BE534

040507

This course provides a comprehensive introduction to Python for data analytics focused on the interpretation of biological data. The course is structured as a series of short lectures covering key concepts and analytical strategies using Python and cutting-edge open source packages for data analytics. The majority of the course focuses on hands-on exercises both in- and out- of class to develop practical coding skills for interpreting and analyzing high-dimensional biological data. Students work in a collaborative learning classroom to gain skills in (1) basic Unix and Python, (2) Python data structures functions, and files, and (3) data wrangling and visualization using IPython, NumPy, and pandas, and (4) analytics using machine-learning methods available in Scikit-Learn. These skills are taught by implementing real-world coding examples to manipulate and process biological data in Python, and effectively use data-oriented Python libraries to analyze and interpret data from biological systems.

GRD - Regular Grades A, B, C, D, E

Graduate

GIDP - ABS (Applied Biosciences), GIDP - ECGN (Ecosystem Genomics)

Online introduction to Linux.

Code academy's Intro to Unix or Command line bootcamp.

Apple or Linux computer or Windows machine with Putty.

An introductory programming class in python is useful but not required.

BE434