The course includes an in-depth treatment of querying SQL databases with lots of hand-on exercises.Ĭontinuing the logical progression of the data science chain, the next course addresses the topics of analyzing and visualizing data.
For data scientists, the first order of business is getting the data and that is the focus of this course. The track continues with course on querying data with Transact-SQL. The orientation course is a great way to get a high-level over view of the discipline of data science with some practical examples and exercises to help you relate to your application development work: The track starts with a Data Science Orientation course that sets the stage for the remaining courses. The courses are laid out in a learning path that makes it easy to progress through the content. The technologies that are used in the track include: T-SQL, Microsoft Excel, Power BI, the R and Python languages, Azure Machine Learning, HDInsight, and Spark. The Data Science track consists of 10 required courses of some 8-12 hours per courses leading to 8 distinct skills.
Let’s take a deeper look at the Data Science track and what it offers to application developers interested in raised their data science game. To access the Academy programs, simply point your browser to: All of the course tracks lead to a Microsoft Professional Program certification which you can add to your resume and share online. The courses contained in each track are delivered entirely online through edX ( ) and feature expert instructors from industry and academia. It’s part of Microsoft’s Academy series of MOOC-like courses that address topics like Big Data, DevOps, and Cloud Administration. Microsoft offers an extremely informative, free training track on data science called the Microsoft Professional Program – Data Science Track. (My search on Bing yielded 4.2 million results.) So where to begin? A quick search for “data science” can be pretty daunting when you’re trying to understand what this emerging field is all about. And we are seeing a lot more people with titles like “data scientist” appearing on our project teams or in the ranks of our business users. We’re seeing more and more requirements for our applications to include “smart”, “intelligent”, and “predictive” features. These days it’s pretty hard to be an application developer without running into concepts like big data, data science, artificial intelligence and machine learning. In this post, Senior App Dev Manager Pete Fuenfhausen breaks down the concept of Data Sciences and provides a walk through of free training track to get oriented with the technologies Microsoft offers in this space.
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