Data Science Certificate

Develop the Skills You Need to Thrive in a Growing Profession.

Work with industry experts on advanced statistical modelling, machine learning and natural language processing. You'll cover content essential for the toolbox of a predictive analytics professional, including neural networks and deep learning; programming languages and software used in data extraction and analysis; and data security, compliance and privacy issues. The course content covers the 7 domains of INFORMS' Certified Analytics Professional (CAP) certification. You'll also learn how to represent data visually to help decision-makers understand your findings. Whether you work in operations, business intelligence or marketing communications, are a recent math or science graduate, or want to change or advance your career, this certificate will open up the in-demand field of Big Data.

The Certificate is comprised of 4 courses, designed and developed to be taken in order for natural progressive learning. These four courses are 12 weeks in length each and they offer a fully online learning experience, with instructor support and peer networking. It is designed for working professionals who need to fit their learning around a busy schedule. As such, there is no requirement to attend synchronous sessions and you can work on them at a time that is convenient for you to complete the assignments.

You will complete weekly text-based modules in jupyter notebooks (part of the Anaconda distribution), which provide opportunities to practice coding and working with data as you learn. In addition, there may be recorded presentations by Guest Lecturers, who will talk about current issues in the field of Data Science. You will showcase your learning by completing assignments and major projects that are relevant to tasks you need to master as a data science professional.

What You'll Learn

  • Explore the evolution of data science and predictive analytics.
  • Know statistical concepts and techniques including regression, correlation and clustering.
  • Apply data management systems and technologies that reflect concern for security and privacy.
  • Adopt techniques and technologies including data mining, neural network mapping and machine learning.
  • Represent big data findings visually to aid decision-makers.

Need to brush up on your programming skills? Take the Introduction to Python 3 6 week online course.


Note: To increase the security and protection of your uWaterloo account you will be required to enrol in the University's 2 Factor Authentication service (2FA) to gain access to our online learning management system - LEARN.

Required Course(s)
Data Science 1: Foundations of Data Science – next start date: January 25, 2021 and May 17, 2021
Data Science 2: Statistics for Data Science – next start date: January 25, 2021 and May 17, 2021
Data Science 3: Big Data Management Systems & Tools – next start date: January 25, 2021 and May 17, 2021
Data Science 4: Machine Learning – next start date: January 25, 2021 and May 17, 2021

The Data Science courses are offered in sequence because they have a laddered curriculum. We would like you to have a positive learning experience, which can be accomplished by taking the courses in order and one at a time; allowing yourself the time to fully absorb the course material. Please note, if you decide not to take the certificate as designed we cannot offer any special considerations or accommodations should you encounter difficulties.

Students need to commit 10-12 hours per week for each of the Data Science courses. You have three years from the start date of your first course to complete the certificate. Prior Learning Assessment (PLA) may be granted for Data Science 1: Foundations of Data Science.
Important: Upon completion of your certificate requirements, you must request your certificate by submitting a Certificate Request Form.

Online Data Science courses taken through Professional Development at the University of Waterloo will have HST added to the price. A T2022A tax slip is not issued for these courses.

You can withdraw from this course, or transfer to the next start date, up to 14 days after the start date. You must request this in writing ( before 4:30 pm (EST) on the 14th day. Please indicate if you want a refund or a transfer. There is an administrative fee of $75 (+ applicable taxes) for either option.

After the 14th day your only option is to audit the course. This means you will not receive a refund but will retain access to the course materials for the duration of the course and you will not receive a grade.

Lead Instructors
Larry Simon - Mr. Simon is an entrepreneur, management consultant, and angel investor, specializing in IT strategy and data analytics. He has over 30 years of experience advising startups, global corporations, and government institutions. He is the founder and a Managing Director of Inflection Group. Prior to this he was a Partner with Ernst & Young Consulting, their CTO and National Director of their strategy and delivery centres. He has previously served on the faculty of the Rotman School of Management, as the Head Judge of the Canadian Information Productivity Awards (CIPA), and as a Councillor of the Institute of Certified Management Consultants of Ontario. Larry holds an MBA from the University of Toronto and a B.Math (Computer Science) from the University of Waterloo.

Irina Sedenko – Irina has 20 years of experience designing and implementing enterprise solutions, defining IT strategy and go-to-market approaches. She is focusing her expertise on integrated solutions using the entire range of data for business insights. Irina has held senior leadership positions at Accenture where she led delivery of complex multi-release implementations and strategy initiatives for clients. She has led definition and development of content analytics offerings across several industries and applications of the technology. She helped clients to define the business case and solution approach to achieve their business goals. In the last two years, Irina actively participated in the development of the Data Science certificate program at the University of Toronto School of Continuing Studies – and is an instructor for one of the courses of the program. Irina holds an MBA from Queen’s University, and has been an executive board member of the Canadian Chapter of AIIM (the Enterprise Content Management Association) since 2001.

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