Introduction to Python
Why Python for computing scientists ?
Computing scientists wear many hats: data collectors, data manipulators, analysts, and storytellers.
Python empowers them throughout this entire process.
Its intuitive nature, with no need for strict typing or memory management, makes it a joy to learn, reason about, and share code.
This ease of use extends to powerful functionality, allowing you to tackle projects from small scripts to large-scale applications.
Python's popularity breeds a rich ecosystem of open-source libraries, offering a vast toolbox for any computational task.
Imagine a massive Lego playground overflowing with pre-built structures – that's the power of Python's libraries.
Plus, its built-in package management lets you seamlessly leverage these tools without ever leaving your development environment.
And the cherry on top? Dynamic typing and automatic memory management free you from platform-specific quirks, allowing you to effortlessly port your Python code across different systems, from your local PC to a powerful HPC cluster.
In short, Python provides the perfect blend of simplicity, power, and flexibility, making it an essential tool for any aspiring or established computing scientist.
Training Agenda
Day 01:
- Introduction to Python world
- Setting up python
- Installing Singularity on a personal system
- Basic Syntax
- Data Structures 1/2
Day 02:
- Data Structures 2/2
- Control Structures
- Modules
- Wrap-up and Q&A
Training Dates, timings and Venue
- Day 01 - 22nd April 2024- TAMUQ Building - Computer lab. Room # 202G (9:00AM to 11:30am)
- Day 02 - 24nd April 2024- TAMUQ Building - Computer lab. Room # 202G (9:30AM to 12:00am)
Requirements
1. Hardware : none, attendees will use the computers present in the computer laboratory.
2. Knowledge : this course is designed for beginners with no prior coding experience. However, a former exposure to any programming language can help to navigate the initial learning curve more smoothly.
Course Slides
Here below is the PowerPoint material used during the training:
Course Source Code
Here below is a link to the repository containing the Python scripts used during the training:
Python Training Repository
You are free to download the files on your local machine for learning purpose.