Data Science

Data science (DS) is an interdisciplinary field that utilizes algorithms and methods to transform large volumes of complex data into interpretable knowledge and actionable insights. The success of the data-to-knowledge transformation process relies on the efficiency of bringing the appropriate information to the right person via intelligent information systems. This specialization lies in the intersection of information, systems, and people. The courses will prepare the students a solid foundation of understanding the innerworkings of intelligent information system with the considerations of technical, policy, and societal issues. Specifically, the courses cover data science programming, database design, web systems, data warehousing, data mining, and information security. Students may further deepen their knowledge by taking other machine learning and text mining courses from other departments.

 

Suggested Courses

  • GLIS 629 Information Security 3 Credits
      Offered in the:
    • Fall
    • Winter
    • Summer

  • GLIS 630 Data Mining 3 Credits
      Offered in the:
    • Fall
    • Winter
    • Summer

  • GLIS 634 Web System Design & Management 3 Credits
      Offered in the:
    • Fall
    • Winter
    • Summer

  • GLIS 657 Database Design & Development 3 Credits
      Offered in the:
    • Fall
    • Winter
    • Summer

  • GLIS 691 Special Topics 1 3 Credits
      Offered in the:
    • Fall
    • Winter
    • Summer

    - Computer Programming for Information Professionals
  • GLIS 692 Special Topics 2 3 Credits
      Offered in the:
    • Fall
    • Winter
    • Summer

    - Data Science

 

Practice settings

As the complexity and quantity of digital data continue to grow in every aspect of our society, there is a high demand of data scientists, analysts, and engineers in every sector, from IT to finance, from healthcare to manufacturing, in both private to public sectors. Thus, data scientists and analysts can be found in every sector.

 

Primary responsibilities

The responsibilities of data scientists and analysts vary depending on their roles and functionalities in an organization. Data scientists and engineers are responsible to design and implement the process of transforming raw data from databases to insightful knowledge for C-level management. Data scientists need to ensure the validity of the results. Business analysts designs reports and redesign the business processes to achieve the goals set by the management. Solution architect is responsible to transform the clients’ objectives to feasible software development milestones and tasks that can be implemented by software engineers and machine learning engineers.

 

Examples of job titles

Data scientist

Data analyst

Business analyst

Machine learning engineer

Data engineer

Business reporting specialist

Data integration specialist

Solution architect

 

Potential employers

Canadian Centre for Cyber Security

Canada Revenue Agency

Service Canada

Law enforcements

IT companies

Telecommunication companies

Cybersecurity companies

Financial institutions (e.g., banks, insurance companies)

News media

Social media

Online stores

Hospitals

Health agencies

Transportation sector

Energy sector

 

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