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Webster University • Webster Groves, MO • George Herbert Walker School of Business & Technology • Mathematics/Computer Science

Introduction to Data Science CSIS-2500

  • S2 2017

  • Section W5

  • 3 Credits

  • 03/20/2017 to 05/12/2017

  • Modified 03/07/2017


This course serves as an introduction to data science, which incorporates theories and techniques from many areas, such as statistics and data mining, to extract valuable knowledge from data. The course provides an overview of fundamental principles about how data science can provide solutions to business problems, techniques for extracting meaning from data, and general approaches of data analytical thinking.


CSIS 1500


At the completion of this course students will be able to:

  1. Explain data, what it represents and how it is organized.
  2. Explain how to represent data in a variety of common formats
  3. Discuss predictive modeling, the distinction between model training, evaluation, and use.
  4. Explain big data and problems it presents and some techniques for dealing with big data challenges.
  5. Discuss how to visualize data for exploratory and confirmatory analysis
  6. Discuss data mining and some predictive models, such as decision tree, linear models and probability estimation.
  7. Discuss and apply model evaluation, accuracy, ranking metrics, and model complexity.
  8. Explain some of the main applications of data science.

Required Textbook

Data Science for Business

Author: Foster Provost and Tom Fawcett
Publisher: O'Reilly Media
Edition: 1st
ISBN: 978-1-44-936132-7


Week 1

Topics Covered

  • Introduction to Data Science
  • The Ubiquity of Data Opportunities
  • Data Science, Engineering, and Data-Driven Decision Making
  • Data-Analytic Thinking
  • From Business Problems to Data Mining Tasks
  • The Data Mining Process


  • Chapter 1 Introduction: Data-Analytic Thinking
  • Chapter 2 Business Problems and Data Science Solutions


  • Quiz W1

Week 2

Topics Covered

  • From Correlation to Supervised Segmentation
  • Models, Induction, and Prediction
  • Supervised Segmentation
  • Visualizing Segmentations
  • Trees as Sets of Rules
  • Probability Estimation


  • Chapter 3 Introduction to Predictive Modeling: From Correlation to Supervised Segmentation


  • Quiz W2

Week 3

Topics Covered

  • Fitting Model to Data and Overfitting Avoidance
  • Classification via Mathematical Functions
  • Regression via Mathematical Functions
  • Generalization and Overfitting
  • From Holdout Evaluation to Cross-Validation
  • Overfitting Avoidance and Complexity Control


  • Chapter 4 Fitting a Model to Data
  • Chapter 5 Overfitting and Its Avoidance


  • Quiz W3

Week 4

Topics Covered

  • Similarity, Neighbors, and Clusters
  • Similarity and Distance
  • Nearest Neighbors for Predictive Modeling
  • Nearest-Neighbor Reasoning
  • Clustering
  • Solving a Business Problem Versus Data Exploration
  • Midterm exam


  • Chapter 6 Similarity, Neighbors, and Clusters


  • Quiz W4
  • Midterm

Week 5

Topics Covered

  • Model Evaluation and Performance Visualization
  • Evaluating Classifiers
  • Generalizing Beyond Classification
  • A Key Analytical Framework: Expected Value
  • Ranking Instead of Classifying
  • Profit Curves


  • Chapter 7 Decision Analytic Thinking I: What Is a Good Model?
  • Chapter 8 Visualizing Model Performance


  • Quiz W5

Week 6

Topics Covered

  • Probabilistic Reasoning and Text Mining
  • Combining Evidence Probabilistically
  • Applying Bayes’ Rule to Data Science
  • A Model of Evidence “Lift”
  • Text Representation
  • Beyond Bag of Words


  • Chapter 9 Evidence and Probabilities
  • Chapter 10 Representing and Mining Text


  • Quiz W6

Week 7

Topics Covered

  • Toward Analytical Engineering
  • Targeting the Best Prospects
  • Co-occurrences and Associations
  • Profiling: Finding Typical Behavior
  • Link Prediction and Social Recommendation
  • Data Reduction, Latent Information, and Movie Recommendation


  • Chapter 11 Decision Analytic Thinking II: Toward Analytical Engineering
  • Chapter 12 Other Data Science Tasks and Techniques


  • Quiz W7

Week 8

Topics Covered

  • Data Science and Business Strategy
  • Achieving Competitive Advantage with Data Science
  • Sustaining Competitive Advantage with Data Science
  • Attracting and Nurturing Data Scientists and Their Teams
  • What Data Can’t Do: Humans in the Loop, Revisited
  • Privacy, Ethics, and Mining Data About Individuals
  • Final exam


  • Chapter 13 Data Science and Business Strategy
  • Chapter 14 Conclusion


  • Quiz W8
  • Final Exam

Institutional Policies

Academic Policies

Academic policies provide students with important rights and responsibilities.  Students are expected to familiarize themselves with all academic policies that apply to them.  Academic policies for undergraduate students can be found in the Undergraduate Studies Catalog; graduate students should review the Graduate Studies Catalog.

Undergraduate Studies Catalog

The Undergraduate Studies Catalog contains academic policies that apply to all undergraduate students. The academic policies and information section of the catalog contains important information related to attendance, conduct, academic honesty, grades, and more. If you are an undergraduate student, please review the catalog each academic year. The current Undergraduate Studies Catalog is at:

Graduate Studies Catalog

The Graduate Studies Catalog contains academic policies that apply to all graduate students. The academic policies section of the catalog contains important information related to conduct, academic honesty, grades, and more. If you are a graduate student, please review the catalog each academic year. The current Graduate Studies Catalog is at:


The Grades section of the academic catalog outlines the various grading systems courses may use, including the information about the final grade reported for this class.




There are important policies that govern grades of Incomplete (I), including the circumstances under which Incomplete grades are granted, deadlines for completion, and consequences should the remaining course work not be completed.  It is the responsibility of a student who requests an Incomplete to ensure that he/she understands and follows the policies.

Grade Appeals

Instructors are responsible for assigning grades, and student should discuss grade issues with the instructor. Policies and procedures for appealing grades are available in the appropriate catalog.

Academic Honesty Policy

Webster University is committed to academic excellence. As part of our Statement of Ethics, we strive to preserve academic honor and integrity by repudiating all forms of academic and intellectual dishonesty, including cheating, plagiarism and all other forms of academic dishonesty. Academic dishonesty is unacceptable and is subject to a disciplinary response. Students are encouraged to talk to instructors about any questions they may have regarding how to properly credit others’ work, including paraphrasing, quoting, and citation formatting. The university reserves the right to utilize electronic databases, such as, to assist faculty and students with their academic work.

The University’s Academic Honesty Policy is published in academic catalogs:



As a part of the University commitment to academic excellence, the Academic Resource Center provides student resources to become better acquainted with academic honesty and the tools to prevent plagiarism in its many forms:

Statement of Ethics

Webster University strives to be a center of academic excellence. The University makes every effort to ensure the following:

  • The opportunity for students to learn and inquire freely
  • The protection of intellectual freedom and the rights of professors to teach
  • The advancement of knowledge through scholarly pursuits and relevant dialogue

To review Webster University's statement of ethics, see the Undergraduate Studies Catalog and the Graduate and Studies Catalog:



Contact Hours for this Course

It is essential that all classes meet for the full instructional time as scheduled. A class cannot be shortened in length. If a class session is cancelled for any reason, the content must be covered at another time.

Important Academic Resources

Academic Accommodations

Webster University makes every effort to accommodate individuals with academic/learning, health, physical and psychological disabilities. To obtain accommodations, students must identify themselves and provide documentation from a qualified professional or agency to the appropriate campus designee or the ADA Coordinator at the main campus. The ADA Coordinator may be reached at 314-246-7700 or

If you have already identified as a student with a documented disability and are entitled to classroom or testing accommodations, please inform the instructor of the accommodations you will require for this class at the beginning of the course.

Academic Resource Center 

Additional support and resources may be accessed through the Academic Resource Center (ARC). Support and resources include academic counseling, accommodations, assistive technology, peer tutoring, plagiarism prevention, testing center services, and writing coaching. Visit or Loretto Hall 40 on the main campus for more information.

University Library

Webster University Library is dedicated to supporting the research needs and intellectual pursuits of students throughout the University’s worldwide network. Resources include print and electronic books, journal articles, online databases, DVDs and streaming video, CDs and streaming music, datasets, and other specialized information. Services include providing materials at no cost and research help for basic questions to in-depth exploration of resources. The gateway to all of these resources and services is For support navigating the library’s resources, see for the many ways to contact library staff. 

Drops and Withdrawals

Drop and withdrawal policies dictate processes for students who wish to unenroll from a course.  Students must take proactive steps to unenroll; informing the instructor is not sufficient, nor is failing to attend.  In the early days of the term or semester, students may DROP a course with no notation on their student record.  After the DROP deadline, students may WITHDRAW from a course; in the case of a WITHDRAW, a grade of W appears on the student record.  After the WITHDRAW deadline, students may not unenroll from a course.  Policies and a calendar of deadlines for DROP and WITHDRAW are at:



Academic Calendar -

Current tuition rates, policies, and procedures, including details of pro-rated tuition refunds, are available in the “Tuition, Fees, and Refunds” section of Webster’s Academic Catalogs:



Student Handbook and Other Important Policies

Student handbook and other non-academic policies may apply to you and may impact your experience in this class.  Such policies include the student code of conduct, privacy, technology and communications, and more. Please review the handbook each year and be aware of policies that apply to you.  The handbook is available at:

Sexual Assault, Harassment, and Other Sexual Offenses

Webster University makes every effort to educate the community to prevent sexual assault, harassment, and other sexual offenses from occurring, and is committed to providing support to those affected when this behavior does occur. To access information and resources or to review the Policy on Sexual Assault, Harassment, and Other Sexual Offenses, visit:

Research on Human Subjects

The Webster University Institutional Review Committee (IRB) is responsible for the review of all research on human subjects.  The IRB process applies to all Webster University faculty, staff, and students and must be completed prior to any contact with human subjects.  For more information on the IRB, visit:

Course Evaluations

At the end of this course, you will have the opportunity to provide feedback about your experience. Your input is extremely valuable to the university, your instructor, and the department that offers this course. Please provide your honest and thoughtful evaluation, as it helps the university to provide the best experience possible for all of its students.

Important Technology Information

Connections Accounts

Webster University provides all students, faculty, and staff with a University email account through Connections. Students are expected to activate their Connections account and regularly check incoming University email. Students may choose to have their University email forwarded to an alternate email address. Connections account holders can call the Help Desk (314-246-5995 or toll free at 1-866-435-7270) for assistance with this setup. Instructions are also provided on the Information Technology website at:


WorldClassRoom is Webster’s Learning Content Management System (LMS). Your instructor may use WorldClassRoom to deliver important information, to hold class activities, to communicate grades and feedback, and more. WorldClassRoom is available using your Connections ID at:

Webster Alerts

Webster Alerts is the University's preferred emergency mass notification service, available free to current students, faculty and staff at all US campuses. By registering a valid cell phone number and email address, you will receive urgent campus text, voice mail and email communications. Valuable information concerning a range of incidents affecting you - from weather-related campus closures, class delays and cancellations, to more serious or life-threatening events - are immediately and simultaneously delivered through multiple communication channels. To register for Webster Alerts, visit:

Campus Information