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Final Grades Posted
 Your final course grade is available in Canvas  see our email for details.
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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!

Monday: Lecture: Machine Learning Models in Python with sklearn with Homework m604

Wednesday: Lecture: Clustering with Homework m605

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
. :)
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!

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).

Wednesday: Lecture: Correlation with Homework m602

Friday: Lecture: Linear Regression with Homework m603
Finally, you will dive into hypothesis tests in lab_hypothesis_tests
in your lab section! :)
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!
 Monday’s Lecture: Polling and Sampling and Confidence Intervals with Homework m506
 Wednesday’s Lecture: Hypothesis Testing with Homework m507
 Review of all of “Polling, Confidence Intervals, and Hypothesis Testing” with Homework m5R
Finally, you will also have a assignment focused on polling!
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:
 Lecture: Bernoulli & Binomial Random Variables
 Lecture: Python Functions for Distributions
 Lecture: Central Limit Theorem
Each lecture has a short homework assignment (m502, m503, and m504) and a lab assignment focused on distributions.
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:
Finally, in lab you’ll work on a lab in lab section and finish up your project! Good luck on the midterm! :)
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:
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 13 by the end of the weekend.
Finally, you’ll write some fun functions in lab_similarity
! :)
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: ForLoops in Python
 Lecture: Simple Simulations in Python
 Homework: Simple Simulations in Python (m403)
On Wednesday, you will connect your understanding about sample space to simulation:
On Friday, you will apply your knowledge of conditionals to create if
statements in Python:
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!
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:
After each lecture you will have a masterybased homework – HW17, HW18, and HW19 – and in lab you’ll learn about one of our favorite problems in lab_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:
 Random Numbers in Python
 Multievent Probability: Multiplication Rule
 Multievent Probability: Addition Rule
After each lecture you will have a masterybased homework – HW14, HW15, and HW16 – and in lab you’ll with GPAs in lab_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:
Finally, in lab you’ll work in a brand new dataset in lab_plots
!
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):
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):
In addition, you’ll complete HW7 and HW8 and continue learning to work with DataFrames in lab_exp_design
! :)
Week 2: Working with Pandas + Observation Studies
This week, explore how to select a subset of rows from a DataFrame and observational studies:
 Row Selection with DataFrames
 Observational Studies, Confounders, and Stratification
 Simpson’s Paradox
In addition, there is a quick, masterybased homework for every lecture and you’ll begin to work with DataFrames in Python in lab_pandas
! :)
Week 1: The Beginning
We (Wade and Karle) sent out an email 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:
 What is Data Science?
 Types of Data
 Experimental Design and Blocking
 Python for Data Science: Introduction to DataFrames
Make sure to complete the homework assignments for each and attend your lab section to get handson 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! :)