Nobody will have missed it: data science is _hot _these days. Problem that were deemed impossible to solve — even just a decade ago — are now being tackled by combining abundant amounts of data with the immense power of distributed computing. Companies are building up entire data science teams from the ground. People from all backgrounds and disciplines are making the transition to data science. Everyone wants a piece of the action. Despite all the excitement and opportunities, the field can also seem intimidating to newcomers. Big data, artificial intelligence, Hadoop, R, Beowulf clusters, machine learning, UNIX, statistical libraries, recurrent neural networks, process mining, random forests, APIs, cloud services… How to make sense out of it, where to even begin?
Fortunately, there are many good introductory courses out there. So many, in fact, that simply selecting a suitable one is a challenge in itself. Even the first strides into data science are plagued by an overload of information. To pave the road a little, this article provides a summary of the IBM Introduction to Data Science, arguably one of the most accessible and popular introductions out there. The course content is regularly available for free [1]; the paid version is required to have access to exam questions, the project assignment and the certificate of completion.
As the course itself is already rather condensed, this article aims to really gets to the meat of the course. Stripping away the anecdotes and examples, a to-the-point overview of the course’s core concepts and key messages is provided. The course is aimed primarily at starters in the field, but may also be of interest for more experienced professionals looking for a refresher or an alternative perspective. For those who only have 15 minutes to spare, this might be the overview you are looking for!
Module 1: Defining Data Science
Module 2: What Data Scientists Do
Module 3: Big Data and Data Mining
Module 4: Deep Learning and Machine Learning
Module 5: Data Science in Business
Module 6: Careers in Data Science
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