Frequently Asked Questions

Yes! Students come to our Applied Business Analytics (ABA) programs from all kinds of backgrounds. Some majored in statistics as undergraduates and have worked extensively with data applications. Others come from completely unrelated fields, and are successful in the courses. Your success in the program is mainly driven by your own dedication. Starting off without a statistics or programming background might mean that you will have to work a bit harder at first, but it also has a huge upside—it means that you will see an even bigger net benefit from having taken the ABA courses.

ABA is STEM-designated. This means that graduates of the program are eligible for three total years of OPT (Optional Practical Training), including the two-year STEM extension.

In the ABA program, courses use R, Python, SQL, Excel, and Tableau. ABA also offers several self-paced laboratories that offer exposure to other statistical applications. Our courses are frequently revised in order to keep up with changes in industry.

If you have not already taken our Pre-Analytics Laboratory (AD 100), you should do so before you start the program. The self-paced AD 100 lab provides an overview of several important analytics tools and concepts.

Beyond that, you could brush up on your statistics basics, or practice coding in R or Python. However, you’ll be fully immersed in those tools when you get here, so you may want to just take some downtime right now. Relax, travel, and enjoy yourself so that you can be well-rested for your arrival to campus.

Many of our courses use real-world datasets, some of which require significant data wrangling before analysis can be performed (our graduates tell us that this is quite realistic training for the workforce).

Other courses use simulated datasets, which are built around some course-specific theme or business running case.

Yes—many of our top students serve as Teaching Assistants or Graduate Research Assistants. This can be a good way to gain valuable leadership experience, work closely with a professor, and earn some extra money during your time as a student.

BU MET students can use CPT while enrolled in the program. Some of our students have used CPT for summer work performed at companies (i.e., internships) in the Greater Boston area.

The majority of our courses are taught by full-time faculty, all of whom have acquired relevant professional experience prior to entering academia. Nearly one-fifth of our classes are taught by adjunct instructors who work full-time in Boston, managing and analyzing the data of Fortune 100 corporations. We have found that a mix of full-time and adjunct faculty is ideal—our adjunct faculty bring knowledge of cutting-edge, real-world data applications into the classroom, whereas our full-time faculty are completely immersed in teaching and advising our students.

Yes. All of the ABA specialization courses are offered in both the online and face-to-face formats. The material covered in both formats is the same, as is the high instructional quality.

No. Neither test is required for your application.

Yes. In fact, the degrees are identical. The Boston University degree earned by an online student is exactly the same as one earned by an on-campus student.

If you have completed the graduate certificate requirements, and then decide to pursue the Applied Business Analytics master’s, you do not need to reapply. At that point, you have already been accepted into an Applied Business Analytics program, and you have already proven yourself, so your decision to continue on towards the master’s is just an administrative matter (your enrollment in additional classes). The four certificate courses can be counted towards the master’s, so you are already 40 percent of the way there!

To earn your MS in Applied Business Analytics, you will need to take 10 total courses in order to meet the 40-credit requirement for graduation. Eight of those courses are required; for the other two, you may take any of the graduate-level courses offered by MET.

Many ABA students take elective courses offered by MET’s Computer Science department. Among the most popular electives are Information Structures in Python (MET CS 521), Database Design and Implementation for Business (MET CS 669), Data Science with Python (MET CS 677), and Advanced Machine Learning and Neural Networks (MET CS 767).

Sorry, there are no waivers for any of the required courses in the program.

Yes! Boston University’s Center for Career Development is an excellent resource, and it is available to all BU students. Take advantage of this resource, and consider using the CCD for help with your résumé and/or interview preparation.

A good place to start is the eventbrite website. From the homepage, you can enter a search term like “Data Analytics” or “Data Science” along with a location term, such as “Boston.” There are data-related events taking place every night of the week across the city and Greater Boston.

You can also take a more direct approach by using a tool such as LinkedIn to connect with people who share your interests, hobbies, or background.

Here at BU, there are many opportunities to join clubs and to become involved in things like intramural basketball or club soccer.

With networking, remember that you’re playing the “long game”—the things that you learn, and the people that you meet may not impact you immediately. However, the payoff might come in an indirect way. For example, let’s say you attend networking events that are focused around themes related to data analytics and data science.

Having a data portfolio can be a powerful competitive advantage in the job marketplace.

You may already have more of a data portfolio than you realize. If you have already begun to take the ABA specialization courses, many of your assignments could form the starting basis of a data portfolio. The end-of-semester capstone course projects can fulfill that role as well. You can also scour the internet for datasets to which you can apply your own analysis, using the tools and algorithms that you have learned as an ABA student.

Each of those laboratories is designed to build your familiarity with the software tools and applications that you will need to succeed in the ABA program. ADR100 is completely focused on R, whereas AD100 covers the use of several tools and applications.

For these laboratories, there are no credits and no grades. They are a resource that is available to you throughout your time as an ABA student. Ideally, you should complete each of these either prior to enrolling in Business Analytics Foundations (MET AD 571) or concurrently.

The 200-level laboratories are intermediate-level. They cover more topics than the 100-level laboratories, and they do so in considerably greater depth.

The 200-level laboratories are not a requirement for any student—they are an optional resource available to you. Some of our students just pick and choose particular units to focus on with these laboratories. For example, someone might review the unit on ensemble machine learning methods in ADR 200 prior to a job interview, and then check out the SQL material in AD 200 for a different interview. Someone else might use them to brush up on material covered in a specialization course—for example, by reviewing the ADR 200 unit on statistical distributions while taking Enterprise Risk Analytics (MET AD 616).