Prerequisites

Pre-MSBA Preparation

Preparing for your MSBA experience

We want to make sure that you are fully prepared to take on the program's challenging coursework. It's recommended that prospective students explore and become comfortable with the courses below in preparation for the MSBA curriculum.

Python Resources

MSBA students are expected to have prior coding experience in some widely used programming languages (e.g., C/C++, Java). However, the predominant language that will be used throughout the coursework is Python.

Code Academy

codecademy.com learn relevant statistical concepts, and computer science frameworks for Python and SQL Recommended courses:

Data Science Path (covers Python and SQL):Career Path Data Science
Python Courses Python Courses & Tutorials
SQL Courses: SQL Courses & Tutorials

Visit Code Academy

DataCamp

DataCamp offers a free introduction tutorial (4 hours) with videos and exercises. A wide range of intermediate and advance tutorials are available for a small fee.

Visit Datacamp

LearnPython.org

LearnPython.org offers tutorials supported by DataCamp in a user-friendly environment that allows testing inline code.

Visit LearnPython.org

TutorialsPoint

TutorialsPoint offers no-frills basic and advanced tutorials.

Visit TutorialsPoint

After Hours Programming

After Hours Programming offers a very basic introduction tutorial for those who want to start from square one.

Visit After Hours Programming

Execute Python Online

Execute Python Online is a web-based tool that allows users to test and execute code.

Visit Execute Python Online

Math Resources

Students are expected to be comfortable with calculus and linear algebra at the level covered in the book Mathematics for Economists by Simon and Blume. An alternative reference is Mathematics for Economics by Hoy et al. (Parts I-IV).

MITOpenCourseWare

MIT's OpenCourseWare provides open source courses on calculus and linear algebra for students that need a quick refresher. Check the following links:

Calculus online textbook Multivariable calculus Linear algebra

Additional Resources

Digital

Super Data Science Podcast
The Super Data Science Podcast offers over 60 episodes focused on all aspects of Data Science. For those new to the world of data science, this podcast will offer you the opportunity to learn the jargon, get exposure to the newest tools and hear from the prominent names in this emerging field.

Data Science Central
This online community describes itself in the following way, "Data Science Central is the industry's online resource for big data practitioners. From Analytics to Data Integration to Visualization, Data Science Central provides a community experience that includes a robust editorial platform, social interaction, forum-based technical support, the latest in technology, tools and trends and industry job opportunities." We bet that this site will be a helpful resource before, during and after your MSBA experience.

Udemy - Data Science and Programming Courses
Udemy offers low-cost, self-paced courses in a full spectrum of data science topics. We recommend that students review these offerings in order to identify areas of potential focus in data science. We also recommend taking courses in data science-oriented programming.

Khan Academy
Khan Academy is also popular with students because their instructional videos are free. We recommend that you work your way through the majority of videos in the Algebra section.

Books

R for Everyone: Advanced Analytics and Graphics(2nd Edition) (Addison-Wesley Data & Analytics Series) 2nd Edition
ISBN-13: 978-0134546926
ISBN-10: 013454692X
R For Everyone

Digital Analytics Association:Global organization that uses data to understand and improve the digital world through professional development and community.

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