M.Sc. in Computing & Data Analytics
MSc CDA Courses
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:
In the first two semesters of the MSc CDA program, students are introduced to big data challenges and solutions through eight foundation courses.
All core courses are taught by a faculty member 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.
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.
|September to May (8 months)||May to December
Data Analytics Courses
Applied Learning Options
MCDA 5520: Statistics and its Applications in Business
Emphasis in this course is on developing the conceptual foundations and an in-depth understanding of statistical techniques used in data analytics. Following the descriptive/predictive/prescriptive framework that is commonly imposed on topics in analytics, it emphasizes the analysis and solution of complex business decision problems using computer-based models.
MCDA 5530: Human-Computer Interaction
The objective of this course is to teach students how to design, prototype, and evaluate user interfaces using a variety of methods. Topics covered include human capabilities; interface technology; interface design methods; interface evaluation; and visualization methods for data analytics.
MCDA 5540: Managing and Programming Databases
This course examines the design, implementation, and management of database (db) systems. Students learn 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
During this capstone course, students develop applications that are accessible through the internet on a variety of platform including cloud environments and mobile devices. An emphasis is placed on designing and deploying mobile applications; push technology; data structures and memory management; interface design; Scalable Vector Graphics (SVG); cloud computing; and privacy/security
MCDA5560: Business intelligence
This course uses tools and techniques for customer and product profiling using classification and clustering, analysis of demographic information for business decision making, and supply and demand management using predictive models. Professional business intelligence software is used with real-world data sets to effectively analyze statistical patterns for strategic decision making.
MCDA5570: Managing Information Technology and Systems
This course equips students with processes, models, and frameworks to develop organizational IT strategy in the context of big data. It focuses 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 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. Highly complex big data techniques present many interesting computational challenges. The course uses concepts from pattern recognition, statistics, data analysis and machine learning.
MSC CDA Options
The second half of the program features three applied learning choices:
- internship option
- applied learning projects
- research thesis
MSc CDA students can receive paid internships with local, national, and international industry partners, applying their knowledge and skills on real world data and analytics 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 Applied 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 can offer ongoing support.
MCDA5585 Applied 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.
MCDA5586 Master’s Project - Implementation and Analysis of Results
The second in a two-part series, this course focuses on design, development, implementation, and testing of a computing system with focus on data analytics. As before, students will continue to work in teams with a focus on implementation of the complete system, testing, and simulated cut-over to production.
MCDA5591 Master’s Thesis
The thesis stream is designed for students interested in pursuing doctoral studies or a career in research and development. Theses will be in the area of computing with a particular focus on data analytics. Students in this stream will be assigned a thesis supervisor to help guide their progress.