According to a report from McKinsey & Company, “by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.” When you combine that figure with the expectations of big data increasing the annual GDP in retailing and manufacturing by up to $ 325 billion by 2020, you can easily see why learning data science should become a top priority.
Surprisingly, when faced with a free choice over something that costs a penny, many times we opt for the penny thinking that the free option must not be worth as much (and sometimes that’s true!). But thankfully with information on data science, there are a number of free and convenient ways for almost anyone to learn about it. Here are 11 options to jumpstart your education in this quickly expanding field.
If you’re just one year from earning either your masters or PhD from any math, science, engineering, or social science field, then you can apply to become a fellow with the Data Incubator.
The Data Incubator hosts a free 7-week fellowship in New York, Washington D.C. or the San Francisco Bay area where students can learn both the technical and non-technical way to achieve success as a data scientist. Students also learn programming skills from some of the leading data scientists in the world.
DataOnFocus is a website that was started by two men who are “fascinated with all issues related to IT” and want to share their knowledge. For example, they provide resources like “27 Free Data Mining Books” that anyone interested in learning data science should read if they want to get started in this field.
If you want to introduce yourself to data science then you should consider enrolling in this free online course provided by Coursera. Throughout the 8-weeks of study, students will learn the basic techniques of data, algorithms for data mining, and basic statistical modeling through video lectures and projects.
Believe it or not, you can learn data science through the “front door of the internet”. The reddit community shares a number of valuable resources where anyone looking to learn data science can find instructional sites, links to free workshops, and even the ability to ask for advice from fellow redditors.
While this course was originally taught during the fall of 2013, it remains an excellent course for those interested in data science. Not only is this ivy league course informative, most of the resources, such as videos and slides, can be found easily online.
Once you’ve reviewed the course, you should understand data mining aspects like data wrangling, cleaning, and sampling, data management, exploratory data analysis, prediction, and communication of results.
In this post Kunal Jain states “the best way to learn Data Science is to do Data Science.” Because of this fact, he’s presented five different projects in a variety of fields, such as Titanic dataset from Kaggle, learning to mine twitter on a topic, human activity recognition using smartphone dataset, Hubway Visualization challenge, and Movielens data, to help get you started in data science.
If you have a background in either math, computer science, or software engineering fundamentals, you can apply to partake in this 7-week professional training fellowship in New York City of Silicon Valley. During either program you’ll have an opportunity to learn from data science and engineers who work with companies like Facebook, Microsoft, Airbnb, Bloomberg, and reddit.
You don’t have to attend or enroll in any UC Berkeley classes to educate yourself in data science. This blog, which is run by the school’s School of Information, posts frequent interviews and articles with students who share their advice and experiences. For example, 40 different though leaders were asked to define big data. The blog also keeps followers up-to-date on events and the latest new surrounding data science startups.
This offers an extensive list of resource ranging from blogs, online courses, books, and face-to-face educational programs from Github contributors- where you can learn everything from the basics of data science to machine learning to data analysis.
Here you take free courses that focus on topics involving python, mining, statistics, data visualization, and analysis. The courses rely on short instructional videos and interactive learning so you can begin to work on solving real-world problems.
Kaggle describes itself as the “the world’s largest community of data scientists.” Not only are there a number of tutorials and projects to help better understand the various fields of data science, there’s also a large community of data science professionals where you can network and collaborate with. There’s also competitions and a job board if you’re seeking a career in this area.
Get started today!