Foundations in Data Science Bootcamp
Our virtual four-day Foundations in Data Science Bootcamp will give you a solid and engaging introduction to big data analytics, tools, and statistics. Enhance your learning experience with interactive lectures and activities led by expert practising data scientists. Small classes will provide you with the opportunity to interact closely with your instructors and other students. Participants will be provided with access to R and RMD softwares through the Microsoft Azure Platform.
Our next Foundations in Data Science Bootcamp will take place this fall!
Delivery: Fully online (synchronous learning); 22 hours of instruction
Dates: Tuesday, October 12–Friday, October 15, 2021
Time: 9:30 a.m.–3:00 p.m. each day (includes two 15-minute breaks)
Cost: $2,150.00 + HST
Note: No additional software is required.
Register now and secure your spot
Why Should I Participate in This Bootcamp?
- You have no background knowledge in data science and are interested in gaining a better understanding of what it is and how it could be used to enhance organizational goals.
- You do not have a background in data science, but you have basic computational mathematics and numeracy skills; you would like to understand big data science to determine if this is an area you would like to further pursue for upskilling and/or as a career.
- You wish to become comfortable using big data science terminologies and engaging with data scientist colleagues and others with whom you are collaborating on data science projects.
What Will I Learn?
- An overview of data science
- Statistical tools for data analysis
- Data visualization techniques
- Methods for creating data-driven stories
- Machine learning methods (supervised and unsupervised)
- Model evaluation
- Programming in R language
- Data preparation, regression, clustering, and classification in R
- Reframe a business challenge as an analytics challenge.
- Become familiar with statistical concepts and machine learning.
- Demonstrate the fundamental concepts and techniques of data analytics.
- Define basic concepts related to data analytics.
- Discuss the challenges related to big data analytics.
- Identify current trends in big data analytics.
Dr. Ceni Babaoglu is an Assistant Program Director of Data Science at The Chang School and an Associate Member of the Yeates School of Graduate Studies at Ryerson University. Her current research interests include statistical machine learning, data mining, and deep learning. She has partnered with The Globe and Mail, Manulife, St. Michael’s Hospital, and the Toronto Police Service, among other organizations, on research papers in data science. Thousands of students have benefited from the video lectures and online course materials she has prepared for several courses in The Chang School's Data Analytics certificate programs. In addition to teaching data science courses, Ceni supervises students in their big data analytics projects and is the second reader of all MSc data science major research projects.
Dr. Tamer Abdou is an Assistant Program Director of Data Science at The Chang School at Ryerson University. Tamer's primary research area is software engineering, where he mines historical project data and applies artificial intelligence and statistical analysis techniques. His aspiration is to build a pragmatic solution that enables practitioners and researchers to improve and optimize software process quality through an affordable amount of resources. Some of Tamer's research has been conducted in collaboration with industrial sectors and/or adopted by companies such as Mozilla Corporation and IBM CAS Canada. Tamer holds his doctoral degree in Computer Science from Concordia University.
Visit Tamer on Google Scholar for an overview of his recent publications.
Need More Information?
For more information about the Foundations in Data Science Bootcamp, contact Brigid Elmy at firstname.lastname@example.org.