MBA 8020 (Data Visualization) *Citizen Data Scientist Track*
Fall 2023 Updated on Aug 14, 2023 - Section 4 (CRN: 88779): Tuesdays 12:00 pm - 2:30 pm
- Section 9 (CRN: 93223): Tuesdays 3:00 pm - 5:30 pm
| Office Hours | Link | ||
|---|---|---|---|
| Saber Soleymani (instructor) | ssoleymani@gsu.edu | Mondays 2:00 - 3:00 pm | Webex Meetings |
| Sai Roopesh Mandava (Teaching Assistant) | smandava4@student.gsu.edu | Thursday 2:00 - 3:00 pm |
Course Description
The Analytics Experience allows students to work on real-world problems and apply analytical techniques to answer diverse questions. The course provides an overview of current challenges and solutions in data analytics. Given a business situation and data, students will learn how to solve a problem and acquire insight from data with techniques they have learned.
Learning Objectives
By the end of the course, students should be able to:
- Explain descriptive, exploratory, predictive, and prescriptive data analysis.
- Explain various data structures and their use cases.
- Explain ETL (Extract, Transform, Load) techniques, challenges, and solutions.
- Explore, visualize, and modify structured datasets.
- Identify the appropriate type of analysis based on the problem.
- Describe the process of building supervised predictive models.
Textbooks
- 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 | Agenda |
|---|---|---|---|
| 10/10 | Week 1 | Online | Course Introduction, Data Taxonomy, & Python basics |
| 10/17 | Week 2 | In-person | Data Manipulation and Visualization with Python (part I) |
| 10/24 | Week 3 | In-person | Data Manipulation and Visualization with Python (part II) |
| 10/31 | Week 4 | Online | Interactive Visualizations (part I) |
| 11/07 | Week 5 | In-person | Interactive Visualizations (part II) |
| 11/14 | Week 6 | In-person | Specialized data visualization tools |
| 11/28 | Week 7 | Online | Final Project Presentation |
Deadlines
| Assignment | Due Date |
|---|---|
| Reading 1 | Due [Date] (before week 2) |
| Reading 2 | Due [Date] (before week 5) |
| Final Group Project | On [Date] (week 7) |
| Bonus: Reading 3 | Due [Date] |
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 |
| 20 | Reading Reflection 2 |
| 15 | Pop-Quizzes |
| 40 | Final Group Project |
| 10 | Participation & Discussions |
| 10 | Bonus: Reading Reflection 3 |
Course Policies
Attendance Policy
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. While individual attendance will be tracked, it will not be graded directly. 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.
Late/Missed Work Policy
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.
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.
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. If you use a paragraph or code from the internet, you should cite that resource.
Academic Honesty Policy
We must abide by GSU’s 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
Designate Your Workspace
- 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
This course syllabus is a general course plan; the instructor’s 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. I will send an announcement to the class if there has been a major change in the syllabus.