The Data Stack: A Structured Approach
This is great post about the data stack at Factual.
The Data Stack: A Structured Approach
This is great post about the data stack at Factual.
With the large increases in college tuition and the ever increasing amount of information available on the internet. It is no wonder many people are trying to learn new skills on their own. Data Science is one of those disciplines that many people are turning to the internet to acquire the necessary skills. The problem is knowing exactly where to find the best material.
If you have the necessary background in math, statistics, and computer science; then it is a good time to learn some data science specific skills. Coursera just recently launched a course specifically devoted to Data Science. It is titled: Introduction to Data Science. The course is being taught by Bill Howe of the University of Washington’s eScience Institute. I believe this course is an excellent place to start. I am very excited about this course.
Here is a listing of other materials that could be helpful to learning data science.
Many aspects of computer science are fundamental to data science. A good data scientist has to be able to transform/extract/manipulate lots of data. Computer programming is the main technique for such operations. Here are numerous resources to help you learn the fundamentals of computer science.
If you are not familiar with computer programming, this list is a good place to start.
Stack Overflow is a great site for answering all of your programming questions. It is good for beginners as well as more advanced programmers. Also, if you start writing a lot of code, Github is a great place to store that code.
Statistics is an important component of data science. Thus, it would be nice to have some resources available.
Well, here is a list of free statistics resources available online. All of these are fairly introductory, but I am guessing more advanced topics will be coming from these same organizations.
In addition to the free resources online, there are other options as well.
What other resources are available for learning statistics?
Math is one of the key building blocks of data science. While you cannot do a lot of data science with just calculus and linear algebra, both topics are essential for more advanced topics in data science such as machine learning, algorithms, and advanced statistics. Here are some freely available resources for learning both topics.
The following 2 courses from Coursera maybe good for a person learning to think mathematically.
O’Reilly and Data Scientist DJ Patil just released a new free report titled, Data Jujitsu: The Art of Turning Data Into Product. If you are interested in building data products, the report is excellent and definitely worth your time.
The report provides a definition for a data product. It then covers a process for taking an idea from concept to reality. The main point is to use some shortcuts and get the product out fast. Then if people like the product, and only then, spend some time really enhancing the algorithms.