Columbia · Columbia University
Machine learning techniques as applied to data science and economics.
Coding skills by using Matlab on many topics like classification, clustering.
Basic machine learning concepts from no exposure to a general idea.
Class focused mostly on theory rather than gaining coding/programming skills.
I learned lots of machine learning knowledge, including regression, classification, big data, parallel computing, neural network, SVM, clustering, optimization algorithms, reinforcement learning, and how to solve dynamic economic models.
I've learnt more from this course than any other course I've taken at Columbia! I was hesitant to take this course initially because I did not know how to code, and now I can confidently code in Matlab! I have a good grasp of machine learning and AI techniques all thanks to the course structure, great teaching and assignments.
This course taught us a great deal about the theory of different machine learning methods and approaches, and how to apply them to real-world issues.
Best course in the MA economics program at Columbia 1 Columbia University: Arts & Sciences Fall 2022 Course: ECONGR5415_001_2022_3-ADVANCEDECONOMETRICS : ECONGR5415_001_2022_3 - ADVANCED ECONOMETRICS Instructor: Serguei Maliar Pushnoy