Data Science – Fall 2017

MIS 0855 – Prof. Min-Seok Pang

MIS 0855 – Thank you!

Dear all,

I have competed grading of Assignment #5 and entered the final grades to Gradebook and TUPortal. You should be able to check yours now at MIS Community Gradebook ( and on Monday (Dec 18) at TUPortal (

Please be advised that the final grades are firm and final. Under no circumstances will the grades be changed. I will not respond to any request for a higher grade or extra credits.

I would like to sincerely thank you for your hard work and contribution to my class. This semester was one of the best thanks to all of you! I very much appreciate it.

If you’d like to keep in touch with me, you can connect with me via LinkedIn at

Once again, thank you, and I wish the best of luck in your continued studies, career, and future endeavors.

Best regards,
– min-seok

In-Class Exercise – Day 39 – Aggregating Data

In-Class Exercise – Day 39 – Aggregating Data in Tableau.pdf

NCAA 2013-2014 Player Stats.xlsx

In-Class Exercise – Day 39 – answer sheet.docx

Canvas submission link –

The lecture on Dec 6 will be given by Aaron Cheng, our TA, as a guest lecturer. This exercise will be counted toward your final grade.

Day 35-36 – Data Science and Your Career – class slides and videos

Day 35 – Your Career.pdf

Amazon Go –

Fetch Automates Your Warehouse With Robots – IEEE Spectrum

Mad Money Features Betterment – CNBC

Riding in Uber’s Self-Driving Cars – The Verge

Robot Customer Service Rep – NBR

Robot Journalists – The Daily Show

Self-Driving Truck Makes First Shipment – CNNMoney

Self-Scanning Robot – Mashable

Technology Kills Middle Class Jobs – AP

World Business – Legal Outsourcing – YouTube!

Present your final project plan and get 3% extra credit (only for first eight)

For next Wednesday (Nov 15), I am seeking volunteers who would like to present a plan for Assignment #5. The presenters or all members of the presenting groups will get a 3% extra credit on Assignment #5. (If you get 90 out of 100, your grade would become 92.7.)

The volunteers will be expected to present the three parts of the project as follows.

1. Topic or title of the project
2. Scenario, questions, or hypotheses
3. Description of the data

I will provide feedback on the plan in-class.

I am inviting the first eight volunteers (either as an individual or a group) for presentations. To sign up, you should email me with either questions (#2) or data that you plan to use (#3).

If you’re interested in, please email me as soon as possible before all eight spots are filled.

Class schedule for the remainder of the semester

Day Date Topic
27 Nov-01 W Visualizing Network
28 Nov-03 F Visualizing Network
29 Nov-06 M Exam #2 Review
30 Nov-08 W Exam #2
31 Nov-10 F Predictive Analytics
32 Nov-13 M Predictive Analytics
33 Nov-15 W Prep for Assignment #5 (Original Data Analysis)
34 Nov-17 F Twitter Sentiment Analysis
Nov-20 M No Class (Thanksgiving Break)
Nov-22 W No Class (Thanksgiving Break)
Nov-24 F No Class (Thanksgiving Break)
35 Nov-27 M Data Science and Your Career
36 Nov-29 W Data Science and Your Career
37 Dec-01 F Exam #3 Review
38 Dec-04 M Exam #3
39 Dec-06 W Aggregating Data (by Guest Instructor Aaron Cheng)
Dec-08 F No Class (Instructor travels for a conference)
Dec-11 M No Class (Instructor travels for a conference)

In-Class Exercise – Day 27-28 – Visualizing Network

In-Class Exercise – Day 27-28 – Visualizing Network.pdf

Flight Paths July 4-8 2016.xlsx

Flight Networks July 4 2016.xlsx

Capital Bikeshare Trips Apr 1 2016.xlsx

Canvas submission link for Nov 3 –

Canvas submission link for Nov 1 –