CSCI 200/DMI 200 Data Mining - Fall 2019

Course Information

Lectures:

MWF 1:00 - 1:50 PM, Freedom 303

Professor:


Dr. Yana Kortsarts
Office: 313 Freedom Hall
Phone: (610) - 499 - 4367
e-mail: ykortsarts@widener.edu
homepage: http://cs.widener.edu/~yanako

Office Hours:

Place: Freedom Hall 313
Time:
• Monday: 12:00 - 1:00 PM
• Wednesday: 12:00 - 1:00 PM, 4:00 - 6:00 PM
• Thursday: 6:00 - 7:00 PM - Virtual Office Hours by Skype connect to office_hours_for_students
• Friday: 4:00 - 5:00 PM

Office Hours by Appointment:

To make an appointment, please, send an e-mail ykortsarts@widener.edu
Time:
• Monday, Wed: 9:30 - 10 AM
• Monday: 4:00 - 5:00 PM

Additional office hours and extra help are ALWAYS available!
Please see me in class, call me or email me. I am available at other times outside of the listed office hours to help you. JUST ASK.
To make an appointment, please, send an e-mail ykortsarts@widener.edu

Recommended Texts - NOT REQUIRED:

• Data Mining and Business Analytics with R, Johannes Ledolter, Willey, ISBN: 978-1-118-44714-7
• Applied predictive Analytics: Principles and Techniques for the Professional Data Analyst, Dean Abbott, Wiley, ISBN-13: 978-1118727966
• Data Mining for Business Intelligence, Galit Shmueli, Nitin R. Patel, Peter C. Bruce, Willey, ISBN-13: 9780470526828
• QlikView Your Business: An expert guide to Business Discovery with QlikView and Qlik Sense Oleg Troyansky, Tammy Gibson, Charlie Leichtweis, Lars Bjork (Foreword by) ISBN: 978-1-118-94955-9
• Garcia, M., Harmsen, B. (2012). QlikView 11 for Developers. Birmingham: Packt Publishing

Course Description

This is an introductory course on data mining. Data Mining is a relatively young field that refers to the process of exploration and analysis of large quantities of data in order to discover meaningful patterns and knowledge. The course introduces students to basic descriptive as well as introductory predictive analytics methods to discover and report influential and meaningful patterns in data and predict future behavior. This is a computer science course for business informatics and digital media informatics students, and free elective for computer science and computer information systems students. 3 semester hours

Tentative Course Topics

• Concepts of analytics, descriptive analytics, predictive analytics, business intelligence and data mining
• Overview of descriptive analytics
• Introduction to QlikView and QlikSense ( http://www.qlik.com/ )
• Designing data visualizations using QlikView and QlikSense
• Overview of the predictive anayltics techniques
• Introduction to SAP Predictive Analysis
• Introductory predictive modeling algorithms

Student Learning Outcomes

Upon successful completion of this course, students will be able to:
• Demonstrate understanding of common data mining tasks
• Demonstrate understanding of the goals and importance of Business Intelligence and data analytics
• Apply introductory descriptive analytics techniques to perform the data analysis
• Design data visualizations using QlikView and QlikSense
• Apply introductory predictive analytics techniques to perform data analysis and predict future behavior

Corresponding Digital Media Informatics Objective:

• O.6 Understanding and ability to apply data mining

Corresponding A&S Goals

• Goal 2: A liberally educated graduate thinks critically.
  • 2.a. Makes claims and draws conclusions that require the analysis and evaluation of evidence.
  • 2.b. Synthesizes divergent content, methodologies, and models
• Goal 3: A liberally educated graduate uses quantitative methods effectively.
  • 3.b. Interprets, makes inferences, and draws conclusions from data.
  • 3.c. Determines whether numerical results are reasonable.
• Goal 4: A liberally education graduate has developed a wide range of intellectual perspectives and methodologies.
  • 4.a. Evaluates the workings of the natural and physical world using theories and models that can be tested by experiments and observations.

Corresponding Widener University Institutional Learning Objectives (ILOs)

• ILO 1. Students will demonstrate the knowledge, skills, and scholarship appropriate to their major field of study.
• ILO 2. Students will be able to think critically and communicate effectively.

Policies

Attendance Policy

Attendance is requied. Class Participation and Attendance is 25% of the final grade Missed classes mean you are losing points towards your final grade.

Academic Fraud

The Science Division strictly enforces the University's policy on cheating and other forms of academic fraud.

Student Academic Grievance Procedure

If a student has a grievance concerning a class in which he/she is enrolled, he/she will first try to resolve the problem with the instructor of the class. If it is impossible to resolve the matter at this level, then the grievance must be placed in writing and appealed in the following order:
• Division or Program Head
• Dean of Arts and Sciences (Arts and Sciences Academic Council)
• Provost of the University
• University Academic Council
All student grievances will first be referred to the class instructor before they are treated at the level of the Division Head.

Please see Widener's Undergraduate Catalog for:
Standards for Academic Integrity, Appeal Procedures for Student Academic Grievances, and Attendance Policy.

Please see Widener's Policies on Attendance in the student handbook on-line:
Student Handbook

Learning Accommodations

In accordance with the Americans with Disabilities Act, any student has the right to request reasonable accommodation of a disability. Accommodations can be requested through Academic Support Services, Disabilities Services (520 E. 14th St., 610-499-1266). Disabilities Services is the office that authorizes all accommodations on campus. Please note that you will need to present documentation of your disability to Disabilities Services. It is important to make this request as soon as possible so that we will have time to make any necessary arrangements

Electronic Devices in the Classroom

• NO CELL PHONES. Cell phones must be turned off for the duration of the class.
• All electronic devices except cell phones are permitted

Evaluation Criteria and Policies

• Make-up quizzes and lab assignments
  
  Any make-up for the quizzes and lab assignments must be arranged in advance and done IN CLASS.
• Tentative Quizzes and Lab Assignments Schedule
  • The quiz or lab assignment will be given every Friday
• The duration of the quiz and lab assignment is 50 minutes (full lecture period)
• All lab practices are graded. Grading scale for practice labs: 1 - attended, 0 - not attended

• ALL DATES ARE SUBJECT TO CHANGE. Students will be notified at least one week prior any change in quiz or lab assignment date. The changes will be posted on the course website and sent by e-mail. CHECK THE COURSE WEBSITE AND WIDENER E-MAIL REGULARLY.

The work handed in must be the student's own work.
Assignments which are written in groups are easily identifies and will receive grades of 0 for all participants.

The weights of the homework, quizzes and lab assignments in the final grade are as follows:

Final Grade

In Class Laboratory Assignments and Quizzes	75%
Lab Practices, Attendance, and Homework	25%
Total	100%

Final Grade Table

A:	95 - 100
A-:	90 - 94
B+:	87 - 89
B:	83 - 86
B-:	80 - 82
C+:	77 - 79
C:	73 - 76
C-:	70 - 72
D+:	67 - 69
D:	60 - 66
F:	59 - 0