1. MIS2502: Data Analytics Course Introduction
Aaron Zhi Cheng

2. Contact info
Aaron Zhi Cheng
Office: 201F Speakman
Office hours:
3:50 – 4:50 PM, Mondays & Wednesdays, or by appointment
ITA: Nathaly Gonzalez

3. About Me
A Ph.D. candidate in Business Administration, with a specialization Fox
An external researcher and data scientist for a few companies
IBM (Beijing, China)
TalkingData (Beijing, China)
Vivat Insurance (Amsterdam, the Netherlands) 
Hersha Hospitality Trust (Philadelphia, USA)
National Health Development Research Center (Beijing, China).
community.mis.temple.edu/zcheng

4. Course Overview A foundation for
designing database systems and,
analyzing business data
Hands-on experience with various tools: MySQL, Excel, and R

5. https://www. kdnuggets

6. Modules No. Module Introduction 1 Relational Data Modeling 2
Introduction 1
Relational Data Modeling 2
SQL 1: Getting Information Out of a Database 3
SQL 2: Putting Information Into a Database 4
Extract, Transform, Load (ETL) 5
Dimensional Data Modeling 6
Principles of Data Visualization 7
Advanced Data Analytics and R 8
Classification Using Decision Trees 9
Clustering 10
Association Rules

7. Course Materials No textbook is required for this course.
Where to get course materials?

8. Course Websites community.mis.temple.edu/mis2502sec003f18 Canvas:
Usage
Community Site:
community.mis.temple.edu/mis2502sec003f18
syllabus, schedule, class announcements, slide decks, in-class exercises, assignment instructions, as well as other course documents.
Canvas:
canvas.temple.edu
assignment submission, sharing videos/recordings, posting grades.

9. Evaluation and Grading
Item
Percentage
Exams (3)
60%
Assignments (8)
24%
Group Project 6%
In-class activities 5%
Presence & Participation

10. Exams There will be three exams
Despite some natural overlap in material between the exams, the exams are not intended to be cumulative
Make-up exams will not be given under most circumstances.

11. Assignments Deliverables: Submit through Canvas # Assignment 1
ER Modeling 2
SQL #1 – Getting Data out of the Database 3
SQL #2 – Putting Data into the Database 4
ETL in Excel 5
Introduction to working with R/RStudio 6
Decision Trees 7
Clustering 8
Association Rules

12. Late Assignment Policy
All assignments will be assessed a 50% penalty (subtracted from that assignment’s score) for the first day (i.e. 24 hours) they are late.
No credit will be given for assignments turned in more than 24 hours past the deadline.
Equipment failure is not an acceptable reason for turning in an assignment late

13. A Note on Regrade Requests
Must be submitted within 1 week of the date when the grade was returned.
I reserve the right to regrade the entire assignment/exam and thus your grade may go up or down.

14. In-Class Activities Very hands on in nature Deliverables:
examples and datasets
Deliverables:
Submit through Blackboard
Allowed to miss two submissions for in-class activities
Graded by success or fail

15. Presence & Participation
Perfect score = frequent presence + active participation
Unexcused absence:
Two unexcused absence without penalty
E.g., missing a class because of a job interview, contests or meetings related to professional development
Excused absence:
Only allowed for extreme circumstances such as illness or family emergency and requires documentation
Please contact me by as soon as possible

16. Plagiarism and Academic Dishonesty
Assignments and exams are to be done individually and should represent your own work.
Plagiarism and academic dishonesty are prohibited, such as
Copying from another student’s assignment or exam
Using material from a source without a proper citation
Turning in an assignment from a previous semester as if it were your own
Having someone else complete your homework or project and submitting it as if it were your own
Using material from another student’s assignment in your own assignment
Submitting work done for a different course or section without the instructor’s approval ahead of time
Helping others to plagiarize or cheat, or doing the work of another person

17. General Tips