Data Science Bootcamp

Our streamlined, four-day Data Science Bootcamp will give you an introductory foundation in big data analytics, tools, and statistics. Engaging lectures and hands-on activities will explore data analytics skills and the creation of a road map for completion of a successful analytics project. Participants will focus on complex algorithms for big data, analytics, big data tools, statistics, and machine learning, and be introduced to the following topics:

  • Data science overview
  • Statistical tools for data analysis
  • Data visualization techniques
  • How to create data-driven stories
  • Machine learning methods: supervised and unsupervised
  • Model evaluation, confusion matrices, and ROC curves
  • Programming in R language
  • Data preparation, regression, clustering, and classification in R and Python
  • Big data tools, Hadoop ecosystem
  • Machine learning with Apache Spark
Want to be sure the Data Science Bootcamp is right for you and the goals you want to achieve? Contact Brigid Elmy for a consultation.

Date: Tuesday, October 15–Friday, October 18, 2019
Time: 9:00 a.m.–5:00 p.m.
Location: Ryerson University

Fee: $3,300 + HST. Light breakfast and lunch are provided each day.

Seating is limited, so early registration is strongly encouraged.

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Facilitator

Dr. Ceni Babaoglu is a Senior Data Analytics Associate at The Chang School and a Data Science Instructor at Ryerson University. Since receiving her PhD in Applied Mathematics from Istanbul Technical University, she has worked as a researcher and Mathematics instructor in Istanbul, Sweden, and Toronto. Four years ago, inspired after visiting a Data Science Laboratory – where she learned the practical applications of data analytics and how it involved (her specialty) mathematics – Ceni shifted her focus to data. Her current research is focused on numerical analysis, data mining, and machine learning programming. She is also an associate member of the Yeates School of Graduate Studies at Ryerson University and co-supervises the major research projects of Data Science and Analytics MSc students.

Connect with Ceni on LinkedIn, or visit her website to learn more about her areas of expertise, teaching, and research.

Admission Criteria

There are no academic prerequisites for enrolment. However, please note that participants will be expected to engage in case studies and group discussions and, as such, should have the appropriate level of work experience. This bootcamp is best suited to professionals who need to leverage data analytics, big data, and predictive analytics to optimize performance at various levels in sectors such as private enterprise, government, nonprofit, retail, health care, and technology.

Format

Concepts will be presented using activities, case studies, and data analytics scenarios in a dedicated computer lab.

Testimonials

What are our past participants saying about the Data Science Bootcamp?

“This is what I was looking for… an overview to cover all the major topics, from data cleaning to modelling to predictions, and a feel for the subject matter.”

“The teacher and the TA were amazing.”

“This week has been very informative. I’ve really enjoyed the quality of the sessions and met several learning goals.”

“The guided R labs were useful to apply what we learned in theory to practical problems.”

For More Information

For more information about the Data Science Bootcamp, contact Brigid Elmy, Special Projects Officer, Business Development and Strategic Planning, at belmy@ryerson.ca.