work experience: investment anlayst for 2 years since I finished school. WSJ reports unemployment for Statistics and Decision Science majors at 6%, which is higher than some of the other professions. Dustin has 20 years of experienced as a cross discipline engineer. No Data Scientist ever has said what you just did. The ranking compares the top computer science schools in the U.S. Read more on how this ranking was calculated. I'm looking to get into a good grad school program to prepare for career in data science. Bachelor's Degree, Computer Science (CS) - Salary - Get a free salary comparison based on job title, skills, experience and education. They make it possible, but then they come to me, the Stats major data scientist, to even read their results & then ask why their model didn't come out as happily as they wanted it to. Prerequisite Flowchart and Course Planning Forms - B.S. Robotics, Vision, Signal processing, etc. Computer science is a stimulating, broad field of study that encompasses everything from theory to application. 9 Common careers for Computer Science graduates 1. Use the top Master's of Computer Science program rankings to find the right master's program for you. I think you should pursue a trade like plumbing. Without having insight into those, you can't even really make a decision. Computer Science jobs are undoubtedly the most sought after positions right now. vs. Statistics? All the time I see machine learning jobs that talk about using Hadoop/Scala/etc that are Java-like and I don't have the background to work on production-level software. Great that you got your own book out. The class required for my major and is an upper level 4000/7000 level grad class. Which one will have the most job opportunities in the near future (10 years approx)? There is also a risk that your Statistics teachers will be traditionalist and avoid machine learning and cross validation topics. Data science isn’t as clear cut; it’s an interdisciplinary field involving computer science and statistics. for the degree of Bachelor of Science in Liberal Arts & Sciences Major in Statistics & Computer Science. Berkeley's overall acceptance rate is 17%, but its Computer Science acceptance rate is only 8.5%. I haven't looked at any DS Bachelors though. The student's personal Program Advisor acts as his/her support system throughout their studies. m rare and are mostly finance-related. It's just like how there's startup businesses that try to get started at the wrong time or before the technology is there. Well minor in on and do a major in the other. Hi all! Studying Computer Science (CS) at UC Berkeley. Whereas if you did statistics, it's much harder to integrate software engineering skills (algorithmic complexity, regular expressions, database, and so on) into your curriculum. Data Science' was actually used multiple times before harvards business review that turned it into an overused buzzword. IMO applying ML and NN and all that finally caught up to DB/storage technologies and processing power around 2012 and the combintion of this resulted in the 'Data science' boom because we were to a point where it was doable to implement these techniques without spending enormous amounts of money on storage/processing power. There is a lot to be said about really understanding the difference between wearing a inferential statistics hat vs. a machine learning hat. background: bachelor's in Math & Comptuer Information Systems from no name state school. IMO were in a 'data/information revolution' that just started and I don't see it stopping in the next 100 years. Hey everyone, Let it be known that I have no real knowledge in either, so I'm starting on the same grounds for both. Press question mark to learn the rest of the keyboard shortcuts, http://catalogue.uci.edu/donaldbrenschoolofinformationandcomputersciences/departmentofstatistics/#majortext. The common tools of a data scientist are R, Python, scikit-learn, Keras, PyTorch and the most widely used techniques are Statistics, Machine Learning, Deep Learning, NLP, CV. Academics tend to get bogged down in theory, and tend to only use MATLAB, which isn't inherently a bad thing, but typically isn't enough for a data science position. You don't really need stats anymore for data science, there's an optimised function and library for everything you will practically need in your work. It simply didn't exist as a word before 2012 and wasn't mainstream before 2015-2016. I make a mental note to get back on those Udemy classes I’ve been neglecting. The demand is real, so pick your extra learning, but don't ever leave your domain. + the pure amount of data and type of data that's been created just wasn't a thing yet when they first created all of the ML/NN techniques. Combined Major: Computer Science and Another Science Subject. Another key difference between a computer science degree and a software engineering degree is the variety of options in career paths. If you are concerned about managing a double-major for both statistics and computer science, maybe you can consider majoring in one and minoring in the other.