Attend Our Online Information Session

Dates:
Friday, November 29, 2019
Friday, February 28, 2020

Time: 12:00 p.m.–1:00 p.m. EST

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Data analytics, big data, and predictive analytics domains are recognized as having significant and growing societal importance to organizational performance.

They are becoming essential to:

  • the research and development of products and services
  • communication with clients and customers
  • commerce
  • finance
  • public utility and infrastructure
  • law enforcement
  • government institutions

This certificate will provide you with a strong foundation in analytics, tools, and statistics. It will help you use data analytics, big data, and predictive analytics to optimize performance in fields like data warehousing, data management, IT, and more. It may provide you with the necessary credentials for career promotion or other professional enrichment.

This certificate program is offered through in-class delivery, in on-campus computer labs and video lectures. No previous background is required. You may also choose to complete the certificate program in an accelerated format. See Fast Track Options below for more details.

Upon successful completion of this certificate, you will be prepared to take the Institute for Operations Research and the Management Sciences (INFORMS) Certified Analytics Professional (CAP®) exam to become a certified professional in this burgeoning field. See Professional Designations and Accreditation below for details.

What Will You Learn?

Gain relevant, timely, and effective education in data analytics foundations, basic and advanced analytics methods, and big data analytics tools.

Learn how to:

  • 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.
  • Understand next-generation big data platforms such as Apache Spark.
  • Know which direction to go next and how to further enrich your knowledge and experience.

Programming Tools

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

Machine Learning

  • IBM Watson
  • Weka

Data Collection and Storage Tools

  • MySQL
  • MongoDB

Advanced Analytics Tools

  • IBM Watson
  • Apache Spark

File System

  • Hadoop Distributed File System

Extract, Transform, and Load Tools

  • Apache Pig
  • Apache Hive

Integrated Development Environment (IDE)

  • MySQL Workbench
  • RStudio
  • Studio3T

This certificate provides training on cutting-edge technology to enrich skills you may already possess as a data analyst.

Who Should Take This Certificate?

This certificate is intended for individuals who want to enrich their knowledge and learn the fundamental components of the world of big data. This includes current and aspiring employees in both public and private corporations and government entities.

You may be interested if you currently hold or wish to hold the following job titles:

  • Data Scientist
  • Data Analyst
  • Financial Analyst
  • Applied Statistician
  • Business Analyst

Who Teaches the Courses?

Our instructors are selected through a highly competitive process and are expert practitioners and highly skilled academics in industrial and research sectors.

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Fast Track Options

If you want to fast-track your certificate, you have two options.

Option 1:

Data Analytics Fast Track (CKME 995) allows you to complete four of the six courses in the Certificate in Data Analytics, Big Data, and Predictive Analytics in a condensed format and access specialized material and instructor support. The fifth and sixth courses, CIND 719 - Big Data and CKME 136 - Data Analytics: Capstone Course, can be completed online in a subsequent academic term of your choosing.

Option 2:

With the Data Analytics Fast Track (CKME 999), you can complete five of the six courses in the Certificate in Data Analytics, Big Data, and Predictive Analytics in an accelerated format and the sixth course, CKME 136 - Data Analytics: Capstone Course, is completed in a subsequent academic term.

Virtual Data Analytics Tutor

In addition to your instructors, you will have access to an online virtual tutor for help with out-of-class assignments and course material: dataanalyticstutor@ryerson.ca.

Industry and Careers

The skills taught in this certificate are applicable across almost all sectors.

In particular, these skills are especially useful for those aspiring to be or are already working as:

  • Data Scientists
  • Data Analysts
  • Financial Analysts
  • Applied Statisticians
  • Business Analysts

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.

Ryerson 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 719 - Big Data Analytics Tools
  • CMTH 642 - Data Analytics: Advanced Tools
  • CKME 136 - Data Analytics: Capstone Course

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

Recommended Course Sequence

We recommend you complete courses in the following order:

Term 1

  • CIND 123 - Data Analytics: Basic Methods
  • CIND 119 - Introduction to Big Data
  • CIND 110 - Data Organization for Data Analysts

These three courses are delivered in-class. They cover a foundational level of the seven knowledge clusters and technical skill sets (from the INFORMS CAP exam) for big data analysis. You can take them concurrently in any combination in the same term or multiple terms. They are each offered on a different day of the week every term, to allow you to take them concurrently. You are encouraged to take CIND 123 and CIND 119 concurrently if you are not able to take all three courses at once.

Term 2

  • CMTH 642 - Data Analytics: Advanced Tools
  • (And CIND 110 if you didn’t take it in your first term)

Option 2:

  • CIND 719 - Big Data Analytics Tools
  • CMTH 642 - Data Analytics: Advanced Tools (if you have already completed CIND 110, 119 and 123).

These three courses are delivered in-class. CMTH 642 and CIND 719 cover the seven knowledge clusters and technical skills (from the INFORMS CAP exam) of big data science analysis at an advanced level. CMTH 642 must be taken after CIND 123 and CIND 119, and it may be taken concurrently with CIND 719. CIND 719 can only be taken after you have completed CIND 110 and CIND 119. If you choose not to take CMTH 642 and CIND 719 concurrently, CMTH 642 may be taken before CIND 719.

To obtain departmental consent for CMTH 642 and CIND 719, please submit a Request for Deparmental Consent or email Anne-Marie Brinsmead, Program Director, at a2brinsm@ryerson.ca. Indicate which term and what night(s) of the week you wish to take each course and your student number. Please also list all of the courses in the certificate you will have completed before the start of the course for which you require departmental consent.

Term 3

  • CKME 136 - Data Analytics: Capstone Course

This capstone course is completed off-campus with online access to your assigned instructor by pre-scheduled appointment, via video message, phone, and email. The capstone course may only be taken after the other five courses have all been completed. To obtain departmental consent for CKME 136, please submit the Request for Departmental Consent.

This is a project completion course on large publicly available data sets. You will be required to come up with a maintainable solution written in either R or Python. You will graduate with a completed project for your career portfolio that you may send to potential employers and present verbally at interviews.

Note: You can choose to complete the certificate at your preferred pace. Some students take two to three courses every term and the capstone course in the third term, to complete the certificate in three consecutive academic terms (Fall, Winter, Spring/Summer).

Testimonials

Mohammed Karim“The Chang School’s Certificate in Data Analytics, Big Data, and Predictive Analytics has given me a unique combination of essential, hands-on skills that allows me to excel in this competitive field. I was able to make professional connections through my courses, both with my classmates and my instructors, who are working subject matter experts. The program allowed me to build on my computer science degree and focus on big data tools and applications. I was looking to enter a field I was passionate about and to get a job I loved doing, and the skills and knowledge I gained from this program have been at the core of my career success.” – Mohammed Karim


Joanna Kader“Since I emigrated from Syria, Ryerson has been the university that welcomed me and offered the right continuing education courses to Canadianize my skills and restart my career in Canada. When Ryerson announced the Data Analytics, Big Data, and Predictive Analytics program, I jumped at the opportunity and was not disappointed. Before I graduated from the program, I was offered a position as a Director with an innovative IT company looking to start its Big Data department. Now I work in Anti-Money Laundering and Anti-Terrorist Financing, Data and Analysis as Product Owner in one of the largest banks in Canada. The Chang School prepared me to start this career and taught me how to be curious and continuously learning.” – Joanna Kader


Mai-Huong Vo“I took the in-class program and I am glad I did. I truly enjoyed the interactions with my classmates, TAs, and instructors. They were all very personable and helpful. For instance, one of my classmates was a professor at top Canadian university. Our discussions were topical and progressive. We discussed how Big data, for example, could potentially be used to improve our healthcare system. The Chang School program is thoughtfully designed to focus on active ways of learning. The lab-work and assignments were based on real life scenarios and incorporated case studies with real datasets.” – Mai-Huong Vo


“The courses are great, and the teachers and the TA help us learn. Thank you to the certificate team for giving us all the information and help we need to succeed in this program, in class and professionally, by reviewing our resumés and more!” – Simon Atron


“I took the Certificate in Data Analytics, Big Data, and Predictive Analytics because I wanted to open my mind to new ways of thinking and expand my skills with the latest data science developments, concepts, and methodologies. I had the opportunity to network with academics and professionals in the data science sector. I gained a demonstrable proficiency of basic data science concepts, as well as an understanding of methodologies and syntaxes. These skills have built on my MBA degree and expanded my critical thinking.” – Kim, Graduate, 2019


Data Science Bootcamp

Are you looking for some general data science training for your company’s leaders?

Consider our four-day Data Science Bootcamp.

Master of Science (MSc) in Data Science and Analytics

Some courses from this certificate partially fulfill the prerequisite course requirements for Ryerson University’s Master of Science (MSc) in Data Science and Analytics.

For more information please email datascigrad@ryerson.ca.

Big Data Consortium Reports

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. Some students take two to three courses every term and the capstone course in a third term, to complete the certificate in three straight academic terms (Fall, Winter, Spring/Summer) or one academic year.

NOTE: Courses run every term. Courses typically fill up six weeks before the start of term, so 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 evening course and still hold your full-time job. If you are only able to take two courses in the first couple of terms, those courses should be CIND 123 and CIND 119. In the event that you are unable to take more than one course, start with CIND 123.

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 (3) 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 719 - Big Data Analytics Tools
  • CMTH 642 - Data Analytics: Advanced Tools

Who is the target audience for this certificate?

This certificate is intended for current or aspiring adult professionals who have an interest in the subject for career advancement. Employers seek data analysts and data scientist who come from a wide range of interdisciplinary educational and professional backgrounds. A strong commitment to brush up on high school geometry, linear algebra, and computational math is recommended while taking courses in this certificate.

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, CKME 136 - Data Analytics: Capstone Course 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 Anne-Marie Brinsmead, Program Director, at a2brinsm@ryerson.ca. It is advised that you attach your current resumé.

Are there any specific PC requirements for course work?

No. We understand that not everyone has a laptop with at least 16 GB of RAM to bring to class; consequently, we have lab sessions for each course where you can use the university’s dedicated Big Data Analytics facilities. However, there will be assignments that you will need to work on during your own time, either by using the university’s computers or your own.

Open Lab Hours are scheduled for you to complete assignments outside of class during the day and from 4:30 p.m.–6:30 p.m., Monday to Friday.

All of the software used will be open source, so you will be able to download it from the Internet.

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

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

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

You will need a PC laptop or PC computer (no Mac OS or Apple products) with:

  • Operating system: Windows 10; 32-bit or 64-bit
  • Processor: Intel®Core™i5-3230M CPU @ 2.60GHz
  • Installed memory (RAM): 16 GB (15.9 usable) (NOTE: You need 16 GB to run Hadoop.)

Which textbooks must I purchase for this certificate?

You will receive your textbook information in your course outline in the first week of class. Please do not purchase any textbooks in advance.

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

Awards and Financial Aid

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Contact Us

Questions? Contact Anne-Marie Brinsmead, Program Director, Engineering, Architecture, and Science.

Phone:  416-979-5000, ext. 2665
Email:  a2brinsm@ryerson.ca

Additional Details

Courses

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