Linux for Scientific Computing Masterclass - 10.5 Hours
What you'll learn
- Linux command line for HPC and Supercomputing
- Sysadmin for Supercomputing
- Job schedulers and batch systems (Slurm and PBS Pro)
- Scientific computing with virtualisation
- Supercomputing software stack
- Linux Scripting- Bash, REGEX, AWK, SED, GREP
- Linux Storage Management
- Linux Networking - Bonding, Teaming, NTP configurations
Requirements
- Access to a computer system for virtualisation
Description
This is the first ever Linux Command Line Administration Masterclass for HPC and Scientific Computing on the Udemy platform. The 10.5+ hours of premium quality video instructions will be helpful both for the aspiring Linux and High-performance/ Scientific computing systems users, who must run applications on thousands of nodes.
WHY LINUX FOR SCIENTIFIC COMPUTING?
If you look at the current Top500 supercomputer rankings, majority out of the 500 just simply say they are running Linux and graduates from any disciplines with Linux, HPC and Scientific Computing knowledge are being paid salary over $100K on average. Linux has long provided an outstanding operating system for a wide range of users in a variety of settings. Therefore, this course is titled "Linux for HPC Systems and Supercomputing".
Students purchasing this course will receive free access to the interactive version (with Scientific code playgrounds) of this course from the Scientific Programming School. Instructions to join are given in the bonus content section. Upon successful completion, students will have the knowledge and skills to:
Use & administer Linux-based HPC systems with proficiency and confidence; and
Use Linux HPC computing and software appropriately in scientific or engineering problems.
Students purchasing this course will receive free access to the interactive version (with Scientific code playgrounds) of this course from the Scientific Programming School (SCIENTIFIC PROGRAMMING IO). Based on your earlier feedback, we are introducing a Zoom live class lecture series on this course through which we will explain different aspects of Linux command line for Data analytics. Live classes will be delivered through the Scientific Programming School, which is an interactive and advanced e-learning platform for learning scientific coding.
MONEY BACK GUARANTEE IF NOT 100% SATISFIED!
When you enroll you will get lifetime access to all of the course contents and any updates and when you complete the course 100% you will also get a Certificate of completion that you can add to your resumé/CV to show off to the world your new-found Linux & Scientific Computing Mastery! Don't forget to join our Q&A live community where you can get free help anytime from other students and the instructor. This awesome course is a component of the Learn Scientific Computing master course.
So What are you Waiting For? Click that shiny enroll button and we'll See you inside ;) FIVE STARS ⭐⭐⭐⭐⭐ 10.5+ HRS OF AWESOME VIDEOS!
Who this course is for:
- Students, researchers and programmers from any discipline
Instructors
The Scientific Programming Instructor Team helps you to learn the use of scientific programming languages, such as CUDA, Julia, OpenMP, MPI, C++, Matlab, Octave, Bash, Python Sed and AWK including RegEx in processing scientific and real-world data. The teamed is formed by PhD educated instructors in the areas of Computational Sciences.
Scientific programming is a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems.
The Scientific Programming School, with 60,000+ students is an awesome e-education start-up initiative to provide professional training and practice courses for Scientific Coding, Linux, and Big Data. It is also an interactive and advanced e-learning platform that gives you the opportunity to run scientific codes/ OS commands as you learn with playgrounds and Interactive shells inside your browser. Scientific Programming Instructors specialize on Linux, Devops, HPC and Data Science coding with scientific programming. Currently we support three OS (Ubuntu, RHEL and SuSE) and 50+ programming languages including the commercial ones like Matlab. At the Scientific Programming School you start learning immediately instead of fiddling with OS, VMs, SDKs and/ IDEs setups. It‘s all setup with Docker on the cloud.