Yufeng Huang is a Lecturer in Columbia University’s Master of Science in Applied Analytics program and an Applied Scientist at Amazon. He holds a Ph.D. in Chemical Engineering from the California Institute of Technology. He recently discussed his class on natural language processing—and shared a strategy for how students can keep up with such a rapidly growing and expanding field as applied and data analytics. Excerpts:
What course are you teaching this semester and why is it important in the field of Applied Analytics?
I am teaching Applied Text and Natural Language Analytics. Using natural language processing techniques, one can gain insights from unstructured textual data including online reviews and comments, news articles and blog posts, customer communications, product and organization descriptions, etc. As text data is more readily available, and new techniques are developed rapidly, text analytics is becoming an essential capability for companies to provide high quality services to customers and to remain competitive. It is important in the field of Applied Analytics because it enables the analysis of the vast amount of valuable unstructured data that was not available before.
What is one piece of advice you would like to share with students?
Data analytics is a growing field, and it is important to continuously be learning to remain knowledgeable about the new developments. However, it is equally important to avoid being overwhelmed by all the new techniques available. One effective strategy is to focus on one technological area and one business area that you are passionate about. The technological area will allow you to dive deep into how the technology works, and to explore the applications of the technology in various business areas. At the same time the business area will allow you to progress in your business career and explore the various technologies that are important to the business. By adopting this strategy, anyone can learn effectively by consciously selecting the most relevant information in the field of applied and data analytics.