THECB Micro-credential Courses

HPRC offers THECB micro-credential courses throughout the semesters.

Upcoming Micro-credential Courses

Fundamentals of Cybersecurity

Description:
This course introduces students to the introductory concepts and terminology of cybersecurity. This includes fundamental security principles and the historical cybersecurity attacks.

Prerequisites: None
Registration Link: https://cvent.me/1lx95q

Parallel Computing Using OpenMP

Description:
This course will introduce students to parallelizing their code using OpenMP. Topics covered will include OpenMP concepts. OpenMP program layout, worksharing constructs, synchronization pragmas, and OpenMP tasks.

Prerequisites: Familiarity with coding in either C/C++, or Fortran. Basic knowledge of operating systems.
Registration Link: https://cvent.me/Vma0PB

Parallel Computing Using MPI

Description:
This course covers the Message Passage Interface (MPI), a standard library to create parallel codes for distributed systems. Topics covered include, MPI terminology, Communicators,Point to Point communications, and collective communications.

Prerequisites: Familiarity with coding in either C/C++, or Fortran. Basic knowledge of operating systems and computer architecture.
Registration Link: https://cvent.me/bgBawM

Fundamentals in Python Programming

Description:
This course covers the most important core components of Python programming at the introductory level. Students will learn fundamental programming concepts such as variables, data structures, flow control, and object-oriented programming. Topics and exercises are selected to be relevant for scientific research applications.

Prerequisites: None
Registration Link: https://cvent.me/1loOLa

Intermediate Python Programming For Data Science

Description:
This course covers a selection of scientific programming tools commonly used in Python programming at the intermediate level. Students will learn research techniques such as manipulating and visualizing data, exploring functions, modeling, and retrieving data from the internet. Topics and exercises are selected to be relevant for data science applications. Tools are drawn primarily from the libraries NumPy, SciPy, Matplotlib, and Pandas.

Prerequisites: Fundamentals of Python Course -or- mastery of core Python programming principles and familiarity with the Google Colab integrated development environment.
Registration Link: https://cvent.me/ea9zew

Advanced Python Programming for Data Science

Description:
This course covers a selection of scientific programming tools occasionally used in Python programming at the advanced level. Students will work with multi-dimensional data and upgrade existing workflows to leverage parallel computing. Topics and exercises are selected to be relevant for data science applications. Tools are drawn primarily from the libraries Xarray and Dask.

Prerequisites: Intermediate Python Course -or- mastery of the array and dataframe data structures and familiarity with the Google Colab integrated development environment.
Registration Link: https://cvent.me/VmeVmM

Fundamentals R Programming

Description:
This course is an introduction to the R programming language and covers the fundamental concepts needed to operate in the R environment. This course assumes no prior experience with R.

Prerequisites: Users will need access to a computer where they can install RStudio. Installation instructions are included in the course.
Registration Link: https://cvent.me/Q8erEx

Intermediate R Programming

Description:
This course covers intermediate concepts in the R programming language and can be taken as a stand-alone course or after completion of the Fundamentals of R programming course.

Prerequisites: Users will need access to a computer with RStudio with the packages shiny, learnr, and ggplot2 installed. Familiarity with data types, variables, built-in functions, vectors, and loops is strongly encouraged.
Registration Link: https://cvent.me/4rZLg9

Fundamentals of Artificial Intelligence and Machine Learning

Description:
Artificial Intelligence (AI) and Machine Learning (ML) technologies such as virtual assistants and recommender systems have changed our daily lives. This course mainly introduces some fundamentals of AI and ML including their relationship, different types of data, training and testing, common types of learning techniques (supervised and unsupervised learning) and applications (regression, classification, and clustering).

Prerequisites: Basic python programming skills.
Registration Link: https://cvent.me/A9BLb1

Introduction to Deep Learning with TensorFlow

Description:
This course gives a brief introduction to deep learning with TensorFlow, an open-source software library for machine intelligence. The basic concepts of deep learning methods will be covered. TensorFlow will be introduced with examples.

Prerequisites: Basic python programming skills.
Registration Link: https://cvent.me/Nv1e8B

Introduction to Deep Learning with PyTorch

Description:
This course introduces the fundamentals of deep learning with PyTorch, a free and open-source machine learning framework developed primarily by Facebook's AI Research (FAIR) Lab. It will cover the basic concepts of deep learning and PyTorch with examples. PyTorch is based on the Torch library and can be used for various applications such as computer vision. It provides tensor computing that could be accelerated with GPUs.

Prerequisites: None
Registration Link: https://cvent.me/ED2dbv

Using SciKit-learn for Artificial Intelligence and Machine Learning

Description:
The first module of this course introduces some fundamentals of AI and ML including their relationship, different types of data, training and testing, common types of learning techniques (supervised and unsupervised learning) and applications (regression, classification, and clustering). The second module introduces some commonly used machine learning algorithms.

Prerequisites: Basic python programming skills.
Registration Link: https://cvent.me/VmWWoQ

RNA-seq and Differential Expression

Description:
This course covers the basic concepts and methodologies needed to conduct differential expression analyses with RNA-seq data.

Prerequisites: This course requires access to the Texas A&M HPRC Grace cluster.
Registration Link: https://cvent.me/eaG0Bb

Short Variant Discovery

Description:
This course covers the bioinformatic methods used to identify short genetic variants in second generation sequencing data.

Prerequisites: This course requires access to the Texas A&M HPRC Grace cluster.
Registration Link: https://cvent.me/eaG9mz

Metagenomics

Description:
This course covers the basic concepts and methods used in analyzing metagenomic data sets.

Prerequisites: This course requires access to the Texas A&M HPRC Grace cluster.
Registration Link: https://cvent.me/WXwNXa

ChIP-seq

Description:
This course covers the basic concepts and methodologies needed to perform analysis of ChIP-seq data.

Prerequisites: This course requires access to the Texas A&M HPRC Grace cluster.
Registration Link: https://cvent.me/naOk52

Fundamentals of Linux

Description:
This course introduces basic Linux commands commonly used for management of files and directories (copy, move, delete, compress, extract, archive, transfer…), I/O redirection, customizing environment, and text processing with vi. In this class, students will be able to practice basic Linux operations using a live terminal at no charge with Google Colab through a web browser.

Prerequisites: None
Registration Link: https://cvent.me/q3Oq5Z

Cloud Computing: Linux for Administrators

Description:
This course introduces basic Linux administration skills including account management (adding/modifying/deleting users and groups), packages installation, monitoring disk usage, and process control. Students will also be able to learn text processing with vi, sed and awk utilities, as well as bash scripting for task automation. In this class, students will be able to practice basic Linux administration tasks using a live terminal at no charge with Google Colab through a web browser. Aspiring cloud professionals will also benefit from understanding Linux administration as it serves as the basis of most cloud instances.

Prerequisites: None
Registration Link: https://cvent.me/oKO3rV