Course details
This hands-on course follows on from COMP 1630 and was designed to introduce Python as a tool for data analytics. Students must have prior database systems and Structured Query Language (SQL) programming, plus have basic Excel spreadsheets skills before registering for this course. Participants must provide their own current model PC with a minimum of an i5 or equivalent processor, 8 GB of RAM and 256 GB storage capable of running Windows 10 or above. High-speed internet access is needed for online sections and homework. BCIT does not provide technical support for student's hardware or operating systems. Starting with an overview of the Python IDE, participants will explore foundational Python programming concepts. Participants are introduced to Variables, Conditions, Operators, Loops, Functions, Arrays, Dictionaries and DataFrames. Exercises and labs explore data analysis using simple statistics with Python. Students are also introduced to string manipulation, Regression, Aggregation, and object-oriented structures with Python used in data analysis. Students are shown how to use Python for basic graphing. COMP 2454 is a required course in the Applied Data Analytics Certificate, ADAC from BCIT Computing. Upon completion successful students will use Python to perform exploratory data analysis and as preparation for data modeling.
Prerequisite(s)
- 60% in COMP 1630
Credits
1.5
Cost
$360.56 - $379.13 See individual course offerings below for actual costs.
Course offerings
Fall 2023
Below are two offerings of COMP 2454 for the Fall 2023 term.
CRN 46632
Duration
Fri Oct 27 - Fri Dec 01 (6 weeks)
- 6 weeks
- CRN 46632
- $360.56
Class meeting times
Dates | Days | Times | Locations |
---|---|---|---|
Oct 27 - Dec 01 | Fri | 18:00 - 21:00 | Online |
Instructor
Lei Zhang
Course outline
Course outline TBD — see Learning Outcomes in the interim.
Cost
$360.56
Important information
- Internet delivery format.
- Departmental approval needed
- Important course information will be sent to you prior to your course start date. Check your myBCIT email account to access this information.
-
Please email cstflex@bcit.ca for Departmental approval. Include your Student number (A0#) and COMP__ and preferred CRN __ and Program Declaration____. Course is 18 hours synchronous online classes. Late registration is not permitted.
Status
CRN 46962
Duration
Fri Sep 15 - Fri Oct 20 (6 weeks)
- 6 weeks
- CRN 46962
- $379.13
Class meeting times
Dates | Days | Times | Locations |
---|---|---|---|
Sep 15 - Oct 20 | Fri | 18:00 - 21:00 | Downtown DTC Rm. 410 |
Instructor
Lei Zhang
Course outline
Cost
$379.13
Important information
- Departmental approval needed
-
Please email cstflex@bcit.ca for Departmental approval. Include your Student number (A0#) and COMP__ and preferred CRN __ and Program Declaration____. Course is 18 hours on campus. This is a BYOD (bring your own device) course, participants must provide their own current model PC with an i5 or higher equivalent processor, 8 GB of RAM minimum, 256 GB minimum storage and high-speed internet access. Late registration is not permitted.
Status
In Progress
This course offering is in progress. Please check this page for other currently available offerings, subscribe to receive email updates or contact us with your comments or questions.
Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Install and set-up Python IDEs.
- Describe fundamental programming concepts using Python.
- Explain how to use and choose appropriate Python data structures.
- Implement fundamental code structures and logic for data analysis using Python.
- Use Python to load, manipulate and prepare structured and unstructured data for modeling.
- Perform exploratory data analysis using Python.
- Report on data using text based and visual statistical summaries using Python.
Effective as of Fall 2021
Related Programs
Python Fundamentals for Data Analysis (COMP 2454) is offered as a part of the following programs:
School of Computing and Academic Studies
- Applied Data Analytics
Certificate Part-time
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