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Next Cohort: May 7-Jun 18

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Duration

7 weeks

Tuition

$1,137

  Toronto

May 7-Jun 18

Plus 3 other start dates

May 10 - Jun 21 2019

Jun 24 - Aug 12 2019

Jun 15 - Aug 6 2019

Commitment

Part-Time

Delivery

Classroom

Year Founded

1948

Scholarships

no

This course is an introduction to learning big data tools such as Hadoop and advanced SQL techniques. Students will gain a clear understanding of Hadoop concepts and technologies landscape and market trends. They will construct SQL queries of moderate to high complexity to retrieve data from a relational database. Note: Tools taught include Hive, Pig, Oozie, LAMBDA, Gigraph and GraphLab.

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Next Cohort: May 7-Jun 18

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Student Reviews (3)

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

Great program in data analytics for business professionals

Toronto •

Graduated From

Data Analytics Fast Track

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 Fast Track

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 compl...

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.

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