Course Syllabus

Note: This course code has changed from CSE 150 to DS 150. You may occasionally see references to the old course code or title.


This course introduces students to how data is used to make decisions and communicate meaning through visualization. Students will also learn the underlying data summaries used in data visualizations (mean, standard deviation, percentiles). This course is worth two credits.

Program Message

This course will introduce students to data science and provide insight into how to use data to make decisions using visualization and statistical inference. Data scientists spend a significant amount of their time cleaning and manipulating data for use in decision making. In this course, we have crafted real-world data for use in our learning to offset much of the work around data cleaning and manipulation. CSE 250, CSE 350/Math 335, CIT 111, CIT 225 and other advanced analytics courses like CSE 450 and Math 488 can help students build those skills.

Students will learn the principles of data storage and management for data analysis and visualization through Google Sheets and Tableau. Neither tool requires the use of a programming language for their use in our class. Both are used heavily in the data science space, and they have many connections to R and Python.

If students sign up for this class, they are most likely driven by curiosity and interested in how data decisions are made (sometimes called data intuition). Possibly, the students will have a more empathetic approach to how the world works and how problems can be solved. Finally, students have an eye for visualization and how data is communicated to make impactful decisions. The course follows these principles of teaching Data Science:

  • Organize the course around a set of diverse case studies
  • Integrate computing into every aspect of the course
  • Teach abstraction, but minimize reliance on mathematical notation
  • Structure course activities to realistically mimic a data scientist’s experience
  • Demonstrate the importance of critical thinking/skepticism through examples



No prerequisites.

Required Resources

Required Resources
Resource Title/Description
(books, software, etc.)
Author/Provider Ed./Vol. 13-Digit ISBN (if applicable)
Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualization Berinato, Scott 1st


(maybe purchased on Amazon, used, for as low as $16.99)

DS 150: Data Intuition and Insight BYU-I Stats

Though other business visualization analytic tools other than Tableau could be used to accomplish assignments in this course, Tableau is specifically required as it is heavily used in the industry and therefore required in this course for assignments. 

Proctored Exams and Assessments

This course will use an online proctoring software called Proctorio. This makes it possible for students to take assessments and exams without a human proctor present. Proctored exams can be accessed like any other exam, once the software has been installed. Exams will be recorded by Proctorio and reviewed by the BYUI Testing Center. Any questionable exams will be forwarded to the instructor for further review.

For step-by-step instructions on Proctorio installation, please refer to this help guide article.


Course Outcomes (CO)

  1. Identify properly structured data for analytics and visualizations.
  2. Create visualizations and summary tables from data.
  3. Communicate with analytics and business professionals on data needs and results.
  4. Use statistical methods to make appropriate inferential conclusions with data.
  5. Describe the impact of data visualizations and summaries in the decision-making process.

Major Assignments

The table below is meant to help you see the relevance of each major assignment as it pertains to the course outcomes (CO).

Major Assignments
Major Assignment Description CO#
Case Study 1 Presentation on good and bad charts 3
Case Study 2 Presentation to sell a product 1, 2, 3
Case Study 3 Article comparing marathons 2, 3, 4
Case Study 4 Presentation visualizing child health 2, 3, 4
Case Study 5 Presentation on the Matthew Effect 2, 3, 4
Case Study 6 Presentation to IRS managers 2, 3, 4
Case Study 7 Presentation for the WHO 1, 2, 3, 4
Visualization Challenge 1, 2, 3, 4

Weekly Patterns

The table below displays typical weekly activities, due dates, and activity descriptions. You can also download an outline of all the reading assignments.

Weekly Patterns
Due Date* Learning Model Activity Title Description
Midweek Prepare Introduction Introduction to the week's content.
Midweek Prepare Overview: Case Study Case Study instructions
Midweek Prove Quiz: Case Study Self-assessment
End of Week Prepare Prepare: Reading Course material
End of Week Prove Quiz: Reading Quiz on course material
End of Week Teach One Another Peer Feedback: Case Study Posting in Slack 
Midweek Prepare Introduction Introduction to the week's content.
Midweek Prove Quiz: Visualization Quiz
End of Week Prepare Prepare: Reading Course material
End of Week Prove Quiz: Reading Quiz on course material
End of Week Prove Submission: Case Study Graded assessment

*Set your time zone within user preferences so the dates and times for course activities will display correctly for your time zone.

In odd-numbered weeks, instructors will be providing you feedback on submitted assignments. In even-numbered weeks, you can expect your instructor to spend time answering your case study questions and guiding you through the data visualization process.

Learning Model

DS 150 employs the principles of the BYU-I Learning Model by exploring the pursuit of truth. Students prepare by studying the course content, build discipleship by sharing thoughts on gospel insights, and teaching one another through sharing feedback and tips on Slack, and ponder and prove through the submission of case study reports and quizzes.



You can expect to receive grades and feedback within 7 days of the due date for all assignments.


Students should be spending six to nine hours on this course per week. Approximately half of that time will be used for reading and the reading quiz. The rest of the time varies between odd and even-week assignments.

Group Work

This course does not divide students into groups for assignments. However, you will need to work with a group in week 2 to record data. The instructor will create groups in Slack. You will be notified via Slack with your group details.

Late Work

As a sign of professionalism and respect, students should complete their work on time. 


Students can resubmit reading quizzes at any time during the semester for a better score. The Case Study quizzes and Case Study Feedback quizzes have multiple attempts, but lock at the due date since their purpose is to prepare students for the Case Study presentation. Case Study presentations can be resubmitted until the end of the semester for a better score.

Extra Credit

There is no extra credit is this course.

Grade Weights

This course has weighted grades according to the following chart:

Grade Weights
Activity Grade Weight
Case Studies 40%
Reading Quizzes 20%
Visualization Discussions 10%
Visualization Challenge 10%
Teach One Another Quizzes 10%
Case Study Quizzes 4%
Case Study Feedback 4%
Other Assignments 2%

Grading Scale

Grading Scale
Letter Grade Percent
A 100% - 93%
A- 92% - 90%
B+ 89% - 87%
B 86% - 83%
B- 82% - 80%
C+ 79% - 77%
C 76% - 73%
C- 72% - 70%
D+ 69% - 67%
D 66% - 63%
D- 62% - 60%
F 59% and lower

University Policies

Students with Disabilities

Brigham Young University-Idaho is committed to providing a working and learning atmosphere that accommodates qualified persons with disabilities. If the student has a disability and require accommodations, please contact the Disability Services Office at (208) 496-9210 or visit their website and follow the Steps for Receiving Accommodations. Reasonable academic accommodations are reviewed for all students who have qualified documented disabilities. Services are coordinated with students and instructors by the Disability Services Office.

This course may require synchronous meetings. If the student is currently registered with the Disability Services Office and needs an interpreter or transcriber for these meetings, please contact the deaf and hard of hearing coordinator at (208) 496-9219.

Disability Services Contact Information:

Other University Policies

Go to the Student Resources module to review the university policies regarding honesty, online etiquette, communication expectations, etc.

Course Summary:

Date Details Due