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Data analytics is critical in almost all industries – from business and finance to government and healthcare. This is driving the need for people who can analyze and integrate data into business decision making. Not only does this certificate equip you with that skill set, it also meets the requirements for you to become a Certificated Analytics Professional (CAP®). Toronto Metropolitan University is recognized by an industry leading association, The Institute for Operations Research and the Management Sciences (INFORMS).

Career-Ready Support Offered

While enrolled in the Certificate in Data Analytics, Big Data, and Predictive Analytics (or Certificate in Practical Data Science and Machine Learning), you will receive a variety of supports, including:

  • Educator support: instructors, teaching assistants, and data analytics tutors provide support for your hands-on practice with virtual data analytics lab activities.
  • Synchronous weekly online sessions: in these Zoom sessions, the teaching team, with practitioner-expert, credentialed data scientists as instructors and teaching assistants , addresses learners’ questions and strengthens their hands-on, data analytics skills and working knowledge for future jobs in the field.
  • Discussion forums: the teaching team will monitor discussion forums where learners ask questions on data analytics applied lab activities, readings, video lectures, assignments, and projects.
  • Virtual tutor services: the virtual mentor is offered at no cost upon request to certificate registrants taking courses for one-on-one Zoom meetings and for consultations by email about the coursework, assignments, final projects, and for career advising.
  • Career support: data science job search and career advising will be offered during the final capstone course, CIND 820 - Big Data Analytics Project.
  • Alumni networking support: participating alumni will receive informal career and networking support through LinkedIn to certificate candidates and graduates.

Industry and Careers

This certificate can lead to a career in various roles. Here are some examples:

  • Business analyst
  • Data analyst
  • Data scientist
  • Financial data analyst

Who Should Take This Certificate?

  • Recent graduates or Individuals who want a data analyst or data scientist career and wish to gain the hands-on experience in analytics, coding, tools, and statistics needed to prepare and analyze data to make business decisions.
  • Professionals looking to build their skill set in technically applied data analysis , machine learning, predictive analytics, together with data organization and management to advance in their career or change their career to data analytics
  • Data analysts who want to advance their skills
  • Managers and business leaders who work with data, manage data analytics projects or lead teams of data analysts.

What Will You Learn?

After completing this certificate, you will be able to do the following:

  • Provide a well-refined hands-on education that covers essential skills and knowledge to excel in the data analytics domain, such as understanding data types and structures, data manipulation and cleaning, statistical analysis, data visualization, machine learning techniques, programming languages for querying data, and understand the business context to provide insights and recommendations effectively.
  • Gain insight into the next steps for your entry-level or mid-level data analytics career, and enhance your practical experience in data analytics and machine learning, as well as your knowledge of AI to progress to senior roles within the data science domain.
  • Understand the different types of databases and how to manage and organize them.
  • Use statistics and machine-learning techniques to prepare, model, and analyze data.
  • Use programming languages like R and Python to turn data into insights that can help a business.

Tools in use include the following:

  • R
  • SAS
  • Python
  • Tableau
  • XPath and XQuery
  • Structured Query Language (SQL)
  • Hadoop (MapReduce)

Data Collection and Storage Tools

  • MySQL
  • MongoDB

Analytics Tools

  • Python Libraries for Data Analysis
  • R Packages for Data Analysis 

Integrated Development Environment (IDE)

  • MySQL Workbench
  • RStudio
  • MS-VSCode
  • Robo3T


Certificate Requirements

  • 6 required courses
  • Cumulative grade point average (GPA) of 1.67+

Admission Criteria


  • Ontario Secondary School Diploma (OSSD) or equivalent
    • With 6 Grade 12 U credits (including English, Mathematics (Advanced Functions and one of either Calculus and Vectors or Data Management), and Science (Biology or Chemistry or Physics)) OR M credits with a minimum average of 70 percent or equivalent academic status


  • Mature student status with 4 years of relevant professional experience
    •  And permission of the academic coordinator

Frequently Asked Questions

How long does it take to complete the certificate?

You may choose how quickly you want to complete all six required courses. To complete the certificate in the fastest way possible, students take four courses (CIND 123, CIND 830, CIND 119 and CIND 110) in Term 1, the fifth course (CMTH 642) in Term 2, and the sixth course (CIND 820 - Big Data Analytics Project) in Term 3, to complete the certificate in three consecutive academic terms (Fall, Winter, Spring/Summer), or one academic year.

Note: Courses run every term and typically fill up six weeks before the start of term. Enrol early to avoid disappointment.

Can I take more than one course in the evening and still hold my full-time job?

Yes. It is possible to take more than one course in one term and still hold your full-time job. If you are only able to take two or three courses in Term 1, those courses should be CIND 123, CIND 830, and CIND 119.

In the event that you are unable to take more than one course in Term 1, start with CIND 123, followed in Term 2 by CIND 830, CIND 119, and CIND 110.

If required, you may opt to take CMTH 642 and CIND 110 in Term 3. In Term 4, you would take CIND 820.

Can any of the course requirements be fulfilled by substitution or transfer credit?

The unique and specialized nature of these courses mean that very few, if any, equivalents exist elsewhere. Students should not depend on using prior learning or study elsewhere to meet certificate requirements.

Do course fees change if I am an international student?

Yes. If the course is degree credit, the international fee rate is three and a half (3.5) times the regular student tuition fee. Visit International Students for details.

The following courses are degree credit:

  • CIND 123 - Data Analytics: Basic Methods
  • CIND 110 - Data Organization for Data Analysts
  • CIND 119 - Introduction to Big Data
  • CIND 820 - Big Data Analytics Project
  • CIND 830 - Python Programming for Data Science
  • CMTH 642 - Data Analytics: Advanced Methods

Are there any company affiliations or career placements available as part of this certificate program?

There are no direct corporate associations or career placements available. However, companies and organizations seeking data analysts and data scientists do contact the Program Director with job postings and the postings are emailed out to all students in the sixth and final course, CIND 820 -  Big Data Analytics Project and to recent certificate graduates. The Chang School can provide career search support upon request, such as resumé preparation and one generalized letter of reference for applying to all job positions.

What programming languages are used to teach this certificate?

The certificate is taught using R-language and Python.

What prerequisites or professional experiences are recommended for this certificate?

This is an Open Admissions program. No previous background is required. However, due to the rigorous nature of this certificate, applicants who are wondering if they’re a good match should contact Client Services at ce@torontomu.ca and attach a current resumé.

Are there any specific technical requirements for course work?


Computer requirements for data science courses:

The minimum required RAM on a student’s computer must be 8 GB, but 16 GB is highly recommended for efficient processing for training/testing heavy machine learning algorithms, loading R packages, and using Python libraries. 

For the processor, Apple's M1 Chip, Intel Core i5 or i7 is preferable. 

The storage unit of the student’s computer must be a solid state drive model and needs to be at a minimum 256 GB.  

A PC or MAC computer can be used to operate the technical tools in the data science courses.

What is the process for installing SAS software on my computer? Is there a cost?

SAS is a free virtual application. Visit Toronto Metropolitan’s Computing and Communications Services (CCS) website to download it.

What laptop or tower PC configuration should I have to complete the capstone course?

This checklist will ensure you have the necessary computer and software requirements to complete this course:

  • I have access to a reliable computer with the minimum recommended requirements (dual-core 1.6 GHz or faster processor, 200GB of disk, 8GB of RAM) to use the software in this course (e.g., Python).
  • I have internet access and an adequate data allowance.
  • I can access Google Meet or Zoom and know how to use it.

Each student will be granted access to a virtual desktop equipped with all the tools to complete their project. These virtual desktops will be available until the end of the enrolled term and will be archived by then. Here is a list of tools that will be included in these virtual desktops:

  • Programming Tools: R, SAS, Python, XPath, and XQuery
  • Data Collection and Storage Tools: MySQL, MongoDB
  • Visualization Tools: Tableau
  • Advanced Analytics Tools: Apache Spark, Weka
  • File System: Hadoop Distributed File System
  • Extract, Transform, and Load Tools: Apache Hive, Sqoop
  • Integrated Development Environments (IDEs): Colab/Jupyter notebooks, MS-VSCode, RStudio, MySQL Workbench

Professional Designations and Accreditation

Informs logo

The Institute for Operations Research and the Management Sciences (INFORMS) is the leading association for professionals in the fields of analytics, management science (MS), and operations research (OR).

INFORMS serves the scientific and professional needs of analytics professionals and operations researchers including educators, scientists, students, managers, analysts, and consultants. INFORMS is recognized as the premier organization for advancing the profession, practice, and science of analytics, operations research, and management science.

Toronto Metropolitan University is recognized by INFORMS as a Recognized Analytics Continuing Education Provider. One (1) Data Analytics, Big Data, and Predictive Analytics Certificate course is equal to 39 INFORMS CAP® Professional Development Units (PDUs). CAP® certified professionals are required to earn 30 PDUs every three calendar years.

The following courses are recognized as satisfying the Professional Development Units (PDUs) requirement of INFORMS to maintain your CAP®:

  • CIND 123 - Data Analytics: Basic Methods
  • CIND 110 - Data Organization for Data Analysts
  • CIND 119 - Introduction to Big Data
  • CIND 820 - Big Data Analytics Project
  • CIND 830 - Python Programming for Data Science
  • CMTH 642 - Data Analytics: Advanced Tools

Ownership Statement: CAP® is a registered mark of the Institute for Operations Research and the Management Sciences (INFORMS).

Awards and Financial Aid


Ontario Student Assistance Program (OSAP)
This certificate program is OSAP eligible. To learn more, visit the Student Financial Assistance website.

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Additional Details


You may only select 1 of CIND 110 or CCPS 270.