SCINet Scientific Computing
Free Online Computational Training Resources
There are a number of free training resources on scientific computing available to ARS scientists and collaborators. Check out these curated collections of learning resources by topic.
| Programming Languages | Analysis Types | Best Practices and Tools |
|---|---|---|
| MATLAB Programming | Artificial Intelligence and Machine Learning | Database Management |
| Python Programming | Bioinformatics | Data Management |
| R Programming | Geospatial | Reproducibility & Productivity Tools |
| SAS Programming and JMP | Statistics | Git and GitHub |
| SQL | Ecological and Earth Sciences |
Additionally, SCINet regularly hosts virtual trainings for USDA ARS scientists and collaborators. In addition to the training resources list on this page, take a look at the SCINet Learning Path and the upcoming training events.
How to Access Training on Different Platforms
AgLearn and LinkedIn Learning
AgLearn hosts multiple free learning courses and learning platforms including LinkedIn Learning and Skillsoft Percipio.
SCINet has created a number of collections and learning paths in LinkedIn Learning. Login to LinkedIn Learning and and search the keyword SCINet for all curated collections.
All federal USDA permanent and term employees should be able to access the courses listed on this free online training page by logging into LinkedIn Learning via AgLearn then following the posted links.
Non-federal USDA employees may access AgLearn/LinkedIn Learning using the following steps:
- Go to aglearn.usda.gov but DO NOT LOG IN
- On the “Welcome to AgLearn” page, click on LinkedIn Learning
- Follow the instructions to “access your LinkedIn Learning account directly” by following the link and logging in with your eAuthentication credentials. (Do not log in to AgLearn)
- Find any of the AgLearn/LinkedIn trainings listed on this page by typing the title of the course in the LinkedIn Learning search bar.
Non-federal USDA employees (contractors) may be granted access to other AgLearn courses (i.e. Percipio/Softskills) on a case-by-case basis, but this is not guaranteed due to licensing restrictions. Please have your supervisor contact your Agency AgLearn Point of Contact and provide a justification stating how a particular training will help the researcher carry out the mission of the agency.
Contact your Agency AgLearn Point of Contact with further questions about how to access AgLearn courses.
Coursera and EdX
Many Coursera and EdX courses can be audited for free (i.e. no certification which requires a fee). For Coursera, licenses are available to ARS scientists and support staff through the SCINet Program (see below for details).
For EdX click enroll on a particular course, create an EdX account, and choose the free audit option.
For Coursera see the full list of free Coursera courses. These courses offer a ‘Full Course, No Certificate’ option. This option lets a user see all course materials, submit required assessments, and get a final grade, but does not provide a certificate.
ARS scientists and staff also have the option to take some courses in audit mode, which provides visibility of most course materials for free but does not provide access to graded assignments and a Certificate.
If the audit option is not avaiable or a certificate is required, ARS Scientists and staff can request a SCINet-sponsored Coursera license, which provides 3-months of full access to Coursera. If more than 3 months is needed to complete a course, a new request will need to be submitted the following quarter to secure the license for another 3 months.
SCINet-funded Coursera Licenses: ARS scientists can request a Coursera license for a three month period to gain access to the full list of Coursera catalogue options related to scientific computing, statistics, and AI. This license also allows ARS scientists to get certifications. To request a license, please visit the SCINet Coursera page.
SAS and JMP
While links below to sas.com and jmp.com videos are immediately accessible, SAS and JMP course offerings on sas.com and jmp.com (not the courses offered through AgLearn) require the learner to create a free account with their email address and password.
To start a course on sas.com:
Follow the link to the course from this page, scroll down the course overview page to the “Self-Paced e-Learning” section, under “Add to Cart” on the right click “Start”, follow the instructions to create a profile for a new user.
To start a course on jmp.com:
Follow the link to the course from this page, from the JMP course page click “Enroll Now”, follow the instructions to create a profile for a new user.
Python Programming
R Programming
| Course Title/Link | Platform or Site | Time Investment |
|---|---|---|
| SCINet: R Programming Collection | AgLearn/LinkedIn | 1-3 hrs/course |
| Introduction to R Programming | AgLearn/Skillsoft | ~2.5 hrs |
| Debugging in R | AgLearn/Skillsoft | 1 hr |
| Programming Techniques in R | AgLearn/Skillsoft | ~2 hrs |
| Domain-Specific Tools in R | AgLearn/Skillsoft | ~1 hr |
| R for Data Science: Data Structures | AgLearn/Skillsoft | 1 hr |
| R for Data Science: Importing and Exporting Data | AgLearn/Skillsoft | 1 hr |
| R for Data Science: Data Exploration | AgLearn/Skillsoft | 1 hr |
| R for Data Science: Regression Methods | AgLearn/Skillsoft | 1 hr |
| R for Data Science: Classification & Clustering | AgLearn/Skillsoft | 1 hr |
| R for Data Science: Data Visualization | AgLearn/Skillsoft | 1 hr |
| Advanced R Programming | Coursera | 12 hrs |
| Data Science Specialization | Coursera | 8 mo; 6 hrs/wk |
| Data Science: R Basics | EdX | 8 wks; 1-2 hrs/wk |
| R Tutorial | Kelly Black, UGA Dept of Mathematics, cyclismo.org | 2+ hrs |
| Intro and Advanced R Tutorials | W.B. King, Coastal Carolina Univ., coastal.edu | 2+ hrs |
| R Basics Tutorials | Coding Club | varies |
| Learn R and Data Science Interactively with swirl | swirlstats | varies |
SAS Programming and JMP
| Course Title/Link | Platform or Site | Time Investment |
|---|---|---|
| SAS e-learning (Webinars, Academic Software, and How-to Videos | sas.com | varies |
| How-to SAS video tutorials | sas.com | 5–10 min videos |
| SAS Programming 1: Essentials | sas.com | 14 hrs |
| Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression | sas.com | 21 hrs |
| SAS Programming for R Users | sas.com | 14 hrs |
| SCINet: SAS Programming Collection | AgLearn/LinkedIn | 1-3 hrs/course |
| Statistical thinking for Industrial Problem Solving | jmp.com | 20-30 hrs |
| On-demand Webinars – Mastering JMP | jmp.com | ≤ 1 hr |
| SAS Base SAS 9 Programming: The SAS environment | AgLearn/Skillsoft | ~2 hrs |
| SAS Base SAS 9 Programming: Introduction to Data Sets | AgLearn/Skillsoft | ~2 hrs |
| SAS Base SAS 9 Programming: Working with Data Sets | AgLearn/Skillsoft | ~2 hrs |
| SAS Base SAS 9 Programming: Creating Reports | AgLearn/Skillsoft | ~2 hrs |
| SAS Base SAS 9 Programming: Inputs and Outputs | AgLearn/Skillsoft | ~2 hrs |
| SAS Base SAS 9 Programming: Data Structures | AgLearn/Skillsoft | ~2 hrs |
MATLAB Programming
| Course Title/Link | Platform or Site | Time Investment |
|---|---|---|
| SCINet: Matlab Learning Pathway | AgLearn/LinkedIn | 4.5hrs |
| Practical Data Science with MATLAB Specialization | Coursera | 2 mo; 10 hrs/wk |
| Exploratory Data Analysis with MATLAB | Coursera | 5 wks; 4 hrs/wk |
| Data Processing and Feature Engineering with MATLAB | Coursera | 26 hrs |
| Predictive Modeling and Machine Learning with MATLAB | Coursera | 4 hrs |
| Data Science Project: MATLAB for the Real World | Coursera | unknown |
| MATLAB and Octave for Beginners | EdX | 4 wks; unknown hrs |
General Statistics
| Course Title/Link | Platform or Site | Time Investment |
|---|---|---|
| SCINet: Statistics Collection | AgLearn/LinkedIn | 1-3 hrs/course |
| SCINet Coursera Collection (Scroll down to see full course collection in Statistics) | Coursera | Varies |
| Statistical Learning (using R) | EdX | 9 wks; 3-5 hrs/wk |
| Statistical Predictive Modelling and Applications | EdX | 9 wks; 3-5 hrs/wk |
| Statistical Rethinking: A Bayesian Approach-Connecting Scientific Models to Evidence | Github | 10 wks; 1-3 hrs/wk |
Artificial Intelligence and Machine Learning
| Course Title/Link | Platform or Site | Time Investment |
|---|---|---|
| SCINet: Machine Learning and AI Collection | AgLearn/LinkedIn | 1-3 hrs/course |
| Machine Learning & AI Foundations: Recommendations | AgLearn/LinkedIn | ~4 hrs |
| Linear Regression Models: Building Simple Regression Models with Scikit Learn and KerasSCORM package (Python) | AgLearn/Skillsoft | 1 hr |
| SCINet AI-COE Coursera Collection | Coursera | Varies |
| AI for Everyone: Master the Basics | EdX | 4 wks; 1-2 hrs/wk |
| Deep Learning Essentials | EdX | 5 wks; 4-6 hrs/wk |
| Machine Learning with Python: A Practical Introduction | EdX | 5 wks; 4-6 hrs/wk |
| Deep Learning Fundamentals with Keras | EdX | 5 wks; 2-4 hrs/wk |
| Deep Learning with Python and PyTorch | EdX | 6 wks; 2-4 hrs/wk |
| Deep Learning with TensorFlow | EdX | 5 wks; 2-4 hrs/week |
| Using GPUs to Scale and Speed-Up Deep Learning | EdX | 5 wks; 2-4 hrs/wk |
Geospatial
| Course Title/Link | Platform or Site | Time Investment |
|---|---|---|
| SCINET: GIS Collection | AgLearn/LinkedIn | 1-3 hrs/course |
| ESRI GIS Videos (on many topics including machine learning) | esri.com | varies |
| Fundamentals of GIS | Coursera | 3-5 hrs/4wk |
| GIS Data Formats, Design and Quality | Coursera | 2-3 hrs/4wk |
| Geospatial and Environmental Analysis (GIS) | Coursera | 3-4 hrs/4wk |
| Imagery, Automation, and Applications (GIS) | Coursera | 2-5 hrs/4wk |
| Introduction to GIS Mapping | Coursera | 18 hrs |
| GIS Data Acquisition and Map Design | Coursera | 21 hrs |
| Spatial Analysis and Satellite Imagery in GIS | Coursera | 16 hrs |
| Intro to GEE | Coding Club | varies |
| GEE 101: Intro to GEE for beginners Part 1 | Google Earth Outreach | 1.5 hr |
| GEE 101: Intro to GEE for beginners Part 2 | Google Earth Outreach | 1.5 hr |
| Training Materials from 3 GEE Workshops | GEE tutorials | 2 hrs each |
| Spatial Data Science (R) | Geospatial and Farming Systems Research Consortium (GFC) | varies |
Data Management
| Course Title/Link | Platform or Site | Time Investment |
|---|---|---|
| Data Science Overview | AgLearn/Skillsoft | 1 hr |
| Data Gathering | AgLearn/Skillsoft | ~1.5 hrs |
| Data Filtering | AgLearn/Skillsoft | 1 hr |
| Data Transformation | AgLearn/Skillsoft | 1 hr |
| Data Exploration | AgLearn/Skillsoft | 1 hr |
| Data Integration | AgLearn/Skillsoft | 1 hr |
| Data Analysis Concepts | AgLearn/Skillsoft | ~1.5 hrs |
| Data Classification and Machine Learning | AgLearn/Skillsoft | ~1.5 hrs |
| Data Communication and Visualization | AgLearn/Skillsoft | ~1.5 hrs |
| Data Management Skill Building Hub | DataONE | varies |
| Data Management Plan Guidance | National Agricultural Library | varies |
Bioinformatics
| Course Title/Link | Platform or Site | Time Investment |
|---|---|---|
| Bioconductor Courses and Analysis Tools | bioconductor.org | varies |
| Online Bioinformatics Tutorials from NIH | NIH | varies |
| Bioinformatics On-line Courses and Tutorials | Color Base Pair | varies |
| Bioinformatics Courses | Class Central | varies |
| Bacterial Genomes: From DNA to Protein Function using Bioinformatics Course | Future Learn | 2 wks; 5 hrs/wk; next course starts 4/20 |
| Bacterial Genomes: Accessing and Analysing Microbial Genome Data Course | Future Learn | 3 wks; 5 hrs/wk; next course starts 5/11 |
| Bioinformatics Courses On Edx | EdX | varies |
| Stastics and R (basics for life sciences | EdX | 2-4 hrs/4wk |
Ecological and Earth Sciences
| Course Title/Link | Platform or Site | Time Investment |
|---|---|---|
| Ecological Models and Data in R (book with pdf chapters) | Princeton University Press | varies |
| Data Science for Ecologists and Environmental Scientists Course | Coding Club/The Data Lab | varies |
| ZevRoss Tech Blog (mostly R resources) | ZevRoss | varies |
| Machine Learning and Visualization Tutorials in Python for Earth Science | earthml (NASA) | varies |
Git and GitHub
| Course Title/Link | Platform or Site | Time Investment |
|---|---|---|
| What is Git? (Interactive tutorial) | atlassian.com | 45 min |
| Intro to GitHub for Version Control | Coding Club | varies |
| Setting up a GitHub Repository for Your Lab | Coding Club | varies |
| SCINet: Git and Github Collection | AgLearn/LinkedIn | 1-3 hrs/course |
Reproducibility, Productivity, and Integration Management Tools
(also see Git and GitHub links above)
| Course Title/Link | Platform or Site | Time Investment |
|---|---|---|
| RStudio | rstudio.com | varies |
| Introducing Jupyter | AgLearn/LinkedIn | ~1 hr |
| Open Source Tools for Data Science | Coursera | 3 wks; 3 hrs/wk |
| Getting Started with R Markdown | Coding Club | varies |
| Learning Markdown | AgLearn/LinkedIn | ~ 1hr |
| Creating Reports and Presentations with R Markdown and RStudio | AgLearn/LinkedIn | ~2.5 hrs |
| EndNote Essential Training | AgLearn/LinkedIn | ~1.5 hrs |
| Coding Etiquette | Coding Club | varies |
| Transferring Quantitative Skills Among Scientists | Coding Club | varies |
| Reproducible Research | Coursera | 11 hrs |
| Work Smarter, Not Harder: Time Management for Personal & Professional Productivity | Coursera | 3 hrs |
| Data Science Productivity Tools | EdX | 1-2 hrs/8wk |
| Unix Tools: Data, Software, and Production Engineering | EdX | 4-6 hrs/6wk |
Database Management
| Course Title/Link | Platform or Site | Time Investment |
|---|---|---|
| Simple Retrieval Queries in MySQL Workbench | Coursera | 1-2 hrs |