Special Topics in Data Analytics

Curriculum guideline

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Course
CSIS 4260
Discontinued
No
Course code
CSIS 4260
Descriptive
Special Topics in Data Analytics
Department
Computing Studies & Information Systems
Faculty
Commerce & Business Administration
Credits
3.00
Start date
End term
201820
PLAR
No
Semester length
15
Max class size
35
Contact hours
Lecture: 2 hours per week Lab/Seminar: 2 hours per week Total: 4 hours per week
Method(s) of instruction
Lecture
Lab
Seminar
Learning activities

Lecture, seminar and hands-on exercises in the lab

Course description
Students will learn about emerging technologies and trends in Data Analytics. This course is divided into several modules. Each module represents a specialized body of knowledge focusing on the technical aspects of the 4V's of big data ( Volume, Velocity, Variety, and Veracity) as well as policy and other aspects such as privacy and ethics. Students will also get a chance to research state-of-the-art Data Analytics in an industry of their choice. This course will provide students the required breadth to jumpstart their career in the Data Analytics field.
Course content
  • Module 1 (2 weeks): Capturing, managing and using data for decision making.
  • Module 2 (3 weeks): Using tools for mining different types of data such as structured data, text data, and web data. 
  • Module 3 (3 weeks): Building the technology stack for Data Analytics in terms of 4 V’s of big data, i.e. Volume, Velocity, Variety, and Veracity.
  • Module 4 (3 weeks): Research Data Analytics in different industries. 
  • Module 5 (1 week): Workshop on data security issues.
  • Module 6 (1 week): Workshop on ethics and privacy issues.
Learning outcomes
  1. Describe the technical requirements of managing extensive amounts of data.
  2. Use various tools to manipulate, map and reduce a large data set.
  3. Design and implement a technical solution to deal with 4 V’s (Volume, Velocity, Variety, and Veracity) of big data.
  4. Appraise data scaling strategies such as different types of partitioning and replication in relation to different data growth and data consumption scenarios.
  5. Evaluate the state of Data Analytics in a chosen industry.
  6. Explain concepts of data security with regards to Analytics data in storage and in trasmission.
  7. Discuss the basic principles of ethical conduct in relation to Data Analytics.
  8. Discuss the basic principles of data privacy in relation to Data Analytics.
Means of assessment
Class Participation 0% - 5%
Assignments (min 2) 20% - 30%
Quizzes (min 2) 10% - 15%
Group Project 20% - 25%
Final Examination 25% - 35%
Total 100%
Textbook materials

Instructor compiled materials

or

other textbooks as approved by the department

Prerequisites

CSIS 3300 OR CSIS 3360