CSC 405/605/705 - Spring 2026 – Schedule

The following gives a day-by-day breakdown of topics covered, readings assigned, and assignment handouts/due dates.

The schedule in this class is flexible, and past dates will be updated to reflect what was actually covered. Future dates are always tentative and subject to change. Slides, assignments, and the associated reading materials will be posted as the course progresses.

Day 1: Monday, January 12

Topic 1: Course Information Slides

Topic 2: Introduction of Data Science Slides

Day 2: Wednesday, January 14

Preparation: Students must have a Python environment installed before class, including pip. Installing Jupyter Notebook in advance is also recommended.

Topics: Jupyter Notebook Slides Demo

No class on Monday, January 19 – Dr. Martin Luther King Jr. Holiday

Day 3: Wednesday, January 21

Preparation: Students must install Git before class. Please ensure Git is working by running ‘git –version’ in the terminal.

Topics: Using Version Control with Git Slides Readings

Day 4: No class on Monday, January 26 - Winter storm

Day 5: Wednesday, January 28

Topics: Re/Introduction to Python 1: Basic syntax, keywords, variables, and data types, Numerical operations, conditional statements, loop controlSlides Demo1Demo2

Day 6: Monday, February, 2

Assignment: You can start Assignment 1

Topics: Re/Introduction to Python 1: in-class exercises Code

Day 7: Wednesday, February 4

Topics: Re/Introduction to Python 2: Using Python to read from and write to files (TXT and CSV files) and perform basic operations Slides Demo

Day 8: Monday, February 9

Topics: Introduction to Pandas: Series and DataFrame Slides Demo

Day 9: Wednesday, February 11

**Topics: ** Using Pandas to read from and write to files (CSV and Excel files) Slides Dataset used in class Pandas API Demo

Day 10: Monday, February 16

Assignment: Assignment 1 due

Topics: Clean datasets using Pandas, including removing missing values, outliers, duplicates, and inconsistent data formats. Slides Dataset used in class

Project: Students can begin the dataset cleaning task for the final project.

Day 11: Wednesday, February 18

Topics: Slides and Demo continued from last time. Demo

Day 12: Monday, February 23

Project: Students should have completed Project Stage I: dataset selection, problem identification, and data cleaning.

Topics: Introduction to NumPy, understanding and create ndarray. SlidesExercise in classDemo

Day 13: Wednesday, February 25

Topics: Introduction to NumPy’s basic functions, such as slicing, indexing, reshape, split, and resize, as well as basic math and arithmetic functions. Slides Demo

Day 14: Monday, March 2

Topics: Introduction to Statistics in Data Science, such as Basic Terminology, different types of Statistical Methods, Statistical Measures. Slides

Day 15: Wednesday, March 4

Review: Review Summary

Quiz 1

No class on March 9 – March 13 (Spring break)

Day 16: Monday, March 16

Topics: Introduction to Statistics in Data Science: probability foundation. Slides

Day 17: Wednesday,March 18

Topics: Introduction to Statistics in Data Science: distributions for continuous variables and discrete variables. Slides

Day 18: Monday, March 23

Day 19: Wednesday, March 25

Day 20: Monday, March 30

Day 21: Wednesday, April 1

Day 22: Monday, April 6

Day 23: Wednesday, April 8

Day 24: Monday, April 13

Day 25: Wednesday, April 15

Quiz 2

Day 26: Monday, April 20

Day 27: Wednesday, April 22

Day 28: Monday, April 27

Topics: Presentation for Final Project

Day 29: Wednesday, April 29

Topics: Presentation for Final Project