Master of Science in Data Science and Analytics
4.4 /5
- Public University
Yeates School of Graduate Studies
Talk to ExpertMaster of Science in Data Science and Analytics at Toronto MU Overview
The Toronto Metropolitan University offers a really good Master of Science in Data Science and Analytics program at the PG level, which lasts for 1 year. To get admission to the program, students must meet the requirements for the course which include having a valid score on tests like IELTS, TOEFL and PTE. The Toronto Metropolitan University tuition fee for the first year of the Master of Science in Data Science and Analytics is CAD 25,740 (INR 1,773,743). Also, the students should budget well for living expenses, which has:
- Accommodation (rent or hostel)
- Food
- Books
- Other important utilities
Duration | 1 year Get Curriculum |
Tuition & Fees | ₹17.46 Lakh Get Fees details |
International Students Admission Website | Go to Website  |
Official Career Service Website | Go to Website |
Course Level | PG Degree |
Master of Science in Data Science and Analytics at Toronto MU Fees
When planning for the Master of Science in Data Science and Analytics, applicants should consider the financial aspects involved. Every student must pay the first-year tuition fee of CAD 25,740 (INR 1,773,743). Additionally, it is also important to account for living expenses such as accommodation, food, and utility costs. Such expenses may vary according to living styles and other fees added by the Toronto Metropolitan University. However, accordingly to the official website the average cost of living that international students have to bear is CAD 15,435 (INR 1,063,626), annually. To know about the complete breakdown of the Toronto Metropolitan University Master of Science in Data Science and Analytics fee structure and all other cost-element-wise expenditures for an elaborate cost overview, please check the table below.
1st year tuition fees | Fees components | Amount (for 1 year) |
|---|---|
| Tuition & fees | INR 17,46,024 |
Other expenses in 1st Year | Fees components | Amount (for 1 year) |
|---|---|
| Hostel & Meals | INR 10,47,004 |
| Insurance | INR 51,282 |
Calculated at the exchange rate of 1 CAD = INR 67.833084 | Tuition & expenses were last updated on 17ᵗʰ July 2025Master of Science in Data Science and Analytics at Toronto MU Curriculum
Students who wish to learn more about Toronto Metropolitan University Master of Science in Data Science and Analytics program can simply click the green button below. The curriculum PDF contains all essential details, including course structure, electives, specializations, and duration. Additionally, it provides a semester-wise breakdown, making it easier to understand the overall program layout.
Download exam sample paper
Master of Science in Data Science and Analytics at Toronto MU Entry Requirements
- No specific cutoff mentioned
- No specific cutoff mentioned
- CGPA - 3/4
- Read less
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Applicant must have a four-year bachelor’s degree (or equivalent) from an accredited institution in engineering, science, business, economics or a related discipline
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Applicant must have a minimum grade point average (GPA) of 3.00/4.33 (B or equivalent), in the last two years of study and demonstrated capacity to succeed in graduate studies
- Prerequisite courses :
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Data Analytics: Basic Methods
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Data Organization for Data Analysts
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Python Programming for Data Science
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- Indian Requirement for the Equivalency of B or equivalent :
- 8.0/10 or 65% Grading practices and scales vary considerably. Refer to the grading scale published by your University
-
Calculate your score and check your eligibility at over 2000+ universities.
Out of 10
Calculate your score and check your eligibility at over 2000+ universities.
Out of 10
- Marks - 93/120
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Register for TOEFL iBT® Test Today and get Rs 500 Off. Use code SHIKTOEFL to avail the discount. Hurry Register now for TOEFL
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- Marks - 63/90
NA
- Marks - 7/9
- Get a Full FREE IELTS Prep Course with Shiksha Study Abroad – Limited Seats for Weekend & Weekday Batches! Register now for IELTS
Master of Science in Data Science and Analytics at Toronto MU Frequently Asked Questions
Master of Science in Data Science and Analytics at Toronto MU Application Process
- Two letters of recommendation are required for each application. The recommendations should be from academic referees – former professors or research supervisors familiar with applicant’s academic abilities.
- Applicants are required to submit an updated CV/resume and, in their statement of interest, highlight how their previous studies and experiences have prepared them for graduate studies at Toronto Metropolitan University. Please be sure to include all relevant work experience and publications.
- Official Transcripts
- A copy of Passport
- Proof of English Language proficiency
- Statement of Interest should be no more than 500-1000 words and should address the following:
- Demonstrate working knowledge of statistics, data structures and algorithms, databases, and R software packages. Please identify any courses in your transcript(s) that may cover these subject areas.
- How students’ previous studies and experience have prepared them for the program
- How this program relates to students career objectives
- Students who can demonstrate temporary financial hardship may be granted a short payment plan not to exceed one term or four months in length
Master of Science in Data Science and Analytics at Toronto MU Rankings
| Rank | Rank Publisher |
|---|---|
| #301 | |
| #301 |
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Master of Science in Data Science and Analytics at Toronto MU Highlights
- This unique Master of Science (MSc) degree program enables students to develop interdisciplinary skills, and gain a deep understanding of technical and applied knowledge in data science and analytics
- Graduates are highly trained, qualified data scientists who can go on to pursue careers in industry, government or research
- The program is offered as a one year full-time or two year part-time MRP option and two year full-time Thesis option
- The MSc in Data Science and Analytics is delivered in both lecture-based and hands-on lab learning environments where students can develop and apply their skills to complex, real-world datasets and data science and analytics problems
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