2017_08_29_Emory Courses on Topics Related to Data Science (1).txt

Emory Courses on Topics Related to Data Science

* IBS 538:  Statistical Design and Analysis of Experiments
* IBS 574:  Computational Biology and Bioinformatics

* BIOS 516 (1) Introduction to Large- Scale Biomedical Data Analysis
* BIOS 534 (2) Machine Learning
* BIOS 544 (2) Introduction to R programming for Non-BIOS students
* BIOS 555: High-throughput data analysis using R and Bioconductor (half a semester course, taken and recommended by many Genetics and Molecular Biology students). 
* BIOS 570 (2) Introduction to Statistical Genetics

* MATH116:  Life Sciences Calculus II
* MATH221:  Linear Algebra 
* MATH361:  Probability and Statistics I 

* CS153:  Computing for Bioinformatics

* MSCR 530 Analytic Methods for Clinical and Translational Research I (3 credits)
* MSCR 533 Data Management (2 credits)
* MSCR 597 Big Data to Knowledge (BD2K) in CTR Research (1 credit)

* INFO 500(2) Principles of Public Health Informatics 
* INFO 511 (3) Analytics
* INFO 521 (3) Database Development for Public Health
* INFO 544 (2) Network Science in Public Health 
* INFO 550 (2) Software Engineering

* QTM120:  Math for quantitative sciences. Part 1 of the QTM courses which are recommended for students who want to brush up on topics in math and computer science before jumping into machine learning. 
o This course is slated to be offered online in summer 2018. 
* QTM210: . Part 1 of the QTM courses which are recommended for students who want to brush up on topics in math and computer science before jumping into machine learning. 
o This course is slated to be offered online in summer 2018
o 
* BUS 550 - Data and Decision Analytics (uses excel and SAS/LPM so nothing fancy programming wise, but a very well taught and practical course on how to make business decisions from data)
* BUS 651 - Strategic Decision Analysis 
* BUS 550 is a pre-req and again mostly uses excel but focuses on game theory concepts
* BUS 554 - Advanced Data Science (this one is more computationally intensive and teaches more "big data" analysis with cloud computing and such)