Special Topics in Data Analytics
Computing Studies & Information Systems
Commerce & Business Administration
Max Class Size
Lecture: 2 hours per week Lab/Seminar: 2 hours per week Total: 4 hours per week
Method Of Instruction
Methods Of Instruction
Lecture, seminar and hands-on exercises in the lab
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.
- 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.
- Describe the technical requirements of managing extensive amounts of data.
- Use various tools to manipulate, map and reduce a large data set.
- Design and implement a technical solution to deal with 4 V’s (Volume, Velocity, Variety, and Veracity) of big data.
- Appraise data scaling strategies such as different types of partitioning and replication in relation to different data growth and data consumption scenarios.
- Evaluate the state of Data Analytics in a chosen industry.
- Explain concepts of data security with regards to Analytics data in storage and in trasmission.
- Discuss the basic principles of ethical conduct in relation to Data Analytics.
- 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%|
Instructor compiled materials
other textbooks as approved by the department