DataQuest is a recently launched online data science learning platform for python. The site consists of a gamified series of missions that increase in difficulty as your skills progress. Here are a few other features of the site.
- Sample Code
- Live, Interactive Browser-based Coding Environment
- Step by Step Instructions
- Instant Feedback
- Helpful Forums for Q&A
The site is still under development and the founder, Vik Paruchuri, is looking for help developing more content and missions for the site. If that is something of interest to you, get in touch with Vik via the DataQuest website.
The creators is the Insight Data Science Fellows Program have done it again. This time they have created the Insight Data Engineering Program. The program aims to training highly specialized software engineers that can build big data systems and big data pipelines. Unlike the data science program, the data engineering program does not target people with PhDs. Please visit the Insight Data Engineering website for a white paper with all the details on the program.
Here is an official announcement:
The Insight Data Engineering Fellows Program is a professional training fellowship designed to help engineers from various backgrounds, as well as mathematicians, and computer scientists, transition to careers in data engineering. – Tuition free, 6 week, full-time, data engineering training fellowship in Silicon Valley this summer. – Alumni network of 70 Insight Fellows who are now data scientists and data engineers at Facebook, LinkedIn, Microsoft, Twitter, Square, Netflix, Airbnb, Palantir, Jawbone and many others. – Interview at top technology companies hiring data engineers at the end of the fellowship. For more information please visit:
Markets for Good, an organization focused on performing data science for the social sector, recently released an ebook highlighting their 17 most influential blog posts. The ebook is titled, Markets for Good Selected Readings: Making Sense of Data and Information in the Social Sector.
Here is just a small sampling of the topics you can read about:
- 3 Reasons Why Open Data Will Change the World
- Let Our Data Define Us
- Put Your Data Where Your Mouth Is
If you are interested in how data can be used to help the world, this ebook is a good place to start.
Hal Daumé III, Assistant Professor of Computer Science at the University of Maryland, has placed the contents of his book online. The book is titled A Course in Machine Learning.
Here is a small sampling of the chapters from A Course in Machine Learning:
- Decision Trees
- Linear Models
- Neural Networks
- Ensemble Methods
- Bayesian Learning
Mohammed J. Zaki, Computer Science Professor at RPI, and Wagner Meira Jr., Computer Science Professor at Universidade Federal de Minas Gerais, have written the textbook Data Mining and Analysis: Fundamental Concepts and Algorithms. The book is currently available as a PDF download.
Based upon the chapters, the book looks very good. It contains large sections on data analysis, clustering, and classification. The final book will be published sometime in 2014.
Alteryx is offering the book, Big Data Analytics For Dummies, for free. If you are new to the term big data, this book provides a brief (about 40 pages) overview of the topic and what big data should be able to do for your company.
You have to register, but it is worth it for the free book.
This is an online, HTML version of the book, Natural Language Processing with Python. The book is a companion for NLTK which is a free, open source toolkit, written in python, for Natural Language Processing (NLP).
David Easley and Jon Kleinberg, both of Cornell University, have placed the contents of their social networking textbook online. All 24 chapters of Networks, Crowds, and Markets: Reasoning About A Highly Connected World are available for download. This could serve as a wonderful learning resource or an excellent reference tool. The material covered is quite extensive, and it provides many real applications of social network analysis. Not all the examples are online social networks.
In case you missed the announcement yesterday, Coursera added 12 new universities and over 100 new courses. The exciting part for people learning data science is a new category of courses: Statistics, Data Analysis, and Scientific Computing. None of the courses have started yet. Most are scheduled for this fall or early 2013. The courses look very good.
Are you excited about these new courses?
Springer has just release a new data science journal named EPJ Data Science. The journal is open access which means that articles are freely available online. That catch is that people whom submit articles must pay a fee for publication. Sometimes the fee will be covered by the author’s university or company. Anyhow, if you are interested in data science research, this journal is probably worth following.
Are you interested in academic journals?
Does this excite you?