Overview
CS3300/CS6375 Introduction to Python Programming for Data Analytics
Course Summary
Combining data, computation, and inferential thinking, data analytics is transforming how people and organizations solve challenging problems and understand their world. This beginner-focused course is designed for students with no prior Python knowledge who want to learn how to apply programming to explore and analyze data in other fields. In this class, we cover key areas of python programming including lists, functions, loops, conditionals, and some libraries such as Math. We also include essential concepts in data analytics such as question formulation, data collection and cleaning, visualization, and data-driven decision making. Through a strong emphasis on data centric programming, critical thinking, and exploratory data analysis, this class emphasizes key principles and techniques of python for data analytics. These include python for transforming, querying and analyzing data; principles behind creating informative data visualizations; and techniques for common data processing.
Prerequisites: None.
Cross Listing Course
CS6375 Introduction to Python Programming for Data Analytics
Combining data, computation, and inferential thinking, data analytics is transforming how people and organizations solve challenging problems and understand their world. This beginner-focused course is designed for students with no prior Python knowledge who want to learn how to apply programming to explore and analyze data in other fields. In this class, we cover key areas of python programming including lists, functions, loops, conditionals, and some libraries such as Math. We also include essential concepts in data analytics such as question formulation, data collection and cleaning, visualization, and data-driven decision making. Through a strong emphasis on data centric programming, critical thinking, and exploratory data analysis, this class emphasizes key principles and techniques of python for data analytics. These include python for transforming, querying and analyzing data; principles behind creating informative data visualizations; and techniques for common data processing. CS6375 and CS3300 are similar. Graduate students must register for CS6375.
Prerequisites: None.
Course Objectives
After this course, you should be able to …
- Learn the basics of Python programming language.
- Understand the fundamental concepts of data analytics.
- Apply Python programming skills to analyze and visualize data.
- Develop data centric problem-solving skills using Python.
- Work with real-world datasets and perform data cleaning, manipulation, and analysis.
- Gain hands-on experience through coding assignments and projects.
- Build a strong foundation for further studies in data science and/or machine learning.
- Use data analytics to explore and solve problems across different fields.
- Prepare for careers in data analytics, data science, and related fields.
Please refer to the class Schedule for weekly updates and learning objectives. This is the central page for the course, where you will also find the Syllabus, Instructor information, and other study materials. Note that the schedule page is subject to change, and the most up-to-date version will always be posted on the course website. Be sure to check it regularly.
What You’ll Learn
The course content includes but not limited to …
- Introduction to Python programming
- Data types and data structures in Python
- Control flow and functions in Python
- File handling and data input/output
- Data collection and cleaning
- Data visualization techniques
- Data-driven decision making
- Hands-on coding and assignments
- Real-world applications of Python for data analytics
- Best practices in coding and data analysis
- Communication of data insights through reports and presentations
- Critical thinking and problem-solving skills in data analytics