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Description: This training provides an overview of Research Computing resources available to the Lehigh research community.

Description: This training provides a hands on introduction to using the SLURM scheduler to submit and monitor jobs. SLURM is the scheduler on Lehigh's HPC resource, Sol, and national supercomputing resources including XSEDE and NERSC.

Prerequisites: An account on Sol or an account on national supercomputing resources (XSEDE, DOE, etc) that uses SLURM.

Familiarity with Linux/Unix environment, basic command and *nix editors such as vi or emacs is mandatory.

Description: Open OnDemand (OOD) is an NSF-funded open-source HPC portal developed by the Ohio Supercomputing Center. The goal of OOD is to provide an easy way for system administrators to provide web access to their HPC resources. This tutorial introduces OOD to access Lehigh's Sol cluster.

Prerequisites: An account on Sol with an active allocation and a web browser. A Lehigh IP or VPN required.

Description: This seminar is geared towards users who wish to bring or build their own software stack to use on Sol and Hawk (or even local linux systems). Topics to be covered include best practices for installing packages using make, cmake and configure, SPACK package manager, and Singularity. 

Prerequisites: Some familiarity with compilers, and linux environment is required.

Description: Linux is a free and open source operating system that is the OS of choice of the world's leading supercomputers as well as LTS HPC clusters and some computer labs at Lehigh. This session will provide an introduction to the linux/unix environment, command line basics, logging in to remote system, transferring data, vi/emacs editors etc to get started with using a Linux/Unix based computer. This training is geared towards researchers who want to learn or need to learn how to use a linux/unix based resource.

Description: In this tutorial, you will learn the basics of R, including language fundamentals, data types, functions and basic programming including File I/O.

Prerequisites: Programming background is beneficial but not required.

Description: This tutorial provides a hands on introduction to Data Visualization using the R programming language

Prerequisites: Programming background in R is required.

Description: Shiny Apps, interactive web applications built using R programming language, have grown in popularity. This session will provide attendees experience using the Shiny package and the idea of reactive programming, which forms the basis of building an interactive web application.

Prerequisites: Programming background in R is required.

Description: In this seminar, you will learn the basics of Python, including language fundamentals and basic programming.

Prerequisites: Programming background is beneficial but not required.

Description: Data Structures are the fundamental constructs around which you build your programs. Python is a high-level, interpreted, interactive and object-oriented scripting language using which we can study the fundamentals of data structure in a simpler way as compared to other programming languages. In this seminar we are going to study a short overview of some frequently used data structures in general and how they are related to some specific python data types.

Prerequisites: Programming background in Python is required. Knowledge of data structure concepts is beneficial but not required.

Description: This seminar provides a hands on introduction to Data Visualization using the Python programming language.

Prerequisites: Programming background in Python is required.

Description: Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence (AI) based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. In this two part seminar you’ll learn the basic machine learning concepts: supervised and unsupervised learning, classification and regression algorithms. This is a two part seminar.

Prerequisites: Basic knowledge of general CS concepts such as data structures, linear algebra and design of algorithm is required.

Description: Text mining, also known as Text Analytics is the process of deriving high-quality information from text. It is the process of examining large collections of written resources to generate new information and to transform the unstructured text into structured data for use in further analysis. In this seminar you’ll learn the basic introduction to text analysis, different steps of text analysis: gathering textual data, cleaning and preparing textual data , analyzing the data (ETL) and visualizing textual data using tools from the HathiTrust Research Center (HTRC).

Prerequisites: Programming background is required. Basic knowledge of general CS concepts such as data structures, linear algebra and design of algorithms is required.

Description: MATLAB is a programming platform designed specifically for engineers and scientists. MATLAB is a special-purpose language that is an excellent choice for writing moderate-size programs that solve problems involving the manipulation of numbers. MATLAB is easy to learn, versatile and the design of the language makes it possible to write a powerful program in a few lines. Using MATLAB, you can: Analyze data, Develop algorithms and Create models and applications. In this seminar you’ll learn the basics of MATLAB, including language fundamentals and basic programming that will help you achieve the above functionalities.

Prerequisites: Programming background is beneficial but not required.