Opportunities for data scientists are rapidly growing in response to the exponential amounts of data being captured and analyzed. Companies hire data scientists to find insights and to solve meaningful business problems. Get the real-world knowledge and hands-on experience that can help you succeed in one of these new jobs. Prove that you have what it takes in the Microsoft Professional Program.Enrollment for the next Data Science Program starts on December 16th. https://lnkd.in/gnBkFKM
R is one of the most popular, powerful data analytics languages and environments in use by data scientists. Actionable business data is often stored in Relational Database Management Systems (RDBMS), and one of the most widely used RDBMS is Microsoft SQL Server. Find out more with the availability of a new free ebook, Data Science with Microsoft SQL Server 2016,
Now that it has been publicly announced. I have been working on the accelerated pilot program for Microsoft’s Professional Degree Program in Data Science these last two months. I still have one class and a capstone project left to finish it up. Very excited to be a part of this demanding program.
In-depth Introduction to Machine Learning in 15 hours of expert videos from Stanford University professors Trevor Hastie and Rob Tibshirani (authors of the legendary Elements of Statistical Learning textbook).If you are new to machine learning or a newer R user, I highly recommend getting the available free PDF download from the authors’ website to gain both a theoretical and practical understanding of many important methods for regression and classification.
Hear from Microsoft Engineers and customer experts on how you can build data driven intelligent solutions, on-premises and in the cloud, with R, Python, Hadoop,and Spark that will drive new and exciting services at the two days at the Data Science Summit that coincides with Microsoft Ignite in September. I am definitely going to try and catch a few of these sessions.
Learning R can be tricky, especially if you have no programming experience or are more familiar working with point-and-click statistical software versus a real programming language. This learning path is mainly for novice R users that are just getting started but it will also cover some of the latest changes in the language that might appeal to more advanced R users.