School, location	Type of Program	Home base/ joint program?	Requirements	Duration	Cost	Outcome/jobs	Description and target audience	Unique selling features	Co-op	Courses
University of British Columbia, Vancouver BC	Master of Data Science	Department of Computer Science and the Department of Statistics	Meet the academic requirements set out by UBC’s Faculty of Graduate and Postdoctoral Studies, including holding the equivalent of a four-year bachelor’s degree from UBC with a minimum B+ (76% at UBC) average in your third and fourth-year courses. Proof of completion of three (three-credit) prerequisite courses: one course in programming (e.g., similar to UBC CPSC 110 or APSC 160), AND one course in probability and/or statistics (e.g., similar to UBC STAT 200 or STAT 241/251 or STAT 302), AND one course in calculus (e.g., similar to UBC MATH 100) or one course in linear algebra (e.g., similar to UBC MATH 221). Completion of a course in both calculus and linear algebra is recommended. If your undergraduate degree was not completed at an English-speaking university, proof of English-language proficiency is required as this program requires a significant amount of reading, writing and oral communication. See the International Students page for more information. Proof of citizenship for domestic and international students. All Applicants must also meet the general admissions requirements for UBC Master’s Degree	10 months - full-time	$30,000 domestic / $39,999 international	Candidates graduate with the skills to extract and analyze data and then communicate the findings of those analyses in compelling and clear ways to help organizations put data to work.	Organizations today, whether for profit or non-profit, lack staff with the skills to extract knowledge from the reams of data available.  The new UBC Master of Data Science program fills that gap. It provides graduates with the ability to analyze data, extract knowledge from that data and provide insights to those who can take action in an organization. The data science value chain spans from programs and jobs aimed at extracting and manipulating large amounts of data to programs and jobs that focus on taking action on knowledge extracted from the data. The UBC Master of Data Science focuses on the middle of the value chain, producing graduates that can apply scientific approaches and techniques to answer questions posed by domain experts. These graduates work alongside experts in big data (for instance, graduates from the SFU Masters in Big Data) and graduates from business analytics degrees who specialize in prescriptive action.  Utilizing descriptive and prescriptive techniques, students extract and analyze data from both unstructured and structured forms and then communicate the findings of those analyses in ways to enable organizations to make informed decisions based on data. Who: Students with an undergraduate degree, required pre-requisite courses, an inquisitive nature, a passion for learning, and a burning intellectual curiosity.	Covers the middle-ground between computing experts and decision-makers.	no	Over 10 months, you will learn how to extract data for use in experiments, how to apply state-of-the-art techniques in data analysis and how to present extracted knowledge effectively to domain experts. • Programming for Data Science • Algorithms and Data Structures • Databases and Data Retrieval • Computing Platforms for Data Science • Data Science Workflows • Data Wrangling • Collaborative Software Development • Web and Cloud Computing • Data Visualization I • Data Visualization II • Privacy, Ethics, and Security • Communication and Argumentation • Exploratory Data Analysis for Data Science • Statistical Inference and Computation I • Statistical Inference and Computation II • Experimentation and Causal Inference • Regression I • Regression II • Unsupervised Learning • Supervised Learning I • Supervised Learning II • Feature and Model Selection • Spatial and Temporal Models • Advanced Machine Learning • Capstone Project
St. Mary's University, Halifax NS	Master of Science in Computing & Data Analytics (MSc CDA)	Faculty of Science + Sobey School of Business	• 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 in-person or via Skype, Google Hangouts, or teleconference. • Letter of Intent • Up-to-date CV • 3 letters of recommendation • English language requirements if ESL	16-month or Part-time program (2 years)	$33,000 International Students for 16-month; $17,000 for 2-year program (Canadians)	.Data scientists .Business analysts .IT managers .Strategistics .Entrepreneurs .Programmers	Designed to meet the complex challenges associated with Big Data. It combines two essential aspects of computing and data analytics: 1. Software design, development, customization, and management. 2. Analytics and Business intelligence: the acquisition, storage, management, and analysis of huge amounts of data to improve efficiency, innovation, and decision making. 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.	IBM Global Delivery Center -- a collaboration between Saint Mary’s University, IBM, and other post-secondary educational institutions in the region -- to promote data analytics education and research.  Industry connections via hackathons and app competitions, structured mentorships and industry conferences. Courses taught by academic faculty and industry professionals.	Not mandatory.	8 core courses, then choose a stream for second half of program: 1) applied learning project; 2) thesis; or 3) internship. Courses include: 1. Software Development in Business Environment 2. Statistics and its Applications in Business 3. Human-Computer Interaction 4. Managing Information Technology and Systems 5. Data Mining 6. Managing and Programming Databases 7. Web, Mobile, and Cloud Application Development 8. Business intelligence
BCIT, Burnaby BC	Applied Data Analytics Certificate	School of Computing and Academic Studies	Grade 12, plus 2 college-level computer courses in Applied Computer Concepts, and MS Office 2013 or Excel Spreadsheet Fundamentals.	Must finisih within 5 years	$9,000	Upon program completion, students will know how to integrate scalable and secure business intelligence solutions for Management Information Systems (MIS). Graduates of the Applied Data Analytics Certificate (ADAC) will be able to design data analytics projects to help organizations across sectors make informed and actionable decisions. ADAC graduates will have learned the technical computing foundations to keep up with changes in data technologies and future business intelligence trends.	The Applied Data Analytics Certificate (ADAC) from BCIT Computing provides the computer science foundations for data analytics systems. Students learn how to determine data requirements, plan for the entire data life cycle, model data, and use IT tools to mine data for business intelligence and data-driven decision making. Starting with relational database systems, students have a foundation for data warehouse, data quality improvement, and visual analytics. Statistics for data analytics, IT and Internet Law, and IT security are required courses, along with Hadoop for an introduction to Big Data. Participants have over a dozen elective courses to choose from, including UX/UI, web, database development, several business intelligence options, performance management and evidence-based decision making.	BCIT part-time program so people can continue working (practical);	No	After the electives are completed, two advanced courses in statistical techniques and data analytics are required. Depending on electives, students may be able to complete this BCIT credential with as few as sixteen courses, part-time in the evenings and on weekends.
University of the Fraser Valley, Abbotsford BC	Data Analysis Post-degree certificate	Math and Statistics	1. A Bachelor's degree from a recognized institution. Note: Students currently earning a university degree may enrol in the courses of the Data Analysis Post-degree certificate, provided they meet the course-prerequisites. They will be granted credit for having completed the certificate when they have met its requirements, and have fulfilled the requirements of their degree. 2. One of the following programming courses: COMP 150, Introduction to Programming COMP 152, Introduction to Structured Programming COMP 155, Object Oriented Programming (recommended) 3. Applicants must satisfy the English language proficiency requirement.	10 months - full-time	$3979 Domestic / $16,100 International		UFV's Data Analyis Post-degree certificate builds on the skills and knowledge you have already acquired in your undergraduate degree, allowing you to grow your career within your own field. The combination of your degree background and your data analysis skills can help you grow your career, diversify your professional opportunities, and boost your earnings. As a data analysis student at UFV, you acquire the skills needed to extract reliable information from large data sets. By taking carefully designed courses with the right mix of computing and statistics, you gain the database skills you need to house, extract, manipulate and maintain data. More importantly, you also learn the statistical techniques needed to collect data correctly, assess its quality, analyze it, and turn it into the business intelligence that companies and institutions highly value in the marketplace. The industry standard statistical software environments SAS and R are used throughout.	Enhance your professional skills - General Big Data program - Open to all professionals with an undergraduate degree	no	Required courses: STAT 106  Statistics I (with a B or better) or MATH 270/STAT 270 Introduction to Probability and Statistics STAT 271  Introduction to Data Analysis and Statistical Modelling STAT 272  Statistical Graphics and Languages COMP 230  Databases and Database Management Systems COMP 331/STAT 331  Data Quality STAT 315 Applied Regression Analysis COMP 381  Introduction to Machine Learning or STAT 431/COMP 431 Data Mining Three courses chosen from the following: STAT 330  Design of Experiments STAT 350 Survey Sampling STAT 402 Applied Generalized Linear Models and Survival Analysis STAT 430  Time Series and Forecasting STAT 470 Applied Multivariate Statistical Analysis COMP 380 Introduction to Artificial Intelligence CIS 385 Project Management COMP 430 Advanced Database Topics COMP 455 Extreme Computing
Carleton University, Ottawa ON	Collaborative master’s in Data Science	Faculty of Graduate and Postdoc Affairs - housed in School of Computer Science;  degree in one of six academic disciplines at Carleton, graduating with a specialization in Data Science or a concentration in Business Analytics in the MBA.	Applicants must already be enrolled in one of the participating Carleton Master’s programs. All students must be in good standing in their home discipline. General quantitative ability, as demonstrated by grades in appropriate related courses, based on university transcripts, will be considered.  Honours bachelor degree.	2 years; 16 months for MBA		Enhance your existing career/research program.	Data science is the next frontier of information technology but few universities offer programming in this area. Carleton’s new collaborative master’s in Data Science is geared at graduate students and high-tech professionals who are interested in understanding how to analyze and use ‘big data’ sets collected by governments, industry, NGOs etc. for purposes such as generating personal recommendations for online shopping, improving the efficiency of health care delivery or predicting national security threats.	Combined with other disciplines and with grad courses at University of Ottawa:  Participating programs include:  Biology* (thesis), Biomedical Engineering* (thesis), Business (concentration), Computer Science* (thesis), Economics (thesis or coursework), Electrical and Computer Engineering* (thesis, project or coursework) and Geography (MSc thesis)		Pathway Options: Coursework, Research Project, Thesis. Students take a Data Science Seminar and complete a thesis, if required, or do a project or add'l courses - Computer Science and Electrical and Computer Engineering require 1-2 additional courses.
Ryerson, Toronto ON	Certificate in Data Analytics, Big Data, and Predictive Analytics (one year program and 15-week fast-track)	Offered through Chang School of Continuing Education	Ontario Secondary School Diploma OSSD with six Grade 12 U or M credits (University/college prep courses)	Generally 1 year; 6 courses or Fast-track in 15 weeks	$700 x 6 courses = $4200	.Web Analytics specialist .Data Analyst (in various industry domains) .Data Analytics Project Lead .Data Science specialist .Data Warehouse specialist .Statistical Modeling Analyst .Data Analytics Modeling Analyst .Predictive Analytics Modeling Analyst	Individuals who complete the Certificate in Data Analytics, Big Data, and Predictive Analytics will have gained an in-depth knowledge of, and capacity in, using a variety of databases and data sets to analyze and understand data and predict future eventualities, trends and patterns, as well as be proficient in laying the groundwork, strategies and implementation of decision management in order to substantiate future initiatives that lead to innovation, high performance and sustainable outcomes for success. Target: working professionals, those working in data warehousing.	Meet the requirements of the INFORMS Certified Analytics Professional (CAP®) program.  The Chang School offers several programs to provide proficiency and skills in big data and advanced analytics. Become a DATA SCIENTIST - education in data analytics foundations, basic and advanced analytics methods, and big data analytics tools.	No	1. Industrial Engineering:  Big Data Analytics Tools 2. Computer Science:  Data Access and Management 3. Mechanical Engineering:  Introduction to Big Data Analytics 4. Mechanical Engineering:  Data Analytics: Basic Methods 5. Mechanical Engineering:  Data Analytics: Capstone Course 6. Mathematics:  Data Analytics: Advanced Methods
Ryerson, Toronto ON	Executive programs:  Executive Workshop on Big Data and Advanced Analytics	Offered through Chang School of Continuing Education	No academic prerequisite; but priority to C-level and managers.	2-days	$1,995	For executives and managers.	Designed for executives and senior managers in organizations that use or are exploring the use of big data or advanced analytics. The objective of the workshop is to help participants develop a strong foundation of data literacy that enables them to make strategic decisions, such as how to deploy big data and advanced analytics within their organization and whether or not it is necessary.	Short course for executives and managers	no
Ryerson, Toronto ON	Executive program: Executive Seminar on Privacy and Big Data	Offered through Chang School of Continuing Education	No academic prerequisite; but priority to C-level and managers.	1-day	$895	For executives and managers.	Designed for executives and senior managers who are responsible for their organization’s data privacy. The objective of the seminar is to help participants understand how, as executives and senior managers, they play an essential role in creating an organization that proactively and effectively manages data privacy, particularly in the era of big data and the emerging Internet of Things.	Short course for executives and managers	no
University of Toronto, Toronto ON	Certificate in the Management of Enterprise Data Analytics	Continuing Studies	The programme is open to students with an undergraduate degree or college diploma in business, economics, statistics, organizational dynamics, computer science, mathematics, accounting, finance, computer security, engineering or other fields which are rigorous and encompass both quantitative and qualitative aspects. A minimum of 3 years work experience is very highly recommended, and candidates should have a good fluency not only with computer usage, but with technological concepts in general. A previous course in statistics or probability will definitely be an asset, as well.	Up to 2 years to complete	$1145 x 3 courses min. = $3435 or $1145 x 4 courses =$4580.		Provides learners with the quantitative, technical, business and managerial skills needed to enable organizations to realize these multi-faceted benefits. Designed to address the growing need for qualified analytic managers and business-minded data scientists, each course in this ground-breaking programme considers the mathematical, technological and managerial / organizational aspects of Big Data in parallel and synergistically. This programme will challenge the both business focused and technically minded participants to broaden their horizons, adopt new ways of thinking and embrace the promise of a smarter, better future – a paradigm shift, achievable through data analytics.	Quick and dirty.	No	Courses: SCS 2942 Foundations of Enterprise Data Analytics – Concepts and Controls SCS 2943 Value Proposition and Technologies of Enterprise Data Analytics SCS 2944 Data Management from Enterprise Data Analytics to Data-Based Decision Making SCS 3030 Big Data Tools and Techniques Mining Financial, Operational and Social Network Data (coming Fall 2014) To complete the certificate programme, 2942, 2943 and either of 2944 or 3030 must be completed. Many students take all 4 courses to deepen their knowledge and understanding.