MSDABC Program Director Interview with Admissions

August 7, 2019

Professor Jiawei Zhang, program director of MS in Data Analytics and Business Computing, recently had a conversation with the NYU Shanghai Graduate Admissions Office regarding curriculum design, class profile and applicant backgrounds of the new class.

Below is a summary of the conversation:

Graduate Admissions: Hi, Professor Zhang. Many students are interested in the MS in Data Analytics and Business Computing program. Could you please share more about it?

Professor Zhang: This program aims to develop students' ability to make informed decisions by analyzing data. Data analytics comprises a series of actions: data collection and processing, insights generation, decision making, and value creation. Only when we implement the entire process in business scenarios makes analytics practical scenarios. The purpose of this program is to cultivate students' hands-on skills: process and analyze the collected data through modeling, produce perspective decisions, implement them through business communication and collaboration, and ultimately to transform them into actual business values.

(Analytics: Data-Driven Decision Making Process)

Graduate Admissions: Students come from different countries and regions in the world and have different major backgrounds. How did you balance students' past experiences and course difficulty level when designing the Data Analytics and Business Computing program?

Professor Zhang: Different professors have incorporated their own unique teaching methods in the design of course difficulty levels, so that students with distinctive learning backgrounds can learn the content at their current knowledge level, and obtain opportunities to further challenge themselves. I will explain it with some examples.

First, take my course, "Decision Models and Analytics”, as an example. When students have difficulty in following the course materials, they can ask questions and get support through my office hours. There is also a dedicated review period before the end of the course, which will help students consolidate knowledge they are not familiar with. For students who want to dive deeper into the subject matter, I added an extra session that covers advanced topics and materials. This is optional for students. These advanced topics will allow students to continue learning and exploring after class if they have ability and/or interest in the subject.

Professor Manuel Arriaga, of Intro to Python Programming, takes a different approach in balancing difficulty levels. Because he teaches three different levels of Python courses at NYU Stern, he extends advanced individual project opportunities from his other courses for students with strong programming backgrounds. 

The design of this introductory course is based on Python basics. Students of elementary level can improve their programming skills gradually through this course. For students who come in with already rich Python programming experience, they can choose to complete advanced individual projects under the guidance of the professor. In this way, Professor Arriaga hopes that students with different programming backgrounds can learn useful and relevant contents and improve their professional competence.

Graduate Admissions: Before the first class started, we heard that many of the courses are newly created only for this program. What are the students' feedback on the courses?

Professor Zhang: Many of our experienced professors used to teach MBA and EMBA programs; however, the focus of MBA programs are different from that of Master of Science, so a lot of content needs to be re-designed. Our master's program is more technical and practical. When designing the content, the professors pay attention in particular to invoking students interest to think about course materials.

Although we admitted many students with very competitive academic and professional backgrounds, they still sometimes find that the courseload is very demanding, especially given the tight schedule. In response to such feedback, professors first consider whether the content taught in the course is required by the industry, and if the answer is yes,  they will encourage students to continue exploration; if it is difficult for students to digest content because the theoretical basis involved is too deep, the teaching methods will be moderately adjusted in future classes.

Graduate Admissions: Will the students have other opportunities to communicate with you outside the classroom?

Professor Zhang: I really like to communicate with students, and I try to engage students with a variety of opportunities. For example, I hosted four lunch sessions with my students. A more relaxing atmosphere can help us to understand each other better. During regular office hours, I chat with students one-on-one in the office to learn about their needs for the program and even their future career plans. Besides office time, I encourage students to email me or make an appointment in person if they have any questions or concerns. A few weeks ago, my students and I visited the Brooklyn Brewery and learned about the company's data-driven operations strategy.

Graduate Admissions: We believe that close communication between professors and students will greatly enhance their learning experience and gains. The last question is, what kind of background do you think is important for students who want to apply for this program?

Professor Zhang: Our program does not require in-depth knowledge of mathematics, but it requires a good foundation in calculus. Therefore, applicants do not necessarily need to be majored in mathematics, but they should have clear logical thinking, analytical and problem-solving abilities, which are more important criteria to evaluate whether students are suitable candidates. For applicants with a strong background in mathematics, our program will guide them to explore the practical applications of mathematical theories. One of the learning objectives of our program is how to transform business problems into mathematical models and obtain optimization solutions based on the models. Therefore, logical thinking and abstract ability are very important to help students transform problems into right models. In terms of programming languages, Python courses are offered in this program, and students will study in depth during the semester. In addition, I strongly recommend that students should have some proficiency in R language. There are many contents of modeling optimization and data mining in this program. Familiarity with R language can help students adapt to the high-intensity one - year course of study as quickly as possible.