This is the course website for MATH/CSCI 485 - Advanced Data Science course taught by Dr. Robin Donatello in Spring 2020 at California State University, Chico. This landing page is used for posting of regular announcements and information for students of the class.

This course aims to help students navigate the evolving and murky waters of the Data Science landscape. We do so by not only providing training in advanced programming and technical skills, but also by providing opportunities for collaboration with other disciplines and reflection on how Data Science impacts human society.

Due to the COVID-19 pandemic all classes will be held online for the remainder of the semseter.

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05-05-2020 Week 15: Tree based models & Ethics

• Week 15 notes posted.
• HW09 CART models has been updated. Download and add the questions to your HW file.

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04-28-2020 Week 14: Tree based models & Ethics

• Week 14 notes posted.
• Start Reading: Weapons of Math Destruction. First written reflection due on Friday.
• Thursday: Intro to tree models and the last homework.
• Schedule has been updated.

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04-21-2020 Week 13: Resampling methods - Application

• Week 13 notes posted.
• Let’s run some machine learning classification models!

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04-14-2020 Week 12: Resampling methods - Theory

• Project instruction page has been linked to the navbar
  • Worth 50 pts total. Gradebook will be updated periodically.
• Don’t forget the weekly report ins
• Next homework: classification and resampling. Link to google classroom assignment in the schedule.
• Week 12 notes posted.

Thursday Update to week 12 notes. Pushing bootstrap back to next week. Work on data and methods slides today. Class is optional.

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04-07-2020 Week 11: Classification methods

• There’s more to life than logistic regression.
• Let’s look at some linear, and non-linear classifying models.
• Start to implement testing/training samples.
• Week 11 notes posted, as well as HackMD notes on classifiers.
• Case study in Doing Data Science - chapter 5 is a relevant topic.

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03-31-2020 Week 10: Text processing, sentiment

• Tuesday holiday. Yay for loosing more class time. 🙄
• Thursday: Project updates, research question operationalization, text processing
• Week 10 notes posted.

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03-24-2020 Week 9: Introduction to Natural Language Processing

• Project updates, starting to talk about NLP.
• New course note format to reflect the online delivery.
  • See these notes to begin.
  • A recording of these notes will be put into Google Drive.

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03-10-2020 Week 8: Translating a scientific question to a data analysis plan.

Crazy week with COVID-19 ramp up. See Google Drive for class notes.

Update - these have been moved into lecture notes. See the materials page.

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03-03-2020 Week 7: Statistical Learning

• We will learn out of the ISLR textbook in several ways such as;
  • I will pose a list of questions and assign them for you to answer/share with the rest of the class. (See hw05 as an example)
  • Selected exercises from the back of the chapter.

There are supplemental videos and slides for the ISLR textbook. Links are on the materials page. Me passively lecturing is not the best way for you to learn. I am trying to include you all in as much of the learning process as possible.

We will not cover ISLR Chapter 3: Linear Regression in much detail, as that is one of the main topics in 456. This however is a GREAT chapter to read for a different perspective/approach to regression. ⭐ ⭐⭐⭐⭐. Highly recommmend.

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02-25-2020 Week 6: Case Studies in Data Science

Examples in Data Science - You will share your case study/chapter in DDS with the rest of the class. - Prepare to only talk for 7-10 minutes on your chosen chapter/case study. If you have more info to share, consider writing up your notes in HackMD and we can add it to our shared notes files.

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02-18-2020 Week 5: Doing Data Science

• Being a Data Scientist means more than just building models. It’s identifying what the customers need, what they currently have, and how to bridge that gap. We’ll be working on case study in class this week.

• On Thursday we’re going to share out case studies from the DDS book. Please respond to the Slack Poll in #readings by EOD on Tuesday (2/18) for which chapter you’re going to read & share on Thursday (2/20).

• You also need to review another teams R Twitter data tutorial. Everyone has read access to all tutorial repos. Use GitHub issues to make comments/suggestions. Things you are to look for:

  1. Terminology not defined / too technical. Doesn’t look like standard R help files.
  2. Instructions start off at an appropriate point, assuming they have installed the Rtweet package but have not loaded it.
  3. Code needs to be able to run independently, without a Twitter account.
  4. Examples of what the data looks like.
  5. Suggestions on how to use the data / what analysis questions could be asked with this data.

• Dates

  • Peer Review due Thursday 2/20
  • Final version due Sunday 2/23
  • I will present your tutorials to the POLS class on Wednesday 2/25 along with providing them a sample data set containing historical tweet data.

• POLS project dates are starting to be set. See google calendar for a general idea of project timeline. More info will be posted on the Project page in the next week or so.

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02-11-2020 Week 4: POLS Twitter analysis project

Housekeeping

• Assignment tracker in google drive
• HW02 collab notes - getting started. We will learn machine learning. It’s not as mystical as you think it is.

This week we will explore the following questions:

• What types of analysis can be done on Twitter data?
• What types of analysis are important in the field of political science / public administration / public opinion?
• HW03 involves team writing a tutorial for the POLS students. We’ll work out how to form teams in Github in class.
• You’re advised to finish all Twitter assignment items before

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02-04-2020 Week 3: POLS Twitter analysis project

• POLS project page has been updated.
• Read over the Hack MD notes/idea dumping ground
• Make a Twitter dev account before Tuesday. (docs are in the hack md post)
• Read over the summary of DS project examples (POLS google drive)

Thursday I will be in a teaching demo from 2-2:50pm. You are expected to come to class and work together. I will come check in with you all when that class is over.

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01-28-2020 Week 2: What is Data Science?

• Websites
  • We’ll finish our introduction to working with blogdown to make dynamic websites.
  • Then you need to start working on creating your own personal page. Deadline for a site with just the basic info (HW1) pushed back to Friday.
• What is Data Science
  • We’ll explore the world of DS a bit more in depth, using HackMD as a place for our collaborative notes.
  • Read DDS Ch 1 and 16 to provide background and context
• What is your DS Niche? - What is your skillset? Your domain? - Where do you want to grow?

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01-21-2020 Week 1: Welcome to Spring 20!

This course website contains all materials except the textbooks for this class. Be sure to familiarize yourself with the organization. You will be here a lot. Bookmark this page.

Invitations to a Slack workspace will have been sent out to your @mail.csuchico.edu email address.