Dr. Suresh Kalathur
Learning from Dr. Suresh Kalathur, Practical Techniques Learned in Class Apply on the Job.
Assistant Professor of Computer Science; Director of Analytics Programs
PhD, MA, Brandeis University; MS, Indian Institute of Technology; BS, National Institute of Technology (India)
What is your area of expertise?
My main areas of expertise are programming languages and analytics. I helped to coordinate the analytics curriculum here at Metropolitan College. There is a great need for data analysts, data scientists, business analytics and business intelligence developers, and others who can apply skills in data analytics. There is no shortage of opportunity, and in fact there are more jobs available than there are people to take them.
What about teaching inspires you?
The field of computer science never stops changing, and as soon as the students see something new it always excites them. As a professor, I am also learning new techniques and technologies for myself that I am able to incorporate into the coursework so that the students can apply them in a practical way. Most of our students are working in the industry, so a big motivator for them is to apply the techniques that they have learned from their classes in their careers. They immediately see the benefit, and are often recognized by their peers as well.
What courses do you teach at MET? (online and/or on campus)
I have taught Data Mining (MET CS 699) and Web Analytics and Mining (MET CS 688) in the past. This semester, I am teaching Foundations of Analytics with R (MET CS 544) online and Rich Internet Application Development (MET CS 701) online and on campus. In spring 2019, I am teaching Server-Side Web Development (MET CS 602) and Rich Internet Application Development (MET CS 701).
Can you highlight a particular project within these course(s) that most interests your students?
For Foundations of Analytics with R (MET CS 544), I ask the students to pick their own data sets for class projects, and students have developed some really interesting projects. It could be weather data or exercise data, depending on their passion, and they execute projects using the tools that are covered in that class.
What specific professional skills are gained from the curriculum?
Our data analytics courses are geared towards asset programming language. We started with Java as the foundation course, and now we also have Python as a foundation course, and those are the new skills that students would learn as they go through the data analytics program. Students will gain the required knowledge of statistics, probability, data description, data distributions, errors, performance estimation, visualization, model evaluation, data mining techniques, web analytics, and web mining. At MET, courses are practical and application-based, so we use tools such as R, SQL Server, Oracle, Google Analytics, and so forth.
What are you currently researching?
My current research topics are programming languages on the server side, as well as tools and techniques for data mining. Some of the work that we did includes analyzing Turing evaluations and comparing them against the online materials that we post for the courses.