Course Description

Equip yourself with the fundamental knowledge of applied data science. Explore the analytic process, analytic problem-framing, statistics foundation, data preparation, and visualization to optimize organizational performance. Students will gain hands-on experience wrangling data of different types and shapes. Learn how to summarize and derive insight from data through visualization and dashboarding.

The course is designed with comprehensive lab activities and a hands-on mini-project.

This course is delivered in collaboration with WeCloudData.

Course Details

Learning Outcomes

By the completion of this course, successful students will be able to:

  • Apply data transformation on structured data using Python data analysis library Pandas
  • Apply basic statistical analysis and data visualization on structured data using Python’s scientific computing libraries such as Numpy and Scipy
  • Evaluate use cases of data analytics such as cohort analysis, segmentation, visual story telling, etc. in the financial, telecommunications, and SaaS industries
  • Explain the general data analytics processes including the tools and steps required.
  • Learn how the processes can be adapted to different analytics use cases
  • Implement data visualization dashboards with tools such as PowerBI or Python
  • Develop key business performance, opportunities and challenges that help business stakeholders


  • Python Programming Refresher
  • Data Science Workflow
  • Data Wrangling Basics
  • Statistics Essentials for Data Visualization
  • Data Exploration and Visualization with Python
  • Visual Storytelling with PowerBI Dashboard

Who is this course for?

This course is designed for:

  • Business associates, project managers
  • Professionals from every level or industry who work with analytics or data
  • BI/Data analysts who want to go beyond Excel and improve their data handling and visualization skills
  • Recent graduates and academics in Computer Science
  • Individuals who are aspired to pursue career opportunities like Data Analyst, Data Science Analyst, Data Scientist


Software Requirement

To complete the lab activities and mini-project, you will require: 

  • Anaconda Python Distribution or Google Colab


There are no mandatory prerequisites for this course. However you are required to perform a self-assessment to ensure you meet the requirements to enrol.

Self-assessment for enrolment

  • A minimum of 6 months of experience in python programming.

Recommended pre-requisites:

Applies Towards the Following Program(s)

Enrol Now - Select a section to enrol in
Online Synchronous
5:00PM to 8:00PM
Sep 17, 2024 to Oct 15, 2024
Online Synchronous
8:00AM to 4:00PM
Sep 21, 2024 to Oct 19, 2024
Schedule and Location
Delivery Options
Course Fees
Flat Fee non-credit $1,495.00
Required Software
Zoom web conferencing software Laptop or computer installed with Windows or Mac OS Anaconda Python Distribution
Reading List / Textbook
No Textbook Required. 
Section Notes

Classes are held online in real time (Mountain Time) at the specified time and dates.

This course uses:

  • D2L Learning Management System
  • Zoom web conferencing software.

This course is delivered in an online blended format, meaning that some classes are taught in a live virtual session using Zoom, and some work have to be completed in a designated online e-learning platform on your own time.

For the best experience, you will require access to a computer with Internet connection, a headset with speakers and microphone, webcam, and a monitor large enough to display multiple applications (or the use of two monitors). Your computer and internet connection should meet certain requirements. See the recommended requirements.

Students unfamiliar with online learning are encouraged to take our free Digital Skills for Learning Online course.

Unless otherwise stated, notice of withdrawal or transfer from a course must be received at least seven calendar days prior to the start date of the course.

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