The University of Toronto Data Science Masters program will provide you with a strong foundation in both theory and practice, as well as hands-on experience developing data applications. This degree will prepare you for careers in the growing field of data science and analytics.
If you are looking forward to graduate programs in Data science, University of Toronto Masters in Data Science could be the right option for you. There are many diploma, degree and diploma courses available at the university level. However, University of Toronto offers a double major Master program focused on data science analytics. The Program is designed with the aim to equip students with skills that are essential for handling large amounts of data to generate useful information for organizations or companies.
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What is Data Science?
Graduates with a degree in computer science can pursue careers as computer and information research scientists, computer network architects, and computer system analysts. As the demand for new
and better technologies increases, the need for highly skilled computer science professionals is also expected to increase.
The goal of data science is to acquire knowledge from data. The field is rapidly progressing with data collection and processing technologies and has origins in statistics and computer science. Many data scientists are not only involved in the technological aspects of data, but in using data to help guide decision-making.
Our data science concentration offers students an advanced understanding of statistical and computer science methods, vigorous research training and the opportunity to test your knowledge in the real world through our applied research internship.
We invite students from a wide range of disciplinary backgrounds to apply but please know that you must demonstrate a strong background in computer science and statistics – preferably through formal academic training at senior undergraduate level.
ABOUT THE CERTIFICATE
Organizations today need professionals who can extract and analyze extremely large amounts of data – Big Data – and present useful insights to business leaders. If you’re one of them, or would like to be, this certificate program is for you. You’ll come away with the kind of deep analytical skills and abilities that organizations and recruiters value. Work with industry experts on advanced statistical modelling, machine learning and natural language processing.
You’ll cover content essential for the toolbox of a predictive analytics professional, including neural networks and deep learning; programming languages and software used in data extraction and analysis; and data security, compliance and privacy issues. The course content covers the 7 domains of INFORMS’ Certified Analytics Professional (CAP) certification. You’ll also learn how to represent data visually to help decision-makers understand your findings. Whether you work in operations, business intelligence or marketing communications, are a recent math or science graduate, or want to change or advance your career, this certificate will open up the in-demand field of Big Data. This certificate is offered in collaboration with the Faculty of Engineering and Applied Science.
The School of Continuing Studies has partnered with University of Waterloo Professional Development to offer this certificate in an online format. These courses are listed below under Required courses. Registration into the online courses is done through the University of Waterloo. Courses completed online will earn a joint University of Toronto SCS and University of Waterloo PD certificate.
WHAT YOU’LL LEARN
- Explore the evolution of data science and predictive analytics.
- Know statistical concepts and techniques including regression, correlation and clustering.
- Apply data management systems and technologies that reflect concern for security and privacy.
- Adopt techniques and technologies including data mining, neural network mapping and machine learning.
- Represent big data findings visually to aid decision-makers.
Academic Requirements
Ontario Secondary School Diploma
Six 4U/M courses, including:
- Calculus & Vectors (MCV4U)
- English (ENG4U)
University Of Toronto Data Science Masters Requirements
Data Science
Program Requirements
- Completion of four graduate level courses (totalling 2.0 Full Course Equivalents (FCEs)). Two of these MUST be from the Department of Computer Science’s graduate course provision. The other two MUST be from the Department of Statistical Science’s course provision and must include STA2453H Data Science Methods, Collaboration and Communication.
- 1.0 FCE in required courses: Communications for Computer Scientists (CSC 2701H) and Technical entrepreneurship (CSC 2702H).
- An eight-month industrial internship, CSC 2703H. The internship is coordinated by the department, and evaluated on a pass/fail basis.
Masters in Data Science in Canada: Top Universities, Admission Process, Cost, Scholarships, & Job Prospects
Masters in Data Science in Canada is a 10-16 month-long course with an average tuition fee of around 17,000 USD. For an Indian student who wishes to study at data science colleges in Canada, this cost equals around 12 Lakhs INR. Available as mainstream and specialization of Masters in Computer Science, Big Data, or Mathematics. Masters in Data Science is a multidisciplinary field including data cleansing, preparation, and analysis. Studying data science allows the candidate to find actionable insights from large sets of structured and raw data. With MS in Data Science degree in Canada, you can make an average of 70,000-90,000 USD a year.
International students looking forward to pursuing MS in data science in Canada need a score of 73% or more in their bachelor’s, IELTS score (other ELP equivalent tests), and for some universities GMAT scores to get into the program. Merely fulfilling the admission criteria for master’s in data science for Canadian colleges does not ensure guaranteed admission. Hence, applicants must try having impressive SOPs, LORs, and CV to support their application package
Top Universities offering Masters in Data Science in Canada
International students who wish to study Masters in Data Science in Canada can apply to the following top universities:
University | Program | Annual Tuition Fees (USD) | |
---|---|---|---|
University of British Columbia | Masters in Data Science | 33,400 | |
Ryerson University | Masters in Data Science | 17,400 | |
University of Toronto | Masters of Science in Allied Computing- Data Science | 27,000 | |
Carleton University | Masters in Computer Science- Data Science (collaborative masters) | MSDAI- 3,400 MMath- 10,650 | |
University of Waterloo* | MDSAI** and MMath in Data Science | 11,400-16,220 | |
HEC Montreal | MS Data Science and Business Analytics | 20,353-20,730 |
* There are two more specializations available with the University of Waterloo in MMath-Statistics, Data Science and MMath-CS, Data Science. However, admissions to these programs will be discontinued as of winter 2020.
**Masters in data science and artificial intelligence
Courses at Data Science & Analytics Colleges in Canada
When planning to study master’s in data science, you can additionally consider pursuing related degrees. Some of the related degrees for students looking for masters in data science in Canada are as follows:
- MS Computing and Data Analytics: Saint Mary’s University
- MS Big Data Analytics: Trent University
- Masters in Computer Science (Big Data Specialization): SFU (Simon Fraser University)
- Masters in Data Analytics: University of New Brunswick, UWO, and Acadia University.
Some universities like University of Calgary, Sheridan College, McGill University, and others offer various PG diploma programs in Canada in data science.
Why Data Science from Canada?
- The average salary for an entry-level data scientist is around 60,000 USD annually.
- The total number of data scientists has doubled over the past four years and there is still a shortage of around 19,000 professionals according to Canada Big Data Consortium.
- A booming opportunity of around 4 million jobs involving data science in the upcoming 5 years.
- The demand for data scientists is 50% higher than that of software engineers.
By studying abroad in Canada, you choose to study in one of the strongest economies in the world. The country offers you a high standard of living, top-level education, and a welcoming environment to thrive and survive through the duration of your course.
Masters in Data Science in Canada: Course Details
The course duration for masters in data science in Canada is mostly around 1 to 1.5 years. Some universities offer 8 months of on-campus study followed by an 8-months internship. The data science courses in Canada may also be available along with data analysis as a single program.
Data Science vs Data Analytics
Often data science and data analytics are used interchangeably. However, the two programs vary from each other. With a focus on processing and performing statistical analysis on pre-set data, data analysis helps in the communication and visualization of data. Given below is a table addressing other differences between the programs:
Basis of Difference | Data Science | Data Analysis |
---|---|---|
Scope | Macro | Micro |
Major Fields | Machine learning, AI, search engine engineering, corporate analytics | Gaming, healthcare, travel, industries with immediate data needs. |
Goal | Helps in finding the right questions | Helps in finding actionable data |
Data Science vs Big Data
When deciding on which related program to pursue international students may face confusion with his/her choice. Given below is a basic difference in the two fields to help you make a better decision
Basis of Difference | Data Science | Big Data |
---|---|---|
Scope | Micro | Macro |
Major Fields | Machine learning, AI, search engine engineering, corporate analytics | Customer, compliance, financial analysis; data communication and retail |
Goal | Helps in data cleansing, preparation, and analysis | Used to analyze insights for leading to better decisions and strategic business moves. |
Curriculum:
Exploring the data, followed by its schematic preparation. A model or an approach type is selected for finding insights from the data. Around the idea, a model is built and the insights are communicated in a comprehensible manner. The following diagram represents the processes involved in data science and interpretation.
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Figure: Processes involved in data science
Data Scientist Qualifications
For any student who wishes to study a data science course, it is important to note that they must possess the following skills. These help in excelling as a data scientist:
- Mathematics and statistics: Required good grounding in Bayesian statistics, probability, and hypothesis testing.
- Artificial intelligence: Machine learning, natural language processing, and computer vision along with modern computational approach.
- Distributed processing: Knowledge of splitting the large data and processing tasks available to several machines.
- Domain knowledge: Understanding and knowledge of specific domains and applications.
- Formulating problems: Data science involves proposing and testing hypotheses, which requires finding commonalities across what appears to be a different issue.
- Data presentation and visualization: Ability to communicate findings from the data in a readily comprehensible and succinct way.
master’s in data science requirements
university of toronto data science masters requirements
Admission Process for Masters in Data Science in Canada
The admission process for masters in data science in Canada varies from university to university. The admissions are, however, offered mostly for winter, summer, and fall sessions. International applicants are required to have completed 16 years of education for applying for a master’s in data science in Canada.
Where to Apply
International applicants can apply through the official websites of the universities offering the program.
Eligibility Criteria for MS in Data Science in Canada
- Four years of a bachelor’s degree in engineering, computer sciences, business analytics, economics, statistics or related subjects.
- Applicants must have an average GPA of 3.0 on a scale of 4.33. This is equivalent to 73-76% or a B on the grade scale for Indian Students.
- Other university-specific admission requirements are tabulated below:
University | Minimum Eligibility |
---|---|
University of British Columbia | Professional experience (optional but desirable), 65% or 8 on a 10 point scale in UG degree. |
University of Toronto | 77-79% or B+ grade in bachelor’s |
Carleton University | GRE/GMAT score |
Ryerson University | B grade or a score of 73-76% |
University of Waterloo | Average of 78% or B+ grade, 1 year of senior-level experience in statistics or CS. |
HEC Montreal | GMAT- 600, GRE, TAGE MAGE- 300 French language proficiency: TEF/TCF- B2 to C1 level |
Masters in Data Science in Canada Admission Requirements
For admission in masters programs in Canada applicants are required to provide the following documents:
- Transcripts: Applicants are required to submit official transcripts of the previous education. Some institutes may request certified copies of the documents. International applicants must provide certified English/French language translations for transcripts that are not in the English language.
- Proof of Language Proficiency: Proof for English language proficiency must be submitted by international students belonging to non-native English-speaking countries. Applicants can submit test scores from TOEFL, IELTS, and other standardized English language test scores. The minimum test score requirements for the universities are as follows:
University | TOEFL iBT (minimum score) | IELTS (minimum score) |
---|---|---|
University of British Columbia | 100 | 7.0 (band score- 6.5) |
University of Toronto | 93 | 7 (band score- 6.5) |
Carleton University | 100 | 7 (band score- 6.5) |
Ryerson University | 93 | 7 |
University of Waterloo | 100 | 7.5 (band score-7) |
HEC Montreal | 95-114 | 7-8 |
Note: The English language proficiency tests accepted at different universities may vary. Applicants must ensure that the test taken is accepted at the selected university.
- Letter of Reference: LORs may be required for admissions in some universities. Applicants are required to submit around 2-3 LORs in most universities for masters in data science.
- Statement of Purpose/Statement of Intent: Some universities may ask applicants to submit a statement of purpose along with the applications.
- Resume/CV: Applicants may be asked to submit a resume or CV with a detailed academic and work experience along with the application.
Admission Decisions for Masters in Data Science Admissions
Post-application deadlines, the admission decisions are released within a time frame of 6-8 weeks. The applicants for masters in data science in Canada are reviewed on overall academic performance, professional references, and related information available in the CV. The decisions may be delayed in certain cases.
university of toronto data science masters fees
Cost for Studying Masters in Data Science in Canada
For an international applicant planning to study in Canada, the costs for studying can be widely distributed into three categories. These are pre-arrival costs, cost of study, and cost of living. The cost of studying or the tuition fee MS in Data Science in Canada varies from 11,600 USD to 33,000 USD.
Pre-arrival Costs
Given below is a table indicating the one-time major costs involved for an international student planning to study abroad.
Type of Expense | Cost (USD) |
---|---|
Program Application Fees | 76-136* |
Visa Application Fees | 235** |
Health Insurance | 10,000 |
IELTS Fees | 185-190 |
TOEFL Fees | 160-250 |
Airfare | 450-1400 |
*Depends on the university
**150 USD for a Canadian Study Permit and 85 USD is Biometric fees.
university of toronto data analytics master
Masters in Data Science in Canada with Scholarships
There are various scholarships available for international students pursuing masters in Canada. Some of the popular scholarships available to students pursuing MS in Data Science are as follows:
Scholarship | Amount Offered (USD) | University |
---|---|---|
Master of Data Science International Scholarship | 18,874 /year | University of British Columbia |
School of Graduate Studies University-wide awards | 5293.75/semester | University of Toronto |
Ontario Graduate Scholarship | 3781/semester | Carleton University |
Ontario Graduate Scholarship | 3781/semester | Ryerson University |
Ontario Graduate Scholarship | 3781/semester | University of Waterloo |
Entrance Scholarship | Varies | HEC Montreal |
Scholarship Details
Masters in Data Science International Scholarship: University of British Columbia offers an entrance scholarship to its international student enrolling in the master’s program in data science. An amount up to 18,874 USD is offered annually on merit-basis.
The School of Graduate Studies University-Wide Awards: Offered to international graduate students with financial need and academic excellence. The scholarship application is available during winter and the results for the same are announced by July. Applicants must fill in a School of Graduate Studies financial need assessment form for applying.
Ontario Graduate Scholarship: Offered to masters and doctorate international students pursuing an education in Ontario province. Ontario Graduate Scholarship offers an amount of 1,325 USD per year.
Entrance Scholarship: Differential Tuition Fees Exemption is an entrance scholarship offered to newly admitted international applicants for MS programs. The scholarship eligibility and amount is subject to differential tuition of MS programs.
Job Prospects Post-Graduation in Data Science in Canada
Data science is currently one of the explosively growing job sectors in the world. Some of the leading data science careers and median salaries for a postgraduate in data science course in Canada are as follows:
Job Prospect | Median Salary (USD/year) | Job Prospect | Median Salary (USD/year) |
---|---|---|---|
Business Analyst | 78,574 | Sr. Data Scientist | 120,000 |
Business Intelligence Analyst | 77638 | Data Architect | 81,000 |
Business Intelligence Developer | 81945 | Application Architect | 110,000 |
Data Engineer | 120,000 | Machine Learning Engineer | 140,000 |
Data Scientist | 107,500 | Machine learning scientist | 162,625 |
Data Analyst | 60,416 | Data Mining Engineer | 80,673 |
Data Science Course in Canada vs USA
The number of universities offering international students with a data science course is more in the USA in comparison with Canada. Factors to consider for an applicant looking for higher education in data science abroad are as follows:
- School Selection: the USA has a higher number of universities offering data science courses in comparison with Canada. Some of the popular colleges/universities offering data science in the USA are as follows:
- Stanford university
- Carnegie Mellon University
- New York University
- Rutgers University
- University of Washington
- Cost Efficiency: The overall cost of studying in the USA is extremely high in comparison with Canada. This makes Canada a better study destination.
- Job opportunities: With more job opportunities, the USA also has a higher number of applicants looking for these jobs. However, Canada does have a comparatively lesser number of job opportunities but also has lesser candidates.
- Work permit hassle: Getting a Canadian work permit is easier than H1B (work permit for the USA). This plays a major role for applicants who wish to stay abroad post-study.
- Healthcare: Canada offers free healthcare to all individuals legally residing in the country. However, health insurance covers in the USA are expensive and mandatory for studying and working in the country..
- Immigrant friendly: Canada trumps over the USA in this category with its immigrant-friendly laws and welcoming atmosphere.
Masters in Data Science from Canada is a lucrative program of study for graduates of computer science or similar programs. With an abundance of job prospects in the field, a master’s degree in Data Science will not just help you secure high-paying jobs, but also give you an extensive understanding of how various big companies like Amazon and Netflix collect and use data to establish a prominent market.
The possible benefits of a Data Science degree from Canada are manyfold and immense. It is not just businesses that prosper with the application of Data Science, but the customers too. The customers benefit by seeing more relevant content, while businesses prosper by targeting the appropriate audience. As a matter of fact, the proper application of Data Science is capable of uplifting economies and countries alike.