We are excited to offer our online course in data science! Developed and taught by NYU instructors, this course is a great opportunity for those looking to expand their STEM interests beyond the high school curriculum. This class is designed for all levels.
- Course Dates: February – April
- Instructors: NYU Faculty
- Tuition Rate: $2,000 (Scholarships available!)
- Graded course
- Students receive an official NYU academic transcript
- Lecture Days/Times: One weeknight per week
- Lab Days/Times: Students are required to attend a weekly lab and may choose between a weekday evening or a weekend morning
- Open to current juniors and seniors
- Application deadline: mid-December
Why GSTEM Data Science?
Because data science is evolving quickly and being a data scientist is a very marketable skill set. The ability to gather, process, analyze, and visualize data will give you an incredible advantage as you move forward with your STEM studies and STEM careers.
Because data is everywhere! We often don’t realize the extent that we use it and how it influences our everyday lives.
Because data science has always been an important, underlying part of the program. The Winston Data Scholarship for our summer program has been around since 2015.
Students can apply for a scholarship when completing the application. Once reviewed, we may offer assistance equaling all or part of the $2,000 tuition.
Contact us at email@example.com.
This course has made me more appreciative of data science and the countless opportunities it provides to researchers. After taking this course, I am more aware of the data around me and the countless data files that appear in my everyday life. Now, with the skills from the course, I can explore any data file that I am curious about and draw my conclusions about problems that I may deal with.
Prior to GSTEM, I had little to no background in computer science. The program helped me delve into the realm that I was previously afraid to enter, and made it so that I could incorporate my love for research and scientific inquiry.
With the knowledge and skills gained from this course, I can now implement data science in my future STEM studies. As an ardent scientific researcher, I plan to further my inquisitiveness in my undergraduate education; I will bring my data science prowess to new laboratories and institutions in order to examine experimental results and harness new interdisciplinary studies.
I emerged from this class with thorough knowledge of a new programming language and an understanding of a modern utility/subject which will only become more significant as the world continues to digitize.
Working with like-minded peers in a supportive environment encouraged me to ask questions and go beyond the syllabus to maximize my learning from this experience.
I especially enjoyed the recurring topic of considering the human contexts of data and data science; we should simultaneously consider the technical consequences as well as the safety, ethical, and moral impacts of all our discoveries and practices.