Hello, and welcome to the first of a new series - Level Up - we’re going to be running on the Stack Overflow blog. Since its inception, this company has been dedicated to serving developers and technologists, helping them find answers to pressing questions and build their knowledge and expertise.
We’ve heard through our developer survey that many of our users enjoy coding not just a profession, but as a hobby and pastime. As we noted in our most recent Community Roadmap, a big part of what we're trying to do is build a place for learners. Using our blog, newsletter, and podcast to further that mission makes a lot of sense.
Codecademy is an interactive online platform with a similar mission. Codecademy is committed to making online coding education engaging, flexible, and accessible for as many learners as possible. Through interactive, outcome-driven courses, Codecademy aims to empower anyone to build something meaningful with technology.
There has always been a demand for remote learning experiences, but the need for this has grown tremendously during the last year, as the pandemic has made gathering for meetups and bootcamps difficult, and closed offices and schools. For the past few months, Codecademy instructors have begun teaching live classes on platforms like Twitch and YouTube. We’re excited to partner with them to bring a series of lessons to you.
We’re kicking things off with an 8 part series on statistics, based on Codecademy’s Master Statistics with Python curriculum content. This series is taught by Sophie Sommer, who learned data science as a student at NYU. We’ll serialize it here, but a number of the videos are also up on Codecademy’s site, so if you want to move forward at your own pace, head over here. And if you want to follow along live, you can tune in at 4pm Eastern Standard Time today. Find the live class or set a reminder here.
Ok, enough setup. I’ll pass things over to Sophie and let her explain things from here.
Thanks Ben. Hi, I'm Sophie. Read on for more details about the course I created.
In today’s tech industry, statistics and data science are becoming increasingly important and valuable skills. They are key to disciplines like machine learning and artificial intelligence. The course I’ve created starts with data cleaning and exploratory data analysis, then moves to inferential statistics and hypothesis testing. It will walk you through the basics of descriptive and inferential statistics and how to conduct your own analysis or experiment. For example, you'll create data visualizations to understand the relationship between apartment prices and various amenities and you'll learn to write your own Python function to conduct a binomial hypothesis test. In the final session, we'll walk through the full process of planning and implementing an A/B test.
In this first lesson, you'll learn how to investigate a new dataset. We'll walk you through the process of creating your own Jupyter notebook using Anaconda, show you how to read in and inspect a dataset, then work together to clean it up for an analysis. We recommend downloading Anaconda prior to the first session, which will simultaneously download Python, Jupyter notebooks, and a number of relevant Python libraries; making it even easier to follow along on your own computer.
If you want to take a look at the code I'm using in these sessions, check out our GitHub repository.
Every Tuesday from now until March 2nd, we'll be streaming a new session at 4PM EST. You can set a reminder for the stream for February 16th here.
Finally, if you want even more stats content, you can sign up for the interactive course this series was based on here. This course was developed by Sophie and has many more quizzes, projects, and helpful nuggets that we can't fit into our streams!
We’ll be returning with a new blog post in a week.