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Data literacy is critical for a number of industries, and data science is another emerging field in high demand in the job market. From product research and development to infrastructure and finance, the need for a foundation in analytics is growing. Rise to meet the challenges posed by data science, and set yourself up for career advancement with our Certificate in Data Analytics, Big Data, and Predictive Analytics.

Note: This certificate will require 4-6 hours per week of dedicated time to study, including completing virtual data analytics activities and attending the weekly Zoom sessions.

With hands-on learning, this certificate will provide you with a strong foundation in analytics, tools, and statistics. It will guide you in using data analytics, big data, and predictive analytics to optimize performance in fields like data warehousing, data management, IT, and more. Upon completing the certificate, you will be prepared to take the INFORMS Certified Analytics Professional (CAP®) exam to become a certified professional in this new and growing field.

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:

  • Virtual mentor services: the virtual mentor is available free of charge upon request to certificate registrants taking courses for 1-on-1 Zoom meetings and for consultations by email about the coursework, assignments, final projects, and for career advising.
  • Alumni networking support: participating alumni will provide informal career and networking support through LinkedIn to certificate candidates and graduates.
  • Career support: data science job search and career advising will be offered during the final capstone course: CIND 820 - Big Data Analytics Project.
  • Synchronous weekly online sessions: in these Zoom sessions, the teaching team addresses learners’ questions and strengthens their hands-on, data analytics working knowledge for future jobs in the field.
  • Educator support: in addition to the lecture videos and slides as well as an ungraded self-assessment quiz, instructors and teaching assistants provide support for your hands-on practice virtual lab activities.
  • Tutor: learners will be assigned a tutor to help with assignments and lab materials by pre-scheduled virtual appointments.
  • Discussion forums: the teaching team will monitor discussion forums where learners can share their experiences and exchange ideas with each other.

Industry and Careers

The skills taught in this certificate are applicable across nearly all sectors. Whether you wish to enrich your skill set in the following roles, or you are interested in pursuing a new career, this certificate offers opportunities for a variety of career paths:

  • Applied statistician
  • Business analyst
  • Data analyst
  • Data scientist
  • Financial analyst

Who Should Take This Certificate?

  • Individuals who wish to enhance their existing knowledge of data and analytics and learn the fundamental components of the world of big data
  • Employees in both public and private corporations and government entities, who are looking to advance in a job with long-term career prospects

What Will You Learn?

You will gain relevant, timely, and effective education in data analytics foundations, basic and advanced analytics methods, and big data analytics tools. After completing this certificate, you will be able to do the following:

  • Demonstrate fundamental concepts and techniques of big data and its industrial applications
  • Develop analytical and numerical expressions using real problems
  • Apply engineering mathematics and computations to solve mathematical models
  • Know where to take your career next and how to further enrich your knowledge and experience

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+
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Admission Criteria

Recommended:

  • 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

OR

  • 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 the fastest way possible, students take four courses (CIND123, CIND830, CIND119 and CIND110) in Term 1, the 5th course CMTH642 in Term 2, and the Big Data Analytics Project CIND820 course in the third term, to complete the certificate in three straight 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 the fourth term you would take the CIND 820.

Can I substitute one of the courses in this certificate for a different course offered at The Chang School?

No. There are no course substitutions allowed in this certificate program.

Are any of the courses available for substitution or transfer credit?

No. All courses in this certificate must be taken at The Chang School and are not eligible for course substitution or transfer credit application.

Do course fees change if I am an international student?

Yes. If the course is degree credit, the international fee rate is three 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 Tools

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@ryerson.ca and attach a current resumé.

Are there any specific technical requirements for course work?

Yes. 

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

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

Contact Us

Questions? Contact Client Services.

Email: ce@ryerson.ca

Additional Details

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