Will Edwards
IT Instructor: Data Science | Data Analysis | Artificial Intelligence
Will Edwards is an instructor at Futuretek Academy. He teaches a courses on Data Analytics, Data Science, and Artificial Intelligence. Topics include data visualization and inferential statistics, mastery of PostgreSQL, and Python from beginner to advanced including sophisticated web-scraping and building applications with the latest AI. Will's graduates include seasoned software engineers, project managers, data professionals and alumni from some of the most elite schools in the world.
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As a Data Science Consultant, Will has provided his expertise to NGOs and private companies on projects ranging from leading edge medical research to building effective data pipelines so that tedious tasks are automated. Will has previously tutored various STEM subjects at a secondary and post-secondary level including calculus, statistics, and the quantitative section of the GMAT.
Career
2023 - Present
Futuretek Academy
IT Instructor:
In Will's time as an Instructor, he has helped 200 participants graduate into Data Science and Analysis jobs.
2021 - Present
Varsity Tutors
Tutor:
Will tutors Data Science, Python, Calculus, Statistics and the GMAT quant section. Students range from high school to graduate school and working professionals including students and alumni from top schools.
2017 - Present
Bright Tapestry Data
Founder:
In July of 2017, Will started Bright Tapestry Data, doing Data Science consulting for professional researchers and institutions including MDs, and I/O Psychologists using a tech-stack focused on Python and R.
2020 - 2021
in-House
Consultant:
In this role, Will led a team of student-interns and worked on company projects related to data science and data engineering, including market research, and improving, troubleshooting and maintaining internal company tools and applications.
2014
Canadian Cancer Society
Research Officer:
In this position, Will built a prospect identification model, and a system for targeting high-net-worth neighborhoods with greater reliability. Techniques used were multivariate regression, PCA, t-tests, and Monte-Carlo methods.