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[Optional] Things you can do before joining MSBA

Category: Blog | #MS in the US

Hello Incoming Students,

Congratulations on your MSBA program admit. You have made it till here, now only nine months of intensive program experience and then you will come out as Data Science Professionals. Yes you heard it right, it is intense, but with proper time management skills, you can pull it off.

So many of you must be thinking, about preparing for the program before joining here, and that’s a great idea. So I will be sharing a few resources for you to read or learn, that would be helpful for you in the long run. But, let me tell you this is all optional, officially the program doesn’t require you to come prepared with everything. You start the course from the basics, so no need to panic if you can’t prepare in advance.

  • Book “Analyzing the Analyzer”: Before joining the program, it is crucial to understand the post-degree opportunities available to Data Science Professionals. This book will help you understand the plethora of skill sets to build as per your desired profile. Book Link

  • Decide on a career path , be it Business Intelligence Engineer, Data Analyst, Data Scientist or Business Consultant. Then check out the job descriptions for similar roles on LinkedIn Jobs and Indeed.com. It would give you a rough idea of what skills to built up during the program.

  • Get some basic idea of Machine Learning Algorithms. This course on Coursera is presented by Andrew Ng and to my knowledge is the best course on machine learning. The course is not free, so you can either pay for it or start the free 1st month and try to go as far as you can in one month. Completing the course is not compulsory, six weeks of content should be enough to get a good idea of the concepts. Alternatively, the video lectures are available on Youtube for free at this link. However, you won’t have access to the quizzes and the programming assignments on Youtube.

  • Book “Freakonomics” -Levitt and Dubner: As Data Science professionals, it is important to interpret data in a meaningful way, test the hypothesis, and convey the results in a simple format. And this book showcases this perfectly. I found this book very interesting because of the deep analysis of the authors. The authors have wonderful data storytelling skills, which automatically gives you the motivation to keep reading the book until it’s over. Must read for future Data Scientists. “Super freakonomics” is a follow-up book of this series and equally enjoyable.

  • Learn programming skills in Python and/or R. Datacamp has some excellent courses in their free tier, so do check them out.

  • Follow Active Data Science professionals on LinkedIn. Some suggestions from my end: Vin Vashishta , Randy Lao , Eric Weber , Favio Vázquez , Mike Tamir , Andriy Burkov. .

I hope this does help you in some ways.

Best of luck.