Joanna Bieri

Applied Math Professor

Department of Economics

University of Redlands

Introduction to Data Science
Fall 2025

Office Location:
Duke Hall #209
Phone: 909-748-8630
E-Mail: joanna_bieri@redlands.edu
(Email or Teams are my preferred contact methods)

Data Science Lab:
TBA

Office Hours:
Click here for my schedule.
You can also email me for an appointment!

Link to our Canvas - for submitting work and checking grades:
Class Canvas

Check out Data Science in a Box - Intro to Data Science - using R.
Our course follows much of this content and thus is licensed under Creative Commons Attribution-ShareAlike 4.0 International.



• Important Course Documents
  
  Course Syllabus
  
  Schedule of Topics
  NOTE: as the semester progresses we may change up the schedule a bit to suit our class pace and interests. The most recent schedule will be posted here.
  
  
  Link to our GitHub - for getting assignments and version control
  
  
  Final Project Proposal - DUE FRIDAY 11/10/25 - Here is info about the proposals and final project:
  Final Projects
  
  Cheat Sheet of Commands 1
  Cheat Sheet of Commands 2
  Video - Common Errors in Python
  
• Daily Assignments - Reading - Handouts
  
  Each day I will post the lecture videos, homework, reading, and other information. Make sure to check here for each day of class.
  • Day 1 - Wednesday - 9/3 - Computer Setup
    
    The overall goal of this class is to engage in curious exploration. Please be patient with yourself and others! Along the way you will learn how to make pretty graphs, some basics of programming in python, and how to think like a Data Scientist.
    
    PRE-CLASS:

    Each class day will have content that you should explore before class. I build my lectures, labs, and discussions assuming that you have done the work before class. Each day you will submit what you have completed before class. It does not have to be perfect, but it must show your attempt to engage in the material.
    
    ** If you are one to leave tabs open, remember to occasionally refresh the page!

    CLASS TIME:

    Each class will have daily in class content.
    Notes - What is Data Science?
    Slides - What is Data Science?
    Notes (how to) - Set up your computer (important that this is done this week)
    Remember to pull the class files to your local machine and make a copy in your working directory!

    ANNOUNCEMENTS:

    Start Prepping for Day 2 - click on the Day 2 link and complete the PRE-CLASS materials.

    
    
  • Day 2 - Monday - 9/8 - Hello World
    
    PRE-CLASS:

    Video: How to be Successful This video is to walk you through being a successful student in this class.
    Notes - Hello World!
    Video: Hello World!
    Remember to pull the class files to your local machine and make a copy in your working directory!
    Take the quiz on Canvas!
    
    Video: How to Canvas This video is to walk you through how to take quizzes and submit homework in the class. It answers the questions:
    -- How do I submit a GIT link (Day2)
    -- How do I find my .ipynb to drag and drop onto Homework 1
    ** If you are one to leave tabs open, remember to occasionally refresh the page!

    CLASS TIME:

    Slides - Hello World - Our first data science exploration!
    Time to work on homework
    Get help with technology
    

    ANNOUNCEMENTS:

    Start Prepping for Day 3 - click on the Day 3 link and complete the PRE-CLASS materials.

    
    
  • Day 3 - Wednesday - 9/10 - Data and Visualization
    
    PRE-CLASS:

    Notes - Data and Visualization
    Video - Data and Visualization
    Remember to pull the class files to your local machine and make a copy in your working directory!
    Take the quiz on Canvas!
    
    

    CLASS TIME:

    Slides - Data and Visualization
    Homework questions
    Extra in class Plots!
    Get help with technology
    Colors
    Markers

    ANNOUNCEMENTS:

    Remember to hand in Homework on Canvas - Due Friday 11:59pm - drag and drop your .ipynb files for days 1-3
    Start Prepping for Day 4 - click on the Day 4 link and complete the PRE-CLASS materials.

    
    
  • Day 4 - Monday 9/15 - Numerical vs Categorical Data
    
    PRE-CLASS:

    Notes - Numerical and Categorical Data
    Video - Numerical and Categorical Data
    Remember to pull the class files to your local machine and make a copy in your working directory!
    Take the quiz on Canvas!
    
    
    

    CLASS TIME:

    Slides - Numerical and Categorical Data
    Homework questions
    Extra in class Plots!
    

    ANNOUNCEMENTS:

    Start Prepping for Day 5 - click on the Day 5 link and complete the PRE-CLASS materials.

    
    
  • Day 5 - Wednesday 9/17 - Data Wrangling
    
    PRE-CLASS:

    Notes - Data Wrangling
    Video - Data Wrangling
    Remember to pull the class files to your local machine and make a copy in your working directory!
    Take the quiz on Canvas!
    
    

    CLASS TIME:

    Slides - Data Wrangling
    Homework questions
    In class - Data Wrangling Code Session.
    

    ANNOUNCEMENTS:

    Start Prepping for Day 6 - click on the Day 6 link and complete the PRE-CLASS materials.

    
    
  • Day 6 - Monday - 9/22 - Data Wrangling Continued
    
    PRE-CLASS:

    Notes - Data Wrangling Continued
    Video - Data Wrangling Continued
    
    Take the quiz.
    

    CLASS TIME:

    Slides - Data Wrangling Continued
    Homework questions
    In class - Work on the Exploration Together.
    

    ANNOUNCEMENTS:

    Start Prepping for Day 7 - click on the Day 7 link and complete the PRE-CLASS materials.

    
    
  • Day 7 - Wednesday - 9/24 - Joins and Merges
    
    PRE-CLASS:

    Notes - Data Wrangling Joins and Merges
    Video - Data Wrangling Joins and Merges
    
    Take the quiz.
    

    CLASS TIME:

    Slides - Joins and Merges
    Homework questions
    Start working on the Practice Exam.
    

    ANNOUNCEMENTS:

    Start Prepping for Day 8 - click on the Day 8 link and complete the PRE-CLASS materials.
    
    EXAM 1 is in 1 week!

    
    
  • Day 8 - Wednesday - 10/1 - Reading in Data
    
    PRE-CLASS:

    Notes - Reading in Data and Data Types - fixing Data Errors
    Video - Reading in Data and Data Types - fixing Data Errors
    
    Take the quiz:
    
    

    CLASS TIME:

    Slides - Reading in Data and Data Types
    Homework questions
    Talk about Exam 1 - Cheat Sheet of Commands
    

    
    
  • Exam 1 - Monday- 10/6
    
    PRE-CLASS:

    - Work on Exam1 - after it becomes available on Canvas
    - This exam is open notes, open computer, etc --- but you cannot use any type of human or AI intervention. This includes asking how to do an entire problem online, asking ChatGPT, or working with friends.
    - The pre-class work on the exam must be COMPLETELY YOUR OWN!
    
    Submit the Exam - First Draft
    Exam 1
    After you submit the exam, you will be able to work in groups on the exam during our class time. You can then go home and work individually on finishing up your best possible work on the exam. Submit your final version of the exam as an additional attempt.

    CLASS TIME:

    Work on Exam 1 in Groups

    ANNOUNCEMENTS:

    Start Prepping for Day 9 - click on the Day 9 link and complete the PRE-CLASS materials.

    
    
  • Day 9 - Wednesday - 10/8 - Importing, Recoding, and Visualizing Data
    
    PRE-CLASS:

    Notes - Importing, Re-coding, and Visualizing Data
    Video - Importing, Re-coding, and Visualizing Data
    Take the quiz
    

    CLASS TIME:

    Slides - Importing, Re-coding, and Visualizing Data
    Homework questions
    Talk about the Final Projects
    

    ANNOUNCEMENTS:

    Start Prepping for Day 10 - click on the Day 10 link and complete the PRE-CLASS materials.
    In about two weeks we will have a week on Data Ethics. I would like you to explore some articles online to see what people are saying about ethics in Data Science. We will also talk about this in class. You are welcome to find your own article. Regardless of whether you pick from the links below or find your own make sure to take note of: The Date of Publication, The Author of the Article, The Source/Publisher (who owns the website), and the Purpose - why was the article written or is there possible bias or conflict of interest?
    
    LOTS OF POSSIBLE ARTICLES - DATA ETHICS
    The Ethics of Managing People's Data
    Big data ethics and 10 controversial experiments
    Introduction to Data Ethics
    The Importance of Ethical Data Collection
    Ethics of Artificial Intelligence
    Is Ethical AI even possible
    Dealing with bias in AI
    Who is making sure the AI machines aren't racist?
    Algorithmic Bias in Healthcare
    Health Care Bias Is Dangerous. But So Are ‘Fairness’ Algorithms
    Shedding light on AI bias with real world examples
    Ethics In The Age Of Data: Navigating The Crossroads Of Privacy And Progress
    The Ethics of Data Ownership: Who Owns Your Digital Identity?
    Ethical Research with Indigenous Peoples: Doing Right by Respecting Native Rights
    A Practical Guide to Data Ethics
    The Ethics of Data in the Age of AI: Why Responsible Data Practices Matter — Medium
    AI Ethics in 2025: Balancing Innovation with Responsibility
    OpenAI’s Sora Is Plagued by Sexist, Racist, and Ableist Biases
    Ethically dubious or a creative gift? How artists are grappling with AI in their work
    

    
    
  • Day 10 - Wednesday - 10/15 - Effective Visualization/Storytelling
    
    PRE-CLASS:

    Notes - Effective Visualization and Data Storytelling
    Video - Effective Visualization and Data Storytelling
    
    Take the quiz
    

    CLASS TIME:

    Slides - Effective Visualization and Data Storytelling
    Homework questions
    

    ANNOUNCEMENTS:

    Start Prepping for Day 11 - click on the Day 11 link and complete the PRE-CLASS materials.
    Get your Data Science Ethics Reading Materials!

    
    
  • Day 11 - Monday - 10/20 - Getting Data - Simpsons Paradox
    
    PRE-CLASS:

    Notes - Getting Data and Simpsons Paradox
    Video - Getting Data and Simpsons Paradox
    
    Take the quiz
    

    CLASS TIME:

    Slides - Getting Data and Simpsons Paradox
    Homework questions
    

    ANNOUNCEMENTS:

    Start Prepping for Day 12 - click on the Day 12 link and complete the PRE-CLASS materials.
    You should be reading your Data Ethics Book/Articles!

    
    
  • Day 12 - Wednesday - 10/22 - Doing Data Science - Web Scraping
    
    PRE-CLASS:

    Helpful lecture and video for preparing your final project proposal (due 11/3)
    Notes - Doing Data Science
    Video - Doing Data Science
    Day 12 - Web Scraping!
    Notes - Web Scraping
    Video - Web Scraping
    
    Take the quiz
    

    CLASS TIME:

    Slides - Web Scraping
    Homework questions
    

    ANNOUNCEMENTS:

    Start Prepping for Day 13 - click on the Day 13 link and complete the PRE-CLASS materials.
    Come to class next week prepared to discuss your ethics reading with your classmates and professor!
    
    
    

  • Day 13 - Monday - 10/27 - Misrepresentation and Privacy
    
    PRE-CLASS:

    Notes - Data Ethics - Misrepresentation and Data Privacy
    Video - Data Ethics - Misrepresentation and Data Privacy
    
    Take the quiz!
    

    CLASS TIME:

    Slides - Data Ethics - Misrepresentation and Data Privacy
    In Class Discussion
    

    ANNOUNCEMENTS:

    Start Prepping for Day 14 - click on the Day 14 link and complete the PRE-CLASS materials.
    You should be reading/finishing your Data Ethics Book/Articles!
    Exam 2 will cover:
    

    - Loading data and doing basic analysis - shape, describe(), columns, look for weird data.
    - The data in this exam will include NaNs
    - Masking data to find specific information.
    - Creating new columns in the data frame - doing a calculation using other columns.
    - Using groupby(), value_counts(), and sort_values()
    - YMerging two data frame into one data frame
    - Visualizing data both recreating a given plot and coming up with a plot of your own.
    - Communicating in written form what the results, data frames (tables) and visualizations (plots) mean in terms of the data.
    
    

    
    
  • Day 14 - Wednesday - 10/29 - Algorithmic Bias
    
    PRE-CLASS:

    Notes - Data Ethics - Algorithmic Bias
    Video - Data Ethics - Algorithmic Bias
    
    Take the quiz!
    
    

    CLASS TIME:

    Slides - Data Ethics - Algorithmic Bias
    In class Discussion
    

    ANNOUNCEMENTS:

    Work on Exam 2 - You should submit your work before you come to class where we will work on the exam in groups.
    My solutions to Exam 1 are now posted on Canvas - you can see what kind of writing and explanation I expect
    
    Start writing your Final Project Proposal - DUE (11/7)

    
    
  • Exam 2 - Monday- 11/03
    
    PRE-CLASS:

    - Work on Exam2 - after it becomes available on Canvas
    - This exam is open notes, open computer, etc --- but you cannot use any type of human or AI intervention. This includes asking how to do something online, asking ChatGPT, or working with friends.
    - The pre-class work on the exam must be COMPLETELY YOUR OWN!
    
    Submit the Exam - First Draft - On Canvas
    
    After you submit the exam, you will be able to work in groups on the exam during our class time. You can then go home and work individually on finishing up your best possible work on the exam. Submit your final version of the exam as an additional attempt.
    
    Cheat Sheet of Commands 1
    Cheat Sheet of Commands 2
    Video - Common Errors in Python
    Video - Homework Day 11 - Solutions - live programming
    

    CLASS TIME:

    Work on Exam 2 in Groups

    ANNOUNCEMENTS:

    Start Prepping for Day 15 - click on the Day 15 link and complete the PRE-CLASS materials.
    Finish writing your Final Project Proposal - DUE FRIDAY 11/7/25 - Here is info about the proposals Final Projects
    

    
    
  • Day 15 - Wednesday - 11/5 - Intro to Modeling and Algorithms
    
    PRE-CLASS:

    Notes - Introduction to Modeling and Algorithms
    Video - Modeling with Plotly Trendlines
    Video - Modeling with Linear Regression
    
    Take the quiz:
    
    

    CLASS TIME:

    Slides - Introduction to Modeling and Algorithms
    Work on the assignment in class
    

    ANNOUNCEMENTS:

    Start Prepping for Day 16 - click on the Day 16 link and complete the PRE-CLASS materials.
    

    
    
  • Day 16 - Monday - 11/10 - Nonlinear Models
    
    PRE-CLASS:

    Notes - Modeling Nonlinear Relationships
    Video - Modeling Nonlinear Relationships
    
    Take the quiz!
    
    

    CLASS TIME:

    Slides - Modeling Nonlinear Relationships
    Work on the assignment in class
    

    ANNOUNCEMENTS:

    Start Prepping for Day 17 - click on the Day 17 link and complete the PRE-CLASS materials.
    
    Linear Regression Kaggle Search - probably good data for linear regressions
    
    

    
    
  • Wednesday - 11/12 - Get caught up!!!
    
    PRE-CLASS:

    Get caught up!!!
    Go back and hand in past due homework
    Make sure you understand Modeling and Algorithms
    Make sure you submitted a project proposal
    
    

    CLASS TIME:

    Get help with the topics that you are struggling with
    Live programming
    

    ANNOUNCEMENTS:

    Start Prepping for Day 17 - click on the Day 17 link and complete the PRE-CLASS materials.
    
    

    
    
  • Day 17 - Monday - 11/17 - Models with Multiple Predictors
    
    PRE-CLASS:

    Notes - Modeling with Multiple Predictors
    Video - Modeling with Multiple Predictors
    
    Take the quiz!
    
    

    CLASS TIME:

    Slides - Modeling with Multiple Predictors
    Work on the assignment in class
    Bike Rental Image to Reproduce
    

    ANNOUNCEMENTS:

    Start Prepping for Day 18 - click on the Day 18 link and complete the PRE-CLASS materials.
    
    

    
    
  • Day 18 - Wednesday - 11/19 - Classification and Categorical Data
    
    PRE-CLASS:

    Notes - Classification and Categorical Data
    Video - Classification and Categorical Data
    
    Take the quiz!
    
    

    CLASS TIME:

    Slides - Classification and Categorical Data
    Work on the assignment in class
    

    ANNOUNCEMENTS:

    Start Prepping for Day 19 - click on the Day 19 link and complete the PRE-CLASS materials.
    
    

    
    
  • Day 19 - Monday - 11/24 - Group Projects Assigned
    
    PRE-CLASS:

    Please come to class ready to think about what you want to work on for your final project.
    

    CLASS TIME:

    Groups assigned
    Each group makes a mini-presentation of their idea
    Chance to choose groups
    

    ANNOUNCEMENTS:

    Start Prepping for Day 20!
    
    

    
    
  • Monday - 12/1 - Monday 12/8 - Group Project Workshops
    
    PRE-CLASS:

    Please come to class ready to work on your final project. This is the best place to collaborate!!!
    

    CLASS TIME:

    Work on Final Projects - Get help from Edgar and Joanna!

    ANNOUNCEMENTS:

    Final projects are Due on Wednesday 12/10/25 at 2:30pm - Each person should submit their copy of the final project! Here is info about the final project:
    Final Projects
    
    
    
    

    
    
• Homework Solutions - Exam Review
  
  All Practice Problems and Programming Assignment solutions are available on Canvas
  
  Cheat Sheet of Commands 1
  Cheat Sheet of Commands 2
  Video - Common Errors in Python
  Video - Homework Day 11 - Solutions - live programming
  
  
  




I catch all the buggies in my code!