Welcome to Darden’s Reviews

This site contains reviews I have created and resources I have gathered to support you on your journey through Codeup’s Data Science program and beyond.

I highly suggest making your own site as a portfolio that shows off your own work throughout the program. It would be a great link to share on your LinkedIn and drop on your resume for potential employers! ___

Resources

Github Page Tutorial

Want to make your own site as a personal portfolio? Check out this How-To infographic I created. The recorded demo of this process is available here. This will get your site up and running in less than half an hour! When you’re ready to make your markdown files beautiful, check out the tutorial below.

Markdown Tutorial

This tutorial will show you how to use lots of exciting markdown code in your README files as well as your Jupyter Notebooks!

Video Tutorial Resources

This page houses the links to helpful video tutorials on a variety of topics.

Interviewing Resources

This page houses helpful resources for you to use when preparing yourself for interviewing.

Storytelling Resources

This page is a collection of resources for putting together and giving great presentations.

---

Data Science Tools

SQL Review Notebooks

These notebook introduce SQL as a tool to interrogate databases and acquire data for use with python libraries like numpy and pandas. They will cover everything from RDBMS terms and structure to subqueries that involve joining and filtering data from multiple tables.

• SQL Intro Review Notebook

This notebook starts out with an important overview of fundamentals and goes through using GROUP BY clauses.

• SQL Joins and Subqueries Review Notebook

This notebook starts out with an overview of table relationships and goes through explanation and examples of using the JOIN clause and subqueries.

• SQL Case and Temporary Tables Review Notebook

This notebooks dives into the CASE statement and working with temporary tables.

Python Review Notebooks

These notebooks explore python basics and move into more complicated concepts like using list comprehensions instead of loops and creating your own functions.

• Python Data Types and Basic Functionality

This notebook is a work in progress but will cover Python data types and objects along with their functionality.

Pandas Review Notebooks

These notebooks introduce the pandas library from Series objects to DataFrame objects including their common attributes, methods, and chaining techniques.

Pandas Series Review Notebook

This notebook covers creating, indexing, and using methods and attributes with the pandas Series object.

• Pandas Series Exercises

Check out lots of great examples of code in action with the pandas Series.

Pandas DataFrame Review Notebook

This notebook covers creating, indexing, aggregating, joining, manipulating, sorting, reshaping, and styling pandas DataFrames.

• Pandas DataFrames Exercises

More code in action, but this time with DataFrames.

• Pandas Advanced DataFrames Exercises

Advanced DataFrames exercise walkthrough solutions.

Stats Review Notebook

This notebook covers Probability Distributions and Hypothesis Testing. I tried to make the concepts approachable and included lots of helpful examples and code snippets.

REST API Review Notebook

This notebook is a very crash course in using a REST API to acquire data. I included foundational terminology I encountered in my own reading and research and some simple code examples. There are also lots of links to further reading and free APIs for more practice.

---

Machine Learning

Classification Review Notebook

This notebook covers the Classification data science pipeline from Acquire through Evaluate. Again, I hope that the concepts are approachable, and I’ve included plenty of helpful code snippets for each stage of the pipeline. This is my most ambitious review notebook yet!

• Classification Acquire Exercises

This notebook covers reading data into DataFrames using a variety of methods, a look at writing functions with data caching options, and creating an acquire module for future use.

• Classification Prepare Exercises

This notebook covers preparing data by encoding with pd.get_dummies(), by imputing using SimpleImputer, by splitting using train_test_split, and creating a prepare module for future use.

Linear Regression Review Notebook

This notebook covers the Linear Regression data science pipeline from Acquire through Evaluate. Again, I hope that the concepts are approachable through expanded notes, and I’ve included plenty of helpful code snippets for each stage of the pipeline. There are lots of great resources linked for future study, as well.

Time Series Review Notebooks

• Acquire Data for Time Series

This notebook acquires data using an API for further use in the Time Series module.

• Prepare Data for Time Series

Coming Soon!

This notebook prepares data with a DateTimeIndex.

NLP Review Notebooks

• Acquire Data Using Beautiful Soup

This notebook walks you through the curriculum exercises that create functions for an acquire.py file by scraping data using the BeautifulSoup and requests libraries.

• acquire.py file

Here is an example of your end product.