3250A - Using Python I: Organize and Analyze Data
Course Description
To succeed in today’s competitive business environment, organizations must not only collect reams of data but glean the most useful insights from this information. In this five-session micro course, you’ll learn to use Python to organize and analyze data and tell compelling stories your customers and stakeholders understand. You’ll plan your own analytics project, using Python to import data, organize it into a data frame and analyze it correctly. You’ll emerge well equipped to apply these methods at work and become a better business storyteller.
Within 4-6 weeks of successfully completing this course, you will receive your micro-credential indicating achievement of the outlined learning outcomes and competencies/skills. Micro-credentials are tamper proof, verifiable, blockchain-based and 100% digital. They can be shared on social media, including LinkedIn and Facebook, embedded in websites or downloaded as PDFs.
Learning Outcomes
By the end of this micro course, you'll be able to:
- Plan an analytics project.
- Apply basic statistical methods.
- Import data into Python, organize into a data frame and conduct basic analysis.
- Tell a compelling story with data.
Competencies/skills developed in this micro course include:
- Python Programming
- Descriptive Statistics with Python
- Querying Databases with SQL
- Data Analytics
- Data Visualization
- Business Storytelling with Data
Notes
Eligible learners may apply to the Ontario Student Assistance Program (OSAP) for this micro-credential. You can find more information on our Financial Aid page.This course may be applied towards the SCS Certificate(s) in
- Data Science : Required Courses
Reena Shaw has six years' experience across data and analytics, with roles spanning the Supply Chain, Logistics, Marketing and Foot Traffic sectors. Her experience as a Data Scientist, Data Analyst, as well as two years of teaching experience has honed a talent for lucidly explaining technical concepts to a non-technical audience, creative lesson plans, her solution-based approach, and for creating personalized approaches to learning. Reena is a graduate of Queen's University's M.Sc (Computer Science) program with a Thesis in Deep Learning.