Through an introduction to Python libraries, students will focus on how the Python programming language can be specifically used for data manipulation, processing and analysis, and visualization.
To be successful in this course, knowledge of the Python programming language is required.
NOTE: Formerly ICT 782 Python Level 2: Python for Data Analysis. Students who successfully completed ICT 782 are exempt from taking ICT 779 Python for Data Analysis.
Python is more than just a programming language. Its flexibility and open sourced language make Python a valuable tool to analyze statistics and shape data for analysis to make informed business decisions.
Course Level Learning Outcomes
By completion of this course, successful students will be able to:
- Design a systematic strategy to examine, manage, and analyze datasets in a specific domain
- Utilize a variety of the Python libraries for performing data analyses
- Prepare data for analysis by effectively combining, cleaning, and transforming datasets
- Import, export, and convert data contained in various file types
- Represent data and analysis results visually and graphically
- Identify use cases for classification and regression techniques
Topics of Instruction
- Introduction to Numerical Python (NumPy), Python Data Analysis Library (pandas), and SciKit-Learn (sklearn)
- Vectorized functions for fast array-based computation
- File input/output for various file types
- Combining, cleaning, and transforming datasets
- Plotting and data visualization with Matplotlib
- Introduction to statistical analysis: classification and regression
Students who successfully completed ICT 781 Python Level 1 are exempt from taking ICT 778 Python Foundations.
- ICT 781 - Python Level 1 (Pass)
- ICT 778 - Python Foundations (Pass)