How to Succeed with Data Science

It has been a while since I have posted on our web site—it has been a very busy year, much more than any other I can think of—except 2010 when I took 189 flights and I have travelled to 48 countries talking about the upcoming major future of self-service BI...much of it today's reality.

Data science has taken off everywhere, even to some of my surprise. I have more serious client projects than I have expected and that has kept me away from online training content. Plans have gone astray, but new ones are in place, with, I hope, new Cortana Intelligence courses to record in January.

I just wrote an essay addressing one of the most common questions I get asked: what should be your first data science project? You see, I have had my share of successful and failed projects since I have embarked on these ten years ago. While I am happy to say that the rate with which I now succeed on customer projects is much better than in the past, that is not just because I happen to know my field better. It is because I am better at setting my own and my customer’s expectations, and by being more careful in choosing the projects that I want to dive into. I would like to share some of my observations with those of you who are newer to this field. I would like to save you some frustration and to help you succeed as often as possible. Read my essay here:

• How to Succeed with Your First Data Science Projects

Class: Practical Data Science with Azure ML, SQL and R

I am chuffed that Microsoft have been promoting my training to some half-a-million people around the world. I strongly believe that if you want to get started in data science, it is not just the technology that matters, but a sound understanding of the concepts, like hypothesis testing or model validity that will make the difference. My week-long course covers all of that, as well as the Azure Machine Learning, SQL Server Data Mining, and Microsoft R Server technologies. The London course has sold out, but I still have spaces left in the last locations for 2016. Click below—and join me! You will learn a lot and I am sure it will help in your career:

• 7–11 November 2016: Chicago
• 14–17 November 2016: Zurich
• 21–25 November 2016: Oslo
• 28 November–1 December 2016: Stockholm

If you would like to find out more about the courses, have a look here, especially check out the detailed syllabus. This course has now been delivered over 13 times, and I have already trained over 250 data scientists just in the last year—most of them have started excellent, exciting, and profitable projects. Join us!

I wish you much success in analytics, and I promise to write more later this year. Thank you, very much, for following my updates. I appreciate your support.

Rafal

PS. You are receiving my newsletter because you have requested to be notified about new content when you registered on our site. Please share your feedback with me, pass it on, but if you are no longer interested in advanced analytics, BI, or data science, use the link below to unsubscribe. I respect your trust.