AI
R
Python
Julia
Git
Bash/Zsh
Emacs
Tools
The next generation of Python notebooks
Getting started
A few words about Python
Running Python
Help and documentation
Syntax
Python objects
Collections
Control flow
Writing functions
Modules, pkgs, and libraries
DataFrames in Python
Array computing with NumPy
Plotting in Python
matplotlib
seaborn
Object-oriented programming
Python at scale
Resources
Learning with LLMs
LLMs and coding
First dab at playing with an LLM
Webscraping with an LLM
Takeaways on coding with LLMs
Text analysis
Package installation
Getting the data
Text processing
Text normalization
Sentiment analysis
Polars: faster DataFrames
The world of DataFrames
Installation
Data types
Data structures
DataFrames inspection
Subsetting data
Lazy evaluation
Comparison with pandas
Resources
GPU-accelerated Python
Notes about GPUs
GPUs on Alliance clusters
A brief intro to CUDA
GPU programming concepts
Arrays with CuPy
Using CuPy after this course
Our workflow
CuPy basics
Custom kernels
Dataframes with cuDF
The RAPIDS cuDF ecosystem
Installation
Setup for this course
Polars GPU engine
JAX: accelerated arrays & AD
Webinars
uv package manager
Next-gen Python notebooks
Dashboards: Shiny vs Dash
RIP pandas, welcome Polars
Slides content
Faster DataFrames
Slides content
Accelerated arrays & AD
Intro programming for HSS
Slides content
Workshops
Web scraping with bs4
DataFrames with pandas
Playing with text
The next generation of Python notebooks
Please find this webinar in
the tools section
.
uv package manager
Dashboards: Shiny vs Dash