should contact the University’s Title IX Coordinator to make a report and/or access support and resources. The Title IX Coordinator can be reached at titleixcoordinator@umbc.edu or 410-455-1717.

You can access support and resources even if you do not want to take any further action. You will not be forced to file a formal complaint or police report. Please be aware that the University may take action on its own if essential to protect the safety of the community. If you are interested in making a report, please use the Online Reporting/Referral Form . Please note that, if you report anonymously, the University’s ability to respond will be limited.

Notice that Faculty are Responsible Employees with Mandatory Reporting Obligations:

All faculty members are considered Responsible Employees, per UMBC’s Policy on Sexual Misconduct, Sexual Harassment, and Gender Discrimination. Faculty and teaching assistants therefore required to report all known information regarding alleged conduct that may be a violation of the Policy to the Title IX Coordinator, even if a student discloses an experience that occurred before attending UMBC and/or an incident that only involves people not affiliated with UMBC. Reports are required regardless of the amount of detail provided and even in instances where support has already been offered or received.

While faculty members want to encourage you to share information related to your life experiences through discussion and written work, students should understand that faculty are required to report past and present sexual harassment, sexual assault, domestic and dating violence, stalking, and gender discrimination that is shared with them to the Title IX Coordinator so that the University can inform students of their rights, resources, and support. While you are encouraged to do so, you are not obligated to respond to outreach conducted as a result of a report to the Title IX Coordinator.

If you need to speak with someone in confidence, who does not have an obligation to report to the Title IX Coordinator, UMBC has a number of Confidential Resources available to support you:

Retriever Integrated Health (Main Campus): 410-455-2472; Monday – Friday 8:30 a.m. – 5 p.m.; For After-Hours Support, Call 988.
Center for Counseling and Well-Being (Shady Grove Campus): 301-738-6273; Monday-Thursday 10:00a.m. – 7:00 p.m. and Friday 10:00 a.m. – 2:00 p.m. (virtual) Online Appointment Request Form
Pastoral Counseling via The Gathering Space for Spiritual Well-Being: 410-455-6795; i3b@umbc.edu; Monday – Friday 8:00 a.m. – 10:00 p.m.

Other Resources:

Women’s Center (for students of all genders): 410-455-2714; womenscenter@umbc.edu; Monday – Thursday 9:30 a.m. – 5:00 p.m. and Friday 10:00 a.m. – 4 p.m.
Shady Grove Student Resources, Maryland Resources, National Resources.

Child Abuse and Neglect:

Please note that Maryland law and UMBC policy require that faculty report all disclosures or suspicions of child abuse or neglect to the Department of Social Services and/or the police even if the person who experienced the abuse or neglect is now over 18.

Pregnant and Parenting Students

UMBC’s Policy on Sexual Misconduct, Sexual Harassment and Gender Discrimination expressly prohibits all forms of discrimination and harassment on the basis of sex, including pregnancy. Resources for pregnant, parenting and breastfeeding students are available through the University’s Office of Equity and Civil Rights. Pregnant and parenting students are encouraged to contact the Title IX Coordinator to discuss plans and ensure ongoing access to their academic program with respect to a leave of absence – returning following leave, or any other accommodation that may be needed related to pregnancy, childbirth, adoption, breastfeeding, and/or the early months of parenting.

In addition, students who are pregnant and have an impairment related to their pregnancy that qualifies as disability under the ADA may be entitled to accommodations through the Office of Student Disability Services.

Religious Observances & Accommodations

Policy

Hate, Bias, Discrimination and Harassment

UMBC values safety, cultural and ethnic diversity, social responsibility, lifelong learning, equity, and civic engagement.

Consistent with these principles, UMBC Policy prohibits discrimination and harassment in its educational programs and activities or with respect to employment terms and conditions based on race, creed, color, religion, sex, gender, pregnancy, ancestry, age, gender identity or expression, national origin, veterans status, marital status, sexual orientation, physical or mental disability, or genetic information.

Students (and faculty and staff) who experience discrimination, harassment, hate, or bias based upon a protected status or who have such matters reported to them should use the online reporting/referral form to report discrimination, hate, or bias incidents. You may report incidents that happen to you anonymously. Please note that, if you report anonymously, the University’s ability to respond may be limited.

Campus Resources

Career Center's resources for diverse populations (including student organizations): http://careers.umbc.edu/students/resources/diverse/
Resources for LGBTQIA+ students: osl.umbc.edu/lgbtq/community_resources/
Office of International Education Services (IES): ies.umbc.edu/
Information regarding recent executive actions: ies.umbc.edu/executive-actions/
Wellness Initiative: wellness.umbc.edu/
Retriever Integrated Health: health.umbc.edu/
Women's Center: womenscenter.umbc.edu/
Center for Women in Technology (CWIT): cwit.umbc.edu/
Women Involved in Learning and Leadership (WILL) Program: gwst.umbc.edu/will/
Sexual assault and relationship violence on-campus resources: womenscenter.umbc.edu/sexual-assault-and-relationship-violence-response-team-and-umbcs-voices-against-violence/
Sexual misconduct policies and procedures (including filing a complaint): ecr.umbc.edu/policies-and-procedures/
Office of Student Disability Services: sds.umbc.edu/
Academic Center for Student Athletes: umbcretrievers.com/sports/2021/8/26/information-facilities-acsa-index.aspx
Veteran Services veterans.umbc.edu/
The Gathering Space for Spiritual Well-Being i3b.umbc.edu/spaces/the-gathering-space-for-spiritual-well-being/
Graduate Student Association: gsa.umbc.edu/
Graduate Student Association Writing Advisor: gsa.umbc.edu/writing-advisor/

Retriever Essentials - Free Food & Essentials for Everyone in the UMBC Community!

Retriever Essentials is a faculty, staff, and student-led partnership that promotes food access in the UMBC community. We offer FREE groceries, toiletries, baby items, and meal swipes, and have opportunities to engage and volunteer:

Pick up items from our free store The Essential Space located in RAC 235
Receive fresh food every Thursday 2:15-2:45pm @ the Library (email or see IG for exact location)
Stop by one of our Food Zones to pick up a pre-assembled bag of non-perishable food items and personal care products
Pick up snacks and food from our Free Corner Stores at the Campus Police Station or Library Atrium
Email us at retrieveressentials@umbc.edu if you need free meal swipes
To donate food, see instructions here!

Also email us if you would like to join our team or volunteer with us!