Instead of t-statistics, why not try some bootstrapping? As far as job titles go, data scientist is kind of the biggest buzzwords of the last few years. Data science combines the application of subjects namely computer science, software engineering, mathematics and statistics, programming, economics, and business management. I don't think I really switched sides, but the world — at least the economics world — around you would have you believe that econometricians and data scientists are sets without an intersection. Instead of solving models explicitly — relying on strict assumptions to be able to do so — models are estimated iteratively with gradient descent (and its derivatives). Alas, you will probably also have to write code, not just words, if you want to work in data science. The specialization in data science is designed to begin after completion of the core sequence and the empirical methods sequence in the standard major. I may be bias here, given that I myself I’m a physicist by training. CSCI-UA.0310 Basic Algorithms (Fall / Spring) prerequisite: CSCI-UA.0102 and MATH-UA.0120 6. But it should give you plenty of things to think about — and expand your range of possible career options. While double majors have been a popular way to balancea deep study of the humanities with traditional degrees in the sciences, basic tabulations suggest that the percent of workers with a double major has been roughly constant, or even decreasing, over the past six years depending on how one restricts the sample. Reading through common data science job descriptions, you may get the idea that economics is the worst training to have. I may write more specific “tutorial” articles later. But when you actually look into what data science usually is, the boundaries between more traditional econometrics/statistics and the hip and cool machine learning become less and less clear (this infographic is a great illustration of it: source). The field of data science is truly interdisciplinary and is … The program in economics can be divided into five component parts: Becker Friedman Institute for Research in Economics, Center for the Economics of Human Development (CEHD), Energy Policy Institute at the University of Chicago (EPIC), Radical Innovation for Social Change (RISC), TMW Center for Early Learning + Public Health, UChicago UCEMA Joint Initiative for Latin American Experimental Economics, Master of Arts Program in the Social Sciences (MAPSS), BA in Economics with Specialization in Business Economics, BA in Economics with Specialization in Data Science, Economic Policy and Public Finance Workshop, Workshop in Economic Theory Joint with Applied Theory Workshop, Center for Early Learning + Public Health, Center for the Economics of Human Development, Kenneth C. Griffin Department of Economics. The specialization in data science is designed to begin after completion of the core sequence and the empirical methods sequence in the standard major. The MSc program in Data Science and Economics aims to train the following professional figures. But you probably have deeper knowledge of linear regression than the average data scientist. Instead of figuring out what the theory is behind the relationship you are trying to study, and carefully selecting explanatory variables and the appropriate model, you try all you can think of and see if it sticks. The Double Master's Programme in Economics gives students the opportunity to pursue two Master's degrees from two universities during a two-year programme. ^ (1) As part of the Data Science and Analytics programme, FoS is planning to co-develop modules on data analytics for functional areas such as business, healthcare and public policy making with other Faculties/Schools. What do data scientists do? It's all about using the right tools in the right applications — and I think econometrics taught you a lot about that. Granted, neural networks can go deep, far deeper than what I've just described. What actually is data science? The Bachelor of Science in Computer Science, Economics and Data Science (Course 6-14) is aimed at educating students at this intellectual nexus and equipping them with a foundational knowledge of economic analysis, computing, optimization and data science, as well as hands-on experience with empirical analysis of economic data, to identify, analyze and solve real-world challenges in real and … Focus in Data Analytics (Major) Starting 2020-2021, students will be able to add the Focus in Data Analytics to the Major. Students may not double count this course towards both the Core Curriculum and the Data Science and Analytics Second Major. Students pursuing the specialization in data science are not required to complete ECON 23950: Economic Policy Analysis. And even the terms you may not know, they are often just examples of skilful copywriting. And don't think that just because you don't know what Hessians are, you can't go into machine learning. Double Majors: Petitions must be submitted prior to the first day of classes in the term in which you intend to graduate. CSCI-UA.0201 Computer Systems Organization (Fall / Spring) prerequisite: CSCI-UA.0102 4. It may be taken in the same Faculty that offers the Major … MATH-UA.0… CSCI-UA.0101 Introduction to Computer Science (Fall / Spring) prerequisite: CSCI-UA.0002 or CSCI-UA.0003 or placement exam 2. A Double Major is a single degree programme, in which a student satisfies the requirements of two Majors. So why no one tells them in university that this is a very real career choice? And course prospectuses are slow to change — favoring more traditional options in finance, academia, government…. There were a total of 321 students who double majored, which is about 21 percent of the dataset. The specialization in data science provides advanced training in computation and data analysis beyond the basic methods discussed in the empirical methods sequence. ), but on a (basic) fundamental level, they just combine layers of logistic(-like) regressions to model more complex non-linear relationships that a single regression may not capture (for great primers on neural nets, see http://karpathy.github.io/neuralnets/ or http://iamtrask.github.io/2015/07/12/basic-python-network/). That it's beneath an economist to go into data science. Instead, they must complete basic training in computer science and at least two data science courses in the Department of Economics. In fact, it probably puts you well ahead of most of computer scientists and mathematicians when it comes to presenting and explaining your work clearly — and putting together longer pieces of texts that have structure and logic behind them. So give it a try. 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