GSU Robinson College of Business

MBA 8020 (Data Visualization) *Citizen Data Scientist Track*

Fall 2023 Updated on Aug 14, 2023

Course Description

The Data Visualization course aims to equip students with the skills and knowledge to effectively represent complex data in a visually intuitive manner. The course covers a range of topics from foundational elements of data visualization to advanced techniques and tools. Students will engage in hands-on activities and a final group project to apply these techniques to real-world data sets.

Learning Objectives

By the end of the course, students should be able to:

  • Understand the fundamentals of data visualization, including data taxonomy and basic data manipulation in Python.
  • Distinguish between different types of data visualizations such as scalar and vector field visualizations.
  • Apply interactive visualization techniques to large-scale data sets.
  • Evaluate the perceptual issues in data visualization and their impact on the effectiveness of visual representations.
  • Utilize specialized tools and frameworks for creating advanced visualizations.
  • Create narrative visualizations that effectively communicate data stories.
  • Understand the ethical considerations in data visualization.


  • Paczkowski, Walter R. Business Analytics: Data Science for Business Problems. Springer Nature, 2022.
  • Wes McKinney Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter. O’Reilly Media, 2022. Available here

Note: This course does not require the purchase of a textbook.

Weekly Schedule

Date Week Number Location Main Topic Subtopics
10/12 Week 1 Online Course Introduction Overview, Syllabus Review, Introduction to Matplotlib
10/19 Week 2 In-person Foundations of Data Visualization Data Taxonomy, Data Manipulation in Python, Scalar Field Visualization
10/26 Week 3 In-person Python for Data Visualization Data Manipulation Continued, Vector Field Visualization
11/02 Week 4 Online Interactive Visualizations Introduction to Interactive Visualization, Large-Scale Data Visualization
11/09 Week 5 In-person Advanced Interactive Visualizations Narrative Visualization, Perceptual Issues in Visualization
11/16 Week 6 In-person Specialized Tools and Frameworks Tools, Graph Visualization, Geospatial Visualization
11/30 Week 7 Online Final Project Presentations Presentation of Final Projects

General Topics Covered

  • Data Taxonomy and Basic Data Manipulation in Python
  • Scalar Field Visualization
  • Vector Field Visualization
  • Large-Scale Data Visualization
  • Interactive Visualization
  • Narrative Visualization
  • Perceptual Issues in Visualization
  • Specialized Tools for Data Visualization
  • Graph Visualization
  • Geospatial Visualization


Assignment Due Date Week Aligned With
Reading Reflection 1 Due 10/25 (before Week 3 starts) Week 2
Reading Reflection 2 Due 11/08 (before Week 5 starts) Week 4
Quiz & Make-up Quiz From 11/10 to 11/14 (noon) Week 5
Final Group Project Due 11/30 (Week 7) Week 7
Bonus: Reading 3 Due 12/02

The weekly schedule and deadlines are tenative and subject to change. Please check the updates on iCollege.

Grading Policy

Letter Grade Breakdown

A+ (97-100+) B+ (87–89.4) C+ (77–79.4) D (59–69.4)
A (91–96.9) B (83–86.9) C (72–76.9) F (0–59.9)
A- (89.5–90.9) B- (79.5 –82.9) C- (69.5 –71.9)

Points Breakdown

Points Assignment
15 Reading Reflection 1
25 Reading Reflection 2
15 Quiz
35 Final Group Project
10 Participation & Discussions
5 Bonus: Reading Reflection 3

Campus Safety

Georgia State University values the safety of all university community members on all of our campuses. To promote campus safety, the university is providing the LiveSafe app free for all students, faculty, and staff. This app provides a quick, convenient, and discrete way to communicate with the GSU police. I strongly recommend that you download the app from either the Apple App Store or Google Play. You can sign-up for Panther Alerts and learn more about LiveSafe by visiting the GSU LiveSafe webpage:

In addition, please make sure you have the campus police numbers in your phone.

  • For emergencies call 404-413-3333
  • For non-emergencies and to request a safety escort call 404-413-2100
  • If you are hearing impaired call 404-413-3203

Accommodations for Students with Disabilities

Students who wish to request accommodation for a disability may do so by registering with the Access and Accommodation Center. Students may only be accommodated upon issuance by the Access and Accommodation Center of a signed Accommodation Plan and are responsible for providing a copy of that plan to instructors of all classes in which accommodations are sought. Please note that accommodations are not retroactive and that students with accommodation plans should provide those to instructors at the beginning of each term.

Course Policies


Students are expected to attend all in-person and online classes to gain the full benefit of the course. However, missing one class without explanation is accepted for this course. If you are unable to attend a class, you need to study the materials of the class you missed and engage more in discussions in future classes. If you miss more than one class, you should explain the reason for your absence in the form at

Make-up Quizzes

The lowest quiz grade will be dropped. If you miss a quiz, that will be considered as your lowest grade. In case of an emergency, you should explain the reason in the form at by selecting the “missing a class” option.

Late/Missed Work

Assignments that are turned in late are subject to a late penalty. 20% deduction will be applied to the submission which is submitted late for up to 48 hours after the deadline. After 48 hours, you will automatically get Zero. If you have a valid reason for missing a deadline, you should explain the reason in the form at

Email Policy

As instructors can see more information about students and their enrolled sections, it is preferable to use iCollege’s messaging system rather than emails. For questions regarding grades, please email the TA and CC the instructor.

Collaboration Policy

All work is expected to be your own for each exam, quiz, homework, and project. No collaboration is allowed unless otherwise stated in the instructions.

Academic Honesty Policy

We must abide by GSU’s Academic Honesty Policy.

Generative AI Policy

You are allowed to use generative AI tools to help with assignments for this course but only with the following conditions:

  1. Attribution is necessary. You must identify the parts of your submissions (assignments, projects, etc.) that you generated using AI tools.

  2. You should fully understand the generated content (including programming code) and be able to explain it to the instructor if asked.

Failure to comply with these conditions will be considered a violation of the Academic Honesty Policy.

Laptop & Technology Statement

You will need a computer to do the assignments. We will be using e-devices in different capacities in the class. Please make sure to silence your e-devices during the meetings.

Online Class Etiquette

  • Treat each online session as if you were present in class.
  • Mute your microphone when it is not in use.
  • Identifying the speaker is sometimes difficult, especially when the screen is shared. Let others know your name whenever you start speaking.

Syllabus Policy

The course syllabus provides a general plan for the course; deviations may be necessary. The syllabus may be updated throughout the course, so you should check iCollege to ensure you are reading the latest version. The instructor will send an announcement to the class if there has been a major change in the syllabus.

Your constructive assessment of this course plays an indispensable role in shaping education at Georgia State. Upon completing the course, please take the time to fill out the online course evaluation.

Saber Soleymani

Visiting Assistat Professor | Software Developer | Data Scientist