CSE103

Course CSE103
Title Data Science Principles
Credits 4
Course Coordinator Kevin McDonnell
Description

An introduction to the fundamental principles and practices of computer programming and data science. Students use modern computing technology to explore, analyze, and visualize real-world datasets chosen from a variety of sources. Includes weekly computer programming assignments and labs. Intended for students with no prior programming experience. May not be taken by students with credit for CSE 114 or CSE 160.

SBC: TECH
Prerequisite Level 3 or higher on the mathematics placement examination
Course Outcomes
Textbook

There is no required textbook. Some materials are drawn from How to Think Like a Computer Scientist, How to Think Like a Data Scientist, Computational and Inferential Thinking: The Foundations of Data Science and other online resources. Lecture materials and supplementary materials will be provided by the instructor throughout the semester.
Major Topics Covered in Course

Week #

  1. Overview of Data Science; Basic Python: Arithmetic, Variables, Calling Functions
  2. Basic Python: Conditional Execution; Logical Expressions
  3. Basic Python: Lists and Iteration
  4. Basic Python: Dictionaries
  5. NumPy: Arrays and Array Operations
  6. pandas: DataFrames and Basic Table Operations
  7. Introduction to Data Visualization
  8. Exploratory Data Analysis
  9. Causality and Experiments
  10. Random Numbers and Simulations
  11. Distributions and Sampling
  12. Introduction to Machine Learning with SciPy
  13. Linear Regression
  14. Classification
  15. Ethical Considerations

 
Laboratory

3 hours lab
Course Webpage

CSE103