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Instructor Brian ZaharatosÌý

Course DescriptionÌý

In the final course of the statistical modeling for data science program, learners will study a broad set of more advanced statistical modeling tools. Such tools will include generalized linear models (GLMs), which will provide an introduction to classification (through logistic regression); nonparametric modeling, including kernel estimators, smoothing splines; and semi-parametric generalized additive models (GAMs). Emphasis will be placed on a firm conceptual understanding of these tools. Attention will also be given to ethical issues raised by using complicated statistical models.ÌýÌý

MS-DS Program Learning OutcomesÌý

Successful completion of this course demonstrate your achievement of the following learning outcomes for the MS-DS program:Ìý

• Acquire, clean, wrangle, and manage data.Ìý

• Correctly perform exploratory data analyses in order to assist with the generation of scientific hypotheses.Ìý

• Apply principles and methods of probability theory and statistics to draw rational conclusions from data.Ìý

• Construct an appropriate statistical model in order to answer important scientific or business-related questions.Ìý

• Assess the validity of a statistical model when applied to a particular dataset.Ìý

• Be sensitive to ethical issues that are involved in dealing with data science applications arising in real world situations.Ìý

• Clearly communicate the results of a data science analysis to a non-technical audience.Ìý

• Use peer feedback, self-reflection and video analysis to improve collaboration skills.Ìý

• Create reproducible statistical workflows.Ìý

• Act ethically in the role of professional data scientist.ÌýÌý

Drops, Tuition Refunds, and WithdrawalsÌý

Because the MS-DS has flexible course start dates, all drops, tuition refunds, withdrawals and grades are handled at the individual course level. It is the student’s responsibility to monitor these deadlines. Coursera and Â鶹Ãâ·Ñ°æÏÂÔØBoulder are not responsible for notifying the students of these deadlines. For approximate session timelines, access the Boulder MS-DS Onboarding Course via the MS-DS degree homepage. To drop or withdraw from a course please complete the appropriate form on the Â鶹Ãâ·Ñ°æÏÂÔØBoulder Office of the Registrar website.ÌýÌý

Drops and RefundsÌý

Program PoliciesÌý

Suspected Violations of AI Tool Usage PolicyÌý

If program staff suspects you may have used AI tools to complete assignments in ways not explicitly authorized or suspect other violations of the honor code, they will contact you via email. Be sure to respond promptly to any related communication so your perspective is included in the case review. Failure to respond timely will not prevent the completion of a case review.ÌýÌý

In suspected cases of unauthorized AI tool usage, the program may:Ìý

• Request the documentation noted above (see AI Usage Documentation Guidelines) or other supplementary materialsÌý

• Issue a warningÌý

• Assign a 0–50% grade for the questionÌý

• Assign a 0–50% grade for the assignmentÌý

• Assign an F grade for the courseÌýÌý

• Reference prior violationsÌý

• Remove access to the course, related materials, and toolsÌý

• Contact the Office of Student Conduct & Conflict Resolution to report suspected Honor Code violationsÌý

Turnitin and similar AI detection tools may be used in these courses for initial detection of possible honor code violations. All suspected violations will be reviewed by a human. AI tools alone will not be used to determine if an assignment is plagiarized, and results from these tools will not be used alone as evidence to penalize students.Ìý

University PoliciesÌý

Accommodation for DisabilitiesÌý

If you qualify for accommodations because of a disability, please submit your accommodation letter from Disability Services to your faculty member in a timely manner so that your needs can be addressed. Disability Services determines accommodations based on documented disabilities in the academic environment. Information on requesting accommodations is located on the Disability Services website. Contact Disability Services at 303-492-8671 or dsinfo@colorado.edu for further assistance. If you have a temporary medical condition, see on the Disability Services website.Ìý

Classroom BehaviorÌý

Students and faculty each have responsibility for maintaining an appropriate learning environment. Those who fail to adhere to such behavioral standards may be subject to discipline. Professional courtesy and sensitivity are especially important with respect to individuals and topics dealing with race, color, national origin, sex, pregnancy, age, disability, creed, religion, sexual orientation, gender identity, gender expression, veteran status, political affiliation or political philosophy. Class rosters are provided to the instructor with the student's legal name. We will gladly honor your request to address you by an alternate name or gender pronoun. Please advise us of this preference early in the semester so that we may make appropriate changes to my records. For more information, see the policies on and the .Ìý

Honor CodeÌý

The Â鶹Ãâ·Ñ°æÏÂÔØ takes issues of academic dishonesty extremely seriously.ÌýÌý