LII:Introduction to Data Science

From LIMSWiki
Jump to navigationJump to search
EdX.svg

Title: Introduction to Data Science

Author for citation: Alex Aklson

License for content: Unknown

Publication date: 2024

This is an IBM-created course that is released on the edX platform. The introductory six-week course will have you "meet some big data science practitioners and we will get an overview of what data science is today." The course is free to take. A verified certificate of completion, via a Verified track from IBM, is available afterwards for $99 USD. The class began in early 2024, and the free audit track expires June 24.

The edX course description:

"The art of uncovering the insights and trends in data has been around for centuries. The ancient Egyptians applied census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year. Since then, people working in data science have carved out a unique and distinct field for the work they do. This field is data science and in this course, you will meet some big data science practitioners and we will get an overview of what data science is today."

"What you'll learn:

  • Definition of data science and what data scientists do
  • Tools and algorithms used on a daily basis within the field
  • Skills needed to be a successful data scientist
  • The role of data science within a business
  • How to form a strong data science team"

About the authors

The course is taught by Dr. Alex Aklson, data scientist at Digital Business Group at IBM Canada. "Alex has been intensively involved in many exciting data science projects such as designing a smart system that could detect the onset of dementia in older adults using longitudinal trajectories of walking speed and home activity. Before joining IBM, Alex worked as a data scientist at Datascope Analytics, a data science consulting firm in Chicago, IL, where he designed solutions and products using a human-centred, data-driven approach. Alex received his Ph.D. in Biomedical Engineering from the University of Toronto."


General layout and contents of the course

A syllabus is not made publicly available for this course. edX indicates the course involves 3–6 hours of study per week.

The course

PDF.png: The course can be found on the edX site, under the Data Analysis & Statistics category. A session is live and will run through September 30, 2023. The class began in early 2024, and the free audit track expires June 24.