MASTER OF SCIENCE IN

Computing & Data Analytics2017

Faculty and Industry ExpertsM.Sc. CDA students benefit from the expertise of award-winning faculty from Saint Mary’s Faculty of Science and the Sobey School of Business, the largest Canadian business school east of Quebec. These instructors are experts in their fields, and actively involved in research and development activities in data analytics. Furthermore, all courses feature industry-based instructors who teach in-demand skills. These industry interactions help M.Sc. CDA students exponentially grow their professional networks and gain

experience solving real-world business problems.

Experiential LearningM.Sc. CDA organizes several industry sponsored appathons and hackathons that provide non-traditional learning opportunities for students. In addition to fostering teamwork and project management skills, students enrich their portfolios by designing and developing innovative data-driven applications and liaise directly with industry judges.

Through special guest lectures and structured, industry-mentor programs available to all students, M.Sc. CDA’s cohort structure offers an enriched learning environment. The program also provides opportunities for students to

attend various conferences and industry-led workshops.

Learn. Generate. Innovate. Expand Your Skills to Meet the Demands of Big Data

Launched in 2015, the Master of Science in Computing & Data Analytics at Saint Mary’s is a 16 month professional graduate program designed to meet the complex challenges associated with Big Data.

The program combines two essential aspects of computing and data analytics:

• Software design, development, customization, and management;

• Data analytics and business intelligence: the acquisition, storage, management, and analysis of huge amounts of data to improve decision making, solve real world problems, and drive innovation.

M.Sc. CDA graduates emerge with the cutting-edge skills to excel as data scientists, business analysts, IT managers, strategists, entrepreneurs, and programmers of business computing solutions.

Career Path: Your Link to IndustryThe primary focus of the M.Sc. CDA program is to develop highly qualified computing and data analytics professionals who will drive innovation and organizational success. M.Sc. CDA prepares students for rewarding and lucrative careers in the data science industry through experiential learning opportunities and industry interaction.

Admissions and Fees

Application deadline: June 1.

M.Sc. CDA cohorts are limited to 30 students. Qualified students are encouraged to apply early.

Admission requirements

• 4-year B.Sc. in Computing Science (or equivalent), with a GPA equivalent to 70%

• Saint Mary’s programming test to evaluate candidates’ computing skills. The test requires students to write two computer programs and complete a technical interview conducted in-person or via Skype, Google Hangouts, or teleconference.

• Letter of Intent• Up-to-date CV• 3 letters of recommendation

Language requirements

Students whose first language is not English and who have not attended an English language secondary school or completed a degree entirely in English, must meet one of the following qualifications:

• TOEFL - minimum 550 on paper-based, minimum iBt 80, no band below 20

• IELTS - minimum 6.5, no individual score below 6.0

• English for Academic Purposes Level 6 course administered by the Language Centre at Saint Mary’s University

Tuition fees

International Students.........................$ 33,000 (CAD)**Estimated amount. Excludes associated fees and living expenses

Tuition for M.Sc. CDA is assessed as a Program fee, divided into four equal instalments due at the beginning of each academic term (September, January, May, September)

For miscellaneous university fees, please use our Graduate Financial calculator: http://www.smu.ca/academics/graduate-tuition-calculator.html

PartnershipsThe entire M.Sc. CDA program is infused with software,

tools, and insights from industry leaders in Big Data,

analytics, and business intelligence. M.Sc. CDA partners

with local, national, and international organizations to help

students develop in-demand analytics skills and knowledge,

leading to exceptional career opportunities.

M.Sc. CDA is also a Registered Education provider for the

Certified Analytics Professional designation.

M.Sc. CDA program graduates will have fulfilled the

education requirements for CAP® credential and are

prepared to write the qualifying exam.

In the first half of the program, M.Sc. CDA students complete these eight core courses in Computing and Data Analytics.

In the second half, candidates complete one of the following applied learning options based on their future goals: an Applied Learning Project, an Internship, or a Thesis.

M.Sc. CDA Program Structure

Four Computing Courses

1. Software Development in

Business Environment

2. Web, Mobile, and Cloud

Development

3. Human-Computer Interaction

4. Managing Information Technology

and Systems

Four Data Analytics Courses

1. Statistics and Its Applications

in Business

2. Managing & Programming

Databases

3. Business Intelligence

4. Data Mining

September to May (8 months) May to December (8 months)

Applied Learning Options

1. Internships

2. Applied projects: System Analysis;

Implementation; and Results

Analysis

3. Thesis

Professional Development

Fall Hackathon

Conferences Career Development

IndustryWorkshops

Spring Hackathon

ProjectManagement

ProfessionalMentorship

Your Future is in Data. Our M.Sc. CDA will help you get there.

• 56% of Fortune 500 companies will increase investments in Big Data over next three years. (Forbes)

• Industry will hire over 4.4 million Data Scientists by 2016. (Gartner)

• Big Data will need 1.5 million managers by 2018. (McKinsey Global Report)

• There was a 123.60% jump in demand for Information Technology Project Managers with analytics expertise over the last twelve months. (Forbes)

Eight courses and three applied learning options designed for emerging IT leaders.

Core CoursesM.Sc. CDA features technologies that are relevant to industry, providing exposure to a broad range of technologies to ensure students can adapt to industry needs and trends: Java/J2EE, C#/.Net, JavaScript/jQuery/jQuery Mobile/node.js, HTML5, PHP, iOS, Android, IBM Bluemix, Azure, SAS, Cognos, SQL/MySQL, NoSQL/Mongo DB, R, Python, IBM Watson.

All core courses are taught by faculty members from the Department of Mathematics and Computer Science or the Sobey School of Business. Each course also features industry instructors, which ensures that students receive real-world learning experiences. M.Sc. CDA also provides extensive tutoring and extended learning opportunities that allow students to reach their full potential. Tutoring and technical mentorship includes group sessions, and one-on-one instruction and practice.

MCDA 5510: Software Development in Business EnvironmentThis 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 BusinessEmphasis in this course is on developing the conceptual foundations and an in-depth understanding of statistical techniques used in data analytics. Topics include descriptive and inferential statistics, multiple regression, forecasting, and quality control. The focus is on statistical analysis of real business problems through design, analysis, and interpretation of data collections.

MCDA 5530: Human-Computer InteractionThe 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 platforms, 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

Data mining refers to a family of techniques used to detect interesting knowledge in data. With the availability of large databases to store, manage and assimilate data, the new thrust of data mining lies at the intersection of database systems, artificial intelligence, and algorithms that efficiently analyze data. Big Data and high-complexity techniques present many interesting computational challenges. The course will use concepts from pattern recognition, statistics, data analysis, and machine learning.

Applied Learning Options

During the second half of the program, students choose from three applied learning choices:

• Internship • Applied Learning Project• Research Thesis

MCDA5587 and 5588 Graduate Internship I & II

M.Sc. CDA students can receive paid internships with local, national, and international industry partners where they can apply their knowledge and skills on real-world data and analytics challenges. While internships are typically eight months, M.Sc. CDA offers the flexibility to meet both student and organizational needs and can

M.Sc. CDA: Your path to IT excellence.

create customized placements. For example, internships

and industry projects can be combined to meet graduation

requirements.

M.Sc. CDA assists students and industry partners throughout

the entire internship lifecycle. In addition to providing a

Faculty supervisor for academic support, M.Sc. CDA also has

a rich network of industry mentors who can offer ongoing

advice and guidance.

MCDA5585 & 5586: Applied Master’s Project

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 course involves the design, development, and

testing of a computing system with a focus on data analytics.

Students will work in teams to develop a system under the

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.

Learn from faculty and industry mentors who are experts in their fields.

The second component focuses on implementation and testing

of a computing system with focus on data analytics. As before,

students 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.

Faculty of Science Saint Mary’s University923 Robie StreetHalifax, Nova Scotia B3H 3C3902.491.6535msc.cda@smu.ca

Saint Mary’s University:Innovation in practice.

Saint Mary’s University is a world-class institution for higher learning with a rich 200+ year history. It offers state-of-the-art facilities and a dynamic, multicultural community. Saint Mary’s is located in the historic city of Halifax, the bustling economic and cultural centre of the province of Nova Scotia, on the east coast of Canada.

Halifax: Atlantic Canada’s Innovation Hub

A growing leader in the information technology sector, Nova Scotia recently solidified its commitment to the growth of industry and data analytics with the establishment of the IBM Global Delivery Center. This Centre, a collaboration between Saint Mary’s University, IBM, and other post-secondary educational institutions in the region, is designed to promote data analytics education and research.

M.Sc. CDA students benefit from IBM’s active academic alliance program, which provides data analytics resources including licensing of software, instructional videos, and data analytics case studies. The collaboration is also expected to include involvement of IBM professionals in student mentoring.

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