Wednesday, 5 May

Programming Languages

Today's tutorials will occur along 4 tracks, each devoted to a different programming language, running concurrently. Each tab below corresponds to one of these tracks. The tutorials associated with each track are listed on the relevant tab.

MATLAB

Using MATLAB on Oscar | 9:30 - 11:00 EDT

An introduction to using MATLAB on Oscar. Topics covered include: working with MATLAB interactively on Oscar, using the MATLAB GUI, and using MATLAB in batch jobs.

Slides | Exercises

MATLAB: Programming Basics | 11:00 - 12:30 EDT

An introduction to programming using MATLAB. Topics covered include: programs and functions, relational operators, logical operators, and controlling flow with if statements and loops.

Exercises

MATLAB: Improving Performance | 1:30 - 3:00 EDT

This workshop will cover basic performance optimization techniques using MATLAB, including: code profiling, pre-allocation, sequential memory access, vectorization, and efficient matrix-vector storage and operations. We will assume that participants have a basic understanding of the MATLAB programming language.

Slides | Exercises | Github Link

MATLAB: Tools for Parallel Computing | 3:00 - 4:30 EDT

This workshop will cover basic performance optimization techniques using parallel computing techniques in MATLAB, including: parallel for-loops (parfor), single program multiple data (spmd), and distributed arrays. We assume that participants have a relatively advanced knowlege of the MATLAB programming language

Slides

Python

Using Jupyter Notebooks | 9:30 - 10:00 EDT

A quick overview to using Jupyter Notebooks. We will provide some python-specific functionality and some tips about notebooks in general.

Python Programming Basics | 10:00 - 12:00 EDT

An introduction to Python programming. Topics covered will include: the basics of variables, lists, dictionaries and arrays; the logic of control-flow techniques such as if-then statements, for loops, list comprehensions; a basic understanding of writing functions.

Data Wrangling in Python | 1:30 - 3:30 EDT

A quick introduction to working with data in python. We will touch on two ways work with data in general. A prerequisite is that you are at least familiar wiht simnple python programming or attended the previous session.

• Using standard python programming

• Using Pandas the Python Data Analysis package

Using Python on Oscar | 4.00 - 4:30 EDT

A short overview on how to work with python on OSCAR

Zoom Link: https://brown.zoom.us /j/97781603131

email: [e-mail] for passcode

DIRECT NOTEBOOK LINK: Click to go the jupyterhub for these series of workshops

R

A Gentle Introduction to R Programming | 9:30 - 12:00 EDT

This session will cover an introduction to R, including data types and data formats, useful R functions, writing your own functions, importing and exporting data, and installing packages.

https://ccv.jupyter.brown.edu/hub/user-redirect/git-pull?repo=git%3A%2F%2Fgithub.com%2Fcompbiocore%2Fccv_bootcamp_R&urlpath=lab%2Ftree%2Fccv_bootcamp_R%2FR_Bootcamp_Intro_R.ipynb&branch=main

R/TidyVerse Essentials | 1:30 - 2:30 EDT

This session will cover data wrangling (filtering, reshaping, joining) using TidyVerse.

https://ccv.jupyter.brown.edu/hub/user-redirect/git-pull?repo=git%3A%2F%2Fgithub.com%2F[…]%2Fccv_bootcamp_R%2FR_Bootcamp_Tidyverse.ipynb&branch=main

Essentials of GGplotting with R | 2:45 - 3:45 EDT

This session will cover data visualization using ggplot.

https://ccv.jupyter.brown.edu/hub/user-redirect/git-pull?repo=git%3A%2F%2Fgithub.com%2Fcompbiocore%2Fccv_bootcamp_R&urlpath=lab%2Ftree%2Fccv_bootcamp_R%2FR_ggplot2.ipynb&branch=main

Using R on Oscar | 4:00 - 4:30 EDT

This session will briefly cover different approaches to using R on Oscar.

https://ccv.jupyter.brown.edu/hub/user-redirect/git-pull?repo=git%3A%2F%2Fgithub.com%2Fcompbiocore%2Fccv_bootcamp_R&urlpath=lab%2Ftree%2Fccv_bootcamp_R%2FR_on_Oscar.ipynb&branch=main

Julia

Introduction to Julia | 9:30 - 11:30 EDT