MASTER OF SCIENCE IN Computing & Data Analytics (M.Sc. CDA)
Learn. Generate. Innovate. Expand Your Skills to Meet the Demands of Big Data Saint Mary s new Master of Science in Computing & Data Analytics (MSc CDA) is a graduate-level, 16-month professional program designed to meet the complex challenges associated with Big Data. It combines two essential aspects of computing and data analytics: Software design, development, customization, and management; Business intelligence and analytics: the acquisition, storage, management, and analysis of huge amounts of data to improve efficiency, customer experience, and decision making. MSc CDA graduates emerge with the cutting-edge skills to excel as effective data scientists, business analysts, IT managers, strategists, entrepreneurs, and programmers of business computing solutions. Program Structure In the first half of the program, MSc CDA students complete 8 core courses in Computing and Data Analytics. In the second half, candidates complete one of the following three applied learning options based on their future goals: an Applied Learning Project, an Internship, or a Thesis. Career Path: Your Link to Industry The primary focus of the MSc CDA program is to develop highly qualified computing and data analytics professionals who will drive innovation and organizational success. MSc CDA prepares students for rewarding and lucrative careers in the data science industry through experiential learning opportunities and industry interaction. Faculty and Industry Experts MSc CDA students benefit from the expertise of awardwinning 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 MSc CDA students grow their professional networks exponentially.
Admissions and Fee Application deadline: June 1 Admission requirements 4-yr BSc 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 via Skype, Google Hangouts, teleconference, or in-person. Letter of Intent Up-to-date CV 3 letters of recommendation Language requirements Experiential Learning MSc CDA organizes several industry sponsored appathons and hackathons, providing non-traditional learning opportunities for students. In addition to fostering teamwork and project management skills, students enrich their portfolios by designing and developing innovative applications and liaise directly with industry judges. Through special guest lectures and structured, industrymentor proograms available to all students, MSc CDA s cohort structure offers an enriched learning environment. The program also provides opportunities for students to attend various conferences and industry-led workshops. Partnerships 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 The entire MSc CDA program is infused with software, tools, and insights from industry leaders in Big Data, analytics, and business intelligence. MSc CDA is proud to partner with these prominent organizations leading the Big Data revolution:
MSc CDA Program Structure 4 Computing Courses + 4 Data Analytics + Courses Applied Learning Options Software Development in Business Environment Statistics and Its Applications in Business Internships Web. Mobile, and Cloud Development Managing & Programming Databases Applied Projects: System Analysis; Implementation & Results Analysis Human-Computer Interaction Business Intelligence Thesis Managing Information Technology & Systems Data Mining
Eight courses and three applied learning options designed for emerging IT leaders. Core Courses MSC CDA features technologies that are relevant to industry, providing 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, Bluemix, Azure, SAS, Cognos, SQL/MySQL, NoSQL/Mongo DB, R, Python, 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. MSc CDA also provides extensive tutoring and extended learning opportunities that allow students to reach their full potential. 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. Your Future is in Big Data. Our MSc 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 Big Data expertise over the last twelve months. (Forbes) 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. 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 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.
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 MSc CDA: Your path to IT excellence. 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. 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 The second half of the program features three applied learning choices: Internship Applied Learning Project Research Thesis MCDA5500: Internship 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 & 5586: Applied Master s Project The second component focuses on implementation and testing of a computing system with focus on data analytics. As before, students 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. 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.
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. MSc 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. smu.ca/mscda Faculty of Graduate Studies and Research Saint Mary s University 923 Robie Street Halifax, Nova Scotia B3H 3C3 902.491.6535 msc.cda@smu.ca