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Course Description

This course introduces basic data science techniques using Python. Students are introduced to core concepts like Data Frames and joining data and they learn how to use data analysis libraries like Pandas, NumPy, and Matplotlib. This course provides an overview of loading, inspecting, and querying real-world data, and how to answer basic questions about that data. Students will gain skills in data aggregation and summarization, as well as basic data visualization.

Earn a SAIT micro-credential 

 

This course qualifies for the SAITMicro badge. Students who successfully complete this course with a final grade of A- (80%) or higher will earn a micro-credential and receive a shareable digital badge. Learn more

Learner Outcomes

Learning Outcomes

Upon completion of this course, you will be able to:

    • Apply basic data science techniques using Python
    • Understand how to load and analyze data
    • Understand and apply core concepts like Data Frames and joining data and use data analysis libraries like Pandas and NumPy
    • Analyze data using statistical functions as well as basic data visualization

Recommendations

CPRG 100 and CPRG 104 or previous working knowledge in Python are strongly recommended prior to taking this course.

Recommended reading (not required):
Python for Data Analysis by Wes McKinney, Oct 2017
Media ISBN: 9781491957660

 

 

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Enrol Now - Select a section to enrol in
Section Title
Python and Data Analytics
Type
Internet Paced
Days
W
Time
6:00PM to 9:00PM
Dates
Sep 07, 2022 to Oct 26, 2022
Schedule and Location
Contact Hours
24.0
Delivery Options
Virtual  
Course Fee(s)
Tuition non-credit $325.00
Service charge(s)
  • Tech Fee ($10)  
Drop Request Deadline
Jul 19, 2021 to Sep 19, 2022
Transfer Request Deadline
Jul 19, 2021 to Sep 19, 2022
Withdrawal Request Deadline
Sep 20, 2022 to Oct 11, 2022
Required Software
JupyterLab – Students will install Jupyterlab using Anaconda IDE with instructors during class https://www.anaconda.com/products/individual#windows
Section Notes

Prerequisites: 
Strongly recommend taking the Introduction to Python Programming course (CPRG 100) and Programming with Python course (CPRG 104) or prior working knowledge of python.

Schedule: 
This course will be delivered virtually using MS Teams & Brightspace/D2L. MS Teams sessions will be held on Wednesdays between September 7 and October 26 from 6:00 pm - 9:00 pm.

We encourage you to use your webcam and microphone to contribute to a more collaborative learning experience. 

Section Title
Python and Data Analytics
Type
Internet Paced
Days
W
Time
6:00PM to 9:00PM
Dates
Nov 02, 2022 to Dec 21, 2022
Schedule and Location
Contact Hours
24.0
Delivery Options
Virtual  
Course Fee(s)
Tuition non-credit $325.00
Service charge(s)
  • Tech Fee ($10)  
Drop Request Deadline
Jul 19, 2021 to Nov 14, 2022
Transfer Request Deadline
Jul 19, 2021 to Nov 14, 2022
Withdrawal Request Deadline
Nov 15, 2022 to Dec 06, 2022
Required Software
JupyterLab – Students will install Jupyterlab using Anaconda IDE with instructors during class https://www.anaconda.com/products/individual#windows
Section Notes

Prerequisites: 
Strongly recommend taking the Introduction to Python Programming course (CPRG 100) and Programming with Python course (CPRG 104) or prior working knowledge of python.

Schedule: 
This course will be delivered virtually using MS Teams & Brightspace/D2L. MS Teams sessions will be held on Wednesdays between November 2 and December 21 from 6:00 pm - 9:00 pm.

We encourage you to use your webcam and microphone to contribute to a more collaborative learning experience. 

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