DSC 140: Fundamentals of Data Science
Course Materials
Introduction to the Course
- Learning Objectives
- Slides, Lecture Notes, and Code
- Introduction to Data Science (MWF: August 26; TR: August 27)
- Overview of Software (MWF: August 28; TR: August 27 - 29)
- Homework
- Introduction and Excel (Due September 16th by 11:59 pm)
- A set of example solutions can be found here. Note that these are only example solutions and not the only correct answers.
- Introduction and Excel (Due September 16th by 11:59 pm)
Excel
- Learning Objectives
- Slides, Lecture Notes, and Code
- Introduction to Excel (MWF: August 30; TR: August 29)
- Statistics in Excel (MWF: September 4; TR: September 3)
- Slides
- Data Set 1 (pizza dataset.xlsx)
- Data Set 1 Solutions
- Data Set 2 (Fires and Thefts.xlsx)
- Data Set 2 Solutions
- Data Set 3 (factbook.csv)
- Data Set 3 Solutions
- Data Set 1 (pizza dataset.xlsx)
- Lecture Notes
- Slides
- Excel Cleaning and Pivot Tables (MWF: September 6, TR: September 3 - September 5)
- Slides
- Data Set 1 (sales data.xlsx)
- Data Set 1 Solutions
- Data Set 2 (Book Data.xlsx)
- Data Set 2 Solutions
- Data Set 1 (sales data.xlsx)
- Lecture Notes
- Slides
- Projects (MWF: September 9 - September 11; TR: September 10)
- Homework
- Introduction and Excel (Due September 16th by 11:59 pm)
- A set of example solutions can be found here. Note that these are only example solutions and not the only correct answers.
- Introduction and Excel (Due September 16th by 11:59 pm)
Python
- Learning Objectives
- Slides, Lecture Notes, and Code
- Introduction to Python (MWF: September 13 - September 16; TR: September 12)
- Creating a GitHub
- Coding Guidelines
- Slides
- Python Basics (PDF)
- This is a PDF version for quick viewing.
- Python Basics (Notebook)
- This is a Jupyter notebook version that will let you run the Python code.
- MWF In-Class Notebook (Jupyter)
- TR In-Class Notebook (Colab)
- Python Basics (PDF)
- Lecture Notes
- Reading Data in Python (MWF: September 18; TR: September 17)
- Notebooks
- Lecture Notes
- Loops in Python (MWF: September 20; TR: September 17 - September 19)
- In-Class Notebooks
- Statistics in Python and Other Python Libraries (MWF: September 23 - September 25; TR: September 24)
- In-Class Notebook
- Data Set
- Data Cleaning in Python (MWF: September 30 - October 4; TR: October 1 - October 3)
- Machine Learning in Python (MWF: October 11 - October 25; TR: October 15 - October 24)
- Introduction to Python (MWF: September 13 - September 16; TR: September 12)
- Python Projects
- Python Projects Part 1 (MWF: September 25 - September 27; TR: September 26)
- Python Projects Part 2 (MWF: October 7 - October 11; TR: October 8 - October 10)
- Homework
- Python Homework 1 (Due September 30th by 11:59 pm)
- Sample Solutions. Note that there is more than one correct way to solve most of the problems.
- Python Homework 2 (Due October 21st by 11:59 pm)
- Python Homework 3 (Due October 28th by 11:59 pm)
- Python Homework 1 (Due September 30th by 11:59 pm)
R
- Learning Objectives
- Slides, Lecture Notes, and Code
- Projects
- R Projects (MWF: November 6 - November 8; TR: November 7)
- Homework
- R Homework (Due November 11th by 11:59 pm)
MySQL
- Learning Objectives
- Slides, Lecture Notes, and Code
- Projects
- MySQL Projects (MWF: November 18 - November 22; TR: November 19 - November 21)
- Homework
- MySQL Homework (Due November 25th by 11:59 pm)
Additional Topics
- Learning Objectives
- Slides, Lecture Notes, and Code
- Gathering Data from the Internet (MWF: November 25; TR: November 26)
Midterm Exam (MWF: October 16; TR: October 15)
Final Exam (MWF: December 9th at 1:00 pm; TR: December 11th at 8:00 am)
Ethics Report (Due October 7th by 11:59 pm)
More details can be found here
Project Report #1 (Due November 1st by 11:59 pm)
More details can be found here
Project Report ##2 (Due November 26th by 11:59 pm)
More details can be found here
Final Project (Due dates from December 1st at 11:59 pm to December 6th at 11:59pm)
More details can be found here