M.Sc. in Computing & Data Analytics

Program Structure and Curriculum

Masters of Science in Computing and Data Analytics is a 16-month professional Master’s program.

MSC CDA features technology platforms, languages, and techniques that are relevant to industry. The program provides exposure to a broad range of technologies to ensure students can adapt to industry needs/trends:

Java/J2EE, C#/.Net, JavaScript/jQuery/jQuery Mobile/node.js, HTML5, PHP, iOS, Android, Amazon Web Services (AWS), IBM Bluemix, Azure, SAS, Cognos, SQL/MySQL, NoSQL/Mongo DB, R, Python, Watson, Hadoop, Spark, Hive

Core Courses

In the first two semesters of the MSc CDA program, students are introduced to software development and big data analytics challenges and solutions through eight foundation courses.

All core courses are taught by faculty members from the Department of Mathematics and Computer Science and Sobey School of Business. Each course also features industry instructors, so that students receive real-world learning experiences.

Sept - Dec (4 months)
Fall Term
Jan - April (4 months)
Winter term
May to Dec (8 months)
Summer & Fall Term
  1. Software Development in Business Environment
  2. Statistics and its Applications in Business
  3. UI/ UX Design and Quality Engineering
  4. Managing and Programming Databases
  1. Web, Mobile, and Cloud Application Development
  2. Business intelligence and Data Visualization
  3. Big Data and Information Technology Management
  4. Data and Text Mining

Applied Learning Options
Complete one of the following:

  1. Graduate Internship I & II
  2. Master’s Project I & II
  3. Master’s Thesis

MCDA 5510: Software Development in Business Environment

This course covers the complete software development process in a business environment, including the system analysis, design, implementation, and testing of software systems. Students will work in teams to develop software systems for business applications using real world methodologies.

MCDA 5520: Statistics and its Applications in Business

Emphasis is on developing an in-depth understanding of statistical techniques used in data analytics. Following the descriptive/predictive/prescriptive framework, it emphasizes the analysis and solution of complex business decision problems using computer-based statistical models.

5530: UI/ UX Design and Quality Engineering

Students design, prototype, and evaluate user interfaces using a variety of methods. Topics covered include business analysis; human capabilities; interface technology; interface design methods; interface evaluation; quality assurance and visualization methods for data analytics.

MCDA 5540: Managing and Programming Databases

Students examine the design, implementation, and management of database (db) systems, considering the implications of data structures and indexing on performance; query processing algorithms and optimization; and concurrency control. In addition to relational db models, study includes alternative data models, structured text, multimedia data, and information retrieval in the context of Big Data.

MCDA5550: Web, Mobile, and Cloud Application Development

Students develop applications accessible through the internet on cloud environments and mobile devices. An emphasis is placed on designing and deploying mobile applications; push technology; data structures, memory management; interface design; Scalable Vector Graphics (SVG); and privacy/security.

MCDA5560: Business intelligence and Data Visualization

Students use professional business intelligence software with real-world data sets to analyze statistical patterns for strategic decision making, customer and product profiling using classification and clustering, analysis of demographics for decision making, and supply/demand management using predictive models.

5570: Big Data and Information Technology Management

Students are provided with processes, models, and frameworks to develop organizational IT strategy in the context of big data. Students focus on leading software and hardware platforms, business software applications and their strategy maps (CRM, ERP, supply chain management, product lifecycle management. Technology adoption, emerging technologies, and diffusion of innovations are covered.

MCDA5580: Data and Text Mining

With the availability of large databases to store, manage and assimilate data, the new thrust of data mining lies at the intersection of db systems, artificial intelligence, and algorithms that efficiently analyze data. Students use concepts from pattern recognition, statistics, data analysis and machine learning for actionable analytics.

Applied Learning Options

The second half of the program features three applied learning choices:

  • internships
  • industry projects
  • research thesis

MCDA 5587 / 5588 Graduate Internship I & II

MSc CDA students can receive paid internships with local, national, and international industry partners, applying their knowledge and skills on real world data and business challenges. While internships are typically eight months, MSc CDA offers the flexibility to meet both student and organizational needs and can create customized placements. For example, a 4-month internship can be combined with an Industry Project to meet graduation requirements.

MSc CDA assists students and industry partners throughout the entire internship lifecycle. In addition to providing a Faculty supervisor for academic support, MSc CDA also has a rich network of industry mentors that offer ongoing support.

MCDA5585 Master’s Project - System & Functional Analysis

Students who pursue this option complete two courses where they develop a group-based applied project that addresses a major data analytics problem identified by an industry partner. Emphasis in this stream is on project management and applying the skills and knowledge gained through CDA.

The first in a two-part series, this course involves the design, development, implementation, and testing of a computing system with focus on data analytics. Students will work in teams to develop a system under supervision of a faculty member. Depending on the nature of their project, students may choose a varying degree of balance between data analytics and system development.

MCDA 5586 Master’s Project - Implementation and Analysis of Results  

The second in a two-part series of courses involving implementation of a complete system, testing, and simulated cut-over to production.

MCDA 5591 Master’s Thesis

The thesis stream is designed for students interested in pursuing doctoral studies or a career in research and development. Students complete a research thesis under the guidance of Faculty Supervisor in conjunction with the other Supervisory Committee members. The student will defend the thesis in front of the Supervisory committee and an external examiner in a public forum.

Industry Workshops and Hackathons

Although not courses per se, students attend a series of workshops on industry relevant topics and participate in various competitions to hone their technical and professional skills.  Examples include:

  • Learning Spark from a Data Engineer, Mobivity Inc.
  • Salesforce Saturday, Cloudkettle Inc.
  • International Business Analytics Challenge, Montreal
  • RBC Next Great Innovator Hackathon, Toronto
  • Data for Good - Poverty Hackathon, Chief Data Office, Government of Canada
  • Innovative Design for Accessibility (IDeA) student competition
  • Payzant Home Hardware Hackathon, David Sobey Centre for Innovation in Retailing & Services
  • Nova Scotia Open Data Hackathon, Province of Nova Scotia