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for 12 weeks

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for 14 weeks

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About

The G. Raymond Chang School of Continuing Education, Ryerson University

The G. Raymond Chang School of Continuing Education at Ryerson University is a leader in innovative, quality, lifelong learning that empowers adults to reach their life and career goals.

We are proud to be Canada’s largest, most successful continuing education program, with approximately 70,000 enrolments each year. What brings people here? Five key elements: superior and innovative programming; teaching staff who are thinkers and practitioners; connectedness through partnerships; a community of motivated students; and our collaborative model.

Student Reviews (4)

The G. Raymond Chang School of Continuing Education, Ryerson University

Certificate in Data Analytics

Graduated From

Data Analytics Fast Track

Overall:

5 out of 5

Instructors:

5 stars

Curriculum:

5 stars

Job Assistance:

5 stars

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 throug...

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.

The G. Raymond Chang School of Continuing Education, Ryerson University

Great program in data analytics for business professionals

Toronto •

Graduated From

Overall:

5 out of 5

Instructors:

5 stars

Curriculum:

5 stars

Job Assistance:

5 stars

Excellent instructors who are at the top of their game in the industry. Good balance of theory and applied learning, including hands-on exercises with SQL, Spark, and Hadoop. Recommended for newcomers to the field who already have a business background...

Excellent instructors who are at the top of their game in the industry. Good balance of theory and applied learning, including hands-on exercises with SQL, Spark, and Hadoop. Recommended for newcomers to the field who already have a business background.

The G. Raymond Chang School of Continuing Education, Ryerson University

Data Analytics at the Chang School

Toronto •

Graduated From

Data Analytics

Overall:

5 out of 5

Instructors:

5 stars

Curriculum:

5 stars

Job Assistance:

5 stars
This program offers a good introduction to statistics, data science, data management, working with large data sets, analytics theory and big data tools. As someone who hasn't coded for 10+ years, I was able to pick it up pretty quickly and complete all...
This program offers a good introduction to statistics, data science, data management, working with large data sets, analytics theory and big data tools. As someone who hasn't coded for 10+ years, I was able to pick it up pretty quickly and complete all of the coding via what was taught in the class or tutorials/lab sessions. The program has exposed us to most of the standard tools: SQL, RegEx, R, Watson, Hive, Pig, Spark, Hadoop, etc.. Also, you get exposure to analytics methodologies (clustering, regression, decision trees, machine learning). The program has been a mix of theory and more practical learning - which helps ensure you really understand the purpose of the tool or method and how to apply it to real-world or business problems. The program has been a great way for me to build up my knowledge and expertise in big data and machine analytics. I am not a full-time technologist, but work with many, and we now have a common language and tool set to problem solve with together. This course would also be a great complementary skill set for someone who is already a technologist or already a data analyst who could then take what they learned and build more depth on it through their professional activities.