Data Science Discovery

Upcoming Deadlines

• Your final course grade is available in Canvas -- see our e-mail for details.

• Interested in helping develop DISCOVERY? Apply to be a CA in Spring 2022!

Week 15: Project and Final Exam

I cannot believe this semester is almost over – over the past 15 weeks, you have learned an incredible amount of statistics, Python, and data science! There is no new lecture content this week and no lab section. Instead, we want to give you plenty of time to both finish your Project 2 and prepare for your Final Exam. This means there are only up to four things remaining for you to complete:

• lab_regression (last week’s lab) is due tonight by 11:59pm
• Project 2: You and Data Science is due this Wednesday at 11:59pm
• Homework 35: Final Exam Practice is available until the last final exam is given
• Finally, and most importantly, the STAT/CS/IS 107 Final Exam, which you will take in the CBTF

Week 14: Machine Learning

This week, we continue our journey with machine learning and you’ll begin to write your first code to have a machine learn!

1. Monday: Lecture: Machine Learning Models in Python with sk-learn with Homework m6-04

2. Wednesday: Lecture: Clustering with Homework m6-05

3. Friday: Lecture: Towards Machine Learning in Python. The final homework, Homework #35, will be scored as your highest grade on any practice final exam.

You will also complete your final lab section this week, lab_regression. :)

lab_regression: Regression

Week 13: Correlation and Linear Regression

This week, we are beginning our journey to understanding how we can use computers to learn – and we’re starting your final project!

1. Monday: Lecture: Overview of Machine Learning. There is no PL homework for Monday, but you should read the requirements for the final project: “You and Data Science” (due on the last day of class, Wednesday, Dec. 8).

2. Wednesday: Lecture: Correlation with Homework m6-02

3. Friday: Lecture: Linear Regression with Homework m6-03

Finally, you will dive into hypothesis tests in lab_hypothesis_tests in your lab section! :)

You and Data Science

lab_hypothesis_tests: Hypothesis Tests

Week 12: Polling, Sampling, & Hypothesis Testing

This week we will finish off polling with three lectures related to sampling and testing! This week has two lecture topics on Monday, one on Wednesday, and Friday is entirely focused on the review of the full learning badge!

1. Monday’s Lecture: Polling and Sampling and Confidence Intervals with Homework m5-06
2. Wednesday’s Lecture: Hypothesis Testing with Homework m5-07
3. Review of all of “Polling, Confidence Intervals, and Hypothesis Testing” with Homework m5-R

Finally, you will also have a assignment focused on polling!

lab_clt: CLT

Week 11: Random Variables and Distributions

After a few weeks of a lot of Python programming, this week has a major focus on statistical concepts! You will learn about random variables and distributions throughout the three lectures this week:

1. Lecture: Bernoulli & Binomial Random Variables
2. Lecture: Python Functions for Distributions
3. Lecture: Central Limit Theorem

Each lecture has a short homework assignment (m5-02, m5-03, and m5-04) and a lab assignment focused on distributions.

lab_random_variable: Random Variable

Week 10: Midterm 2, Project, and Random Variables

This week is Midterm #2 week! Since you will be spending 50 minutes in the CBTF, we cancelled all lecture content for Monday’s lecture (no lecture, no homework) to ensure we give you that time back. In addition, HW24 – the only homework for this week – is your highest grade on the “Midterm 2 Practice Exam” to give you even more reason to make sure you’re prepared for Midterm 2!

There are two lecture pages for this week to prepare you for the content for next week, while you finish up the project:

1. Law of Large Numbers
2. Random Variables

Finally, in lab you’ll work on a lab in lab section and finish up your project! Good luck on the midterm! :)

lab_justice: Justice

Week 9: Functions and Project #1

This week you will learn one of your very last control flow structures in Python – functions – and we will begin our first project!

On Monday, we have a regular day in DISCOVERY:

• Lecture: Functions in Python
• Homework: Functions in Python (m4-06)

On Wednesday:

• We will be announcing the full details LIVE on Wednesday at 12:00noon at this Zoom link. This will be the lecture for Wednesday.
• The project will be due in just under two weeks on Monday, Nov. 1.

On Friday:

• Lecture: Normal Distribution
• No homework, but we recommend you have found all of your images for your project and completed Sections 1-3 by the end of the weekend.

Finally, you’ll write some fun functions in lab_similarity! :)

lab_similarity: Similarity

Project 1: Image Mosaic

Create your own unique image mosaic!

Week 8: Simulation

This week we will start on using Python to simulate probability!

On Monday, you will discovery how to program in simulation in Python using for loops:

• Lecture: For-Loops in Python
• Lecture: Simple Simulations in Python
• Homework: Simple Simulations in Python (m4-03)

On Wednesday, you will connect your understanding about sample space to simulation:

• Lecture: Sample Space and State Space
• Homework: Sample Space (m4-04)

On Friday, you will apply your knowledge of conditionals to create if statements in Python:

• Lecture: Conditionals in Python
• Homework: Sample Space (m4-05)

Finally, you will write several simulation as part of your lab in lab_simulation! This week is packed with a lot of awesome topics, so don’t wait to start nerding out!

lab_simulation: Simulation

Week 7: Advanced Probability and Introduction to Simulation

This week you will finish up “Prediction and Probability” and begin to learn about simulation in preparation for next week where you’ll write your very first simulations in Python! There are three lectures for this week:

1. Conditional Probability
2. Bayes’ Theorem
3. Overview of Simulation

After each lecture you will have a mastery-based homework – HW17, HW18, and HW19 – and in lab you’ll learn about one of our favorite problems in lab_birthday!

lab_birthday: Birthday

Week 6: Probability!

This week is all about diving into probability – you’ll explore random number generation in Python and learn about how to solve complex probability problems with the multiplication and addition rules! There are only three lecture for this week:

1. Random Numbers in Python
2. Multi-event Probability: Multiplication Rule
3. Multi-event Probability: Addition Rule

After each lecture you will have a mastery-based homework – HW14, HW15, and HW16 – and in lab you’ll with GPAs in lab_gpa.

lab_gpa: GPA

Week 5: Midterm 1, Visualization, and Intro Probability

This week is Midterm #1 week! Since you will be spending 50 minutes in the CBTF, we cancelled all lecture content for Monday’s lecture (no lecture, no homework) to ensure we give you that time back. In addition, HW12 is your highest grade on the “Midterm 1 Practice Exam” to give you even more reason to make sure you’re prepared for Midterm 1!

There are only two lecture pages for this week after the day off for Midterm 1:

1. Basic Data Visualization in Python
2. Probability Introduction w/ The Monde Hall Problem with HW13

Finally, in lab you’ll work in a brand new dataset in lab_plots!

lab_plots: Plots

lab_simpsons_paradox: Simpson's Paradox

Week 4: DataFrame Conditionals and EDA

This week you will learn about ways data scientists describe and summarize large datasets with single values (descriptive statistics), how we form complex groups of data with Python, and begin to dive into Wade’s favorite topic (data visualizations):

1. Descriptive Statistics
2. Grouping Data in Python
3. Histograms
4. Quartiles and Box Plots

In addition, you’ll complete HW9, HW10, and HW11 and continue learning to work with DataFrames in lab_simpsons_paradox! :)

Week 3: DataFrame Conditionals and EDA

In this shorted week (no lecture/homework on Monday in observance of Labor Day), you will explore using conditionals with DataFrames and begin to learn about exploring dataset through Exploratory Data Analysis (EDA):

1. DataFrames with Conditionals
2. Software Version Control with git
3. Exploratory Data Analysis Overview

In addition, you’ll complete HW7 and HW8 and continue learning to work with DataFrames in lab_exp_design! :)

lab_exp_design: Experimental Design

lab_pandas: Getting Started with Pandas

The primary Data Science library we will be using this semester is pandas. This lab explores the basic usage of the pandas library and gets you ready for the Data Science challenges we will be beginning next week!

Week 2: Working with Pandas + Observation Studies

This week, explore how to select a subset of rows from a DataFrame and observational studies:

1. Row Selection with DataFrames
2. Observational Studies, Confounders, and Stratification
3. Simpson’s Paradox

In addition, there is a quick, mastery-based homework for every lecture and you’ll begin to work with DataFrames in Python in lab_pandas! :)

lab_intro: Introduction to Data Science

Data scientists use powerful tools to help learn about data. In this first lab, you will set up your account and computer for Data Science Discovery and begin to play around with your very first Python notebook!

Week 1: The Beginning

We (Wade and Karle) sent out an e-mail Monday morning, make sure to view that for important links to the course discord, and more!

This week, explore the basics of data science through four lectures:

1. What is Data Science?
2. Types of Data
3. Experimental Design and Blocking
4. Python for Data Science: Introduction to DataFrames

Make sure to complete the homework assignments for each and attend your lab section to get hands-on experience and for getting your computer set up to be do data science! :)

Welcome to Data Science Discovery!

Welcome! :)

Lecture and Labs both start Week 1! We will post the Week 1 Lecture videos on our course website by 10am on Monday. Talk to you soon! :)