Alumni Spotlight: Punam Katariya, contributed by CourseReport.com
Posted by Vivian Zhang
Updated: Oct 12, 2015
Punam Katariya had a background in data from working as an analyst in market research and her education in math and statistics. Once she learned some programming skills, Punam decided to change careers and enter the world of Data Scientist. After doing her bootcamp research, Punam decided on NYC Data Science Academy because of their syllabus content and the exposure to real experts in the field. Now graduated, Punam tells us about the teaching style at New York City Data Science Academy, her 4 week project, and the biostatistician job offer she received after completing the course.
What were you up to before you started at NYC Data Science Academy?
I had worked as a data and business analyst in market research and staffing industry respectively for total of five years. My education is in mathematics, statistics and business.
Did you have a technical background before you applied?
I didn’t have much professional experience as a coder. However, I was coding in C++ during my Masters program. Because of my interest in data and programming, I was looking for programs on Codecademy and Coursera.
What was your goal in doing a bootcamp?
I wanted to start my big data career as a junior data scientist. My goal from a bootcamp was to achieve hands on experience using software and learn machine-learning techniques on a fundamental level.
Why did you choose NYC Data Science Academy? What factors did you consider?
I chose NYC Data Science Academy because of the syllabus content. I wanted to learn modeling the data and latest modeling techniques. NYC Data Science Bootcamp had good portions of lectures about statistical models using R and Python. Also, they organized industry and field expert workshop and lectures which were very helpful.
What was the application and interview like for you?
There was a coding challenge and a personal interview, I had to go through for application.
Did you get a scholarship to NYC Data Science Academy?
No, I didn’t.
How many people were in your cohort? Did you think it was a diverse cohort in terms of age, gender, and race?
Was everyone on the same technical level?
We were 14 people. Yes, it was a diverse group in terms of age and education background. Many of the other students left their industry to advance their career in Data Science. Some people were very good in programming already and some had core knowledge/experience.
Who were your instructors? What was the teaching style like and how did it work with your learning style?
We had two main instructors. One for in R programming and other for Python, D3 JS, Hadoop and Spark. They were always there to help and encourage students. lectures were always followed by hands on examples and homework/In class exercises. Also, all the students were asked to work on their projects during 12 weeks and present in class. Instructors, guest lecturers and guest speakers have lot of experience in their respective fields.
What technologies did you learn in your course? Were you able to learn it all in the short time you were in your program?
The course includes R, Python, D3JS, Hadoop and Spark. It was not possible for me to digest everything in 12 weeks. So, my goal was to understand the materials well and be good in at least one language.
Were you satisfied with the curriculum/actual material taught in the courses?
Yes, I was satisfied, and sometimes overwhelmed, by the material.
Were there exams/assessments?
No, there weren’t exams.
How many hours per week did you spend on NYC Data Science Academy?
I spent more than 60 hours every week on NYC Data Science.
Can you tell us about a project you worked on?
My first project was “Con Edison Hurricane Sandy Outage Data Presentation with R." I worked alone on this project for 4 weeks during bootcamp.
Did NYC Data Science Academy do job prep with your class?
They offered interview practice sessions with professionals in the field.
What are you doing now- did you move up in your career or get a new job?
I have received an offer for a Biostatistician position and paper work is in process. I was applying for jobs after completing the bootcamp. For the most part, I applied on my own. It took me three months to get a job. NYC Data Science prepared me for the interview also. However, initial material and hands on experience on regression helped me with a couple of interview questions.
Was NYC Data Science worth the money? Would you recommend it?
I think NYC Data Science was worth the money for me. I was able get many interview calls and most recruiters were interested in discussing about my experience. I would definitely recommend it. I don’t think that Data Science can be learned so quickly on your own. At bootcamp you are learning the best practices, not only from the instructors and materials but your peers teach you a lot.
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Vivian is the CTO and School Director of NYC Data Science Academy and CTO of SupStat. With her extensive experience working in the data science field, she developed expertise in multiple programming languages, including R, Python, Hadoop, and Spark. In August 2016, Forbes ranked her amongst one of the nine women leading the pack in data analytics. In 2013, she created the NYC Open Data Meetup group, which stands as one of the largest data science communities offering meetups, conferences, and a weekly newsletter. In her spare time, Vivian enjoys meeting people and sharing her motivational stories with our students and other professionalsView all articles
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