Course Catalog

This one-hour online training will provide detailed information and demonstrations on how to manage data in Excel.   

By the end of this training, attendees will be able to:  

• Filter data by text, numbers, and date  

• Sort data alphabetically and by color  

• Remove duplicates  

• Split and combine columns  

• Create custom lists  

This is an introductory training for those who need to quickly learn basic Excel data management features and for those who are interested in a refresher.  

Basic knowledge of Excel is required.  

This two-and-a-half hour online training will introduce the fundamentals of conducting a meta-analysis. The focus will be on randomized clinical trials; however, the instructor will also briefly discuss the application of meta-analyses in laboratory and observational (epidemiological) studies. Time will be devoted to questions from attendees and references will be provided for in-depth self-study.    

By the end of this training, attendees will be able to:   

• Describe hypothesis testing and different study designs 

• Define what is a meta-analysis 

• List the steps to conduct 

• Explain where to find additional resources 

Attendees should have an acquaintance with basic statistical concepts (including, but not limited to: dichotomous and continuous outcomes, odds ratios, standard deviation and error, weighted average, fixed and random effects and associated models, etc.). However, it will only be necessary to understand the principles and interpretation of these ideas, not the underlying mathematics and calculations to learn the principles presented. This class will not contain a “hands-on” portion or a set of exercises to be completed in a statistical software package during the training or afterwards. 

This class will be taught by the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES). 

This one-hour online training introduces attendees to modeling and simulation of biological systems using MATLAB’s SimBiology and BioPipeline Designer toolboxes. SimBiology is a versatile toolbox for modeling, simulating, and analyzing dynamic biological systems such as metabolic pathways, signaling cascades, and pharmacokinetics/pharmacodynamics (PK/PD) models. BioPipeline Designer complements this by streamlining workflows for integrating biological data and automating computational analyses. 

By the end of this training, attendees will be able to: 

• Describe the capabilities and applications of SimBiology and BioPipeline Designer for modeling and analyzing biological systems. 

• Construct and parameterize basic models of biological processes using SimBiology’s graphical and programmatic interfaces. 

• Simulate dynamic behaviors of biological systems, such as time-course analyses, and interpret simulation results. 

• Automate and streamline data integration workflows using BioPipeline Designer to enhance reproducibility and efficiency. 

• Access and utilize resources for further learning, including tutorials, user guides, and MATLAB community forums 

Attendees are expected to be familiar with the basic functions of the MATLAB to be successful in this training. 

This one-hour online training will provide an overview of NIH Library services and information resources provided for HHS staff via the HHS Virtual Library.   

By the end of this training, attendees will be able to: 

• Demonstrate how to remotely access and login to the HHS Virtual Library online 

• Identify the NIH Librarian assigned to their agency 

• Describe information resources and services available for HHS staff 

• Search for and link to full text journal articles 

• Create a document delivery account and order documents 

Attendees are not expected to have prior knowledge of resources and services provided by the NIH Library for HHS staff.  This training is an excellent jumping off point for those interested in learning to use resources introduced in this class, such as an Introduction to EndNote Desktop, an Introduction to PubMed, and an Introduction to Scopus.  

This one-hour online training will provide an overview of NIH Library services and information resources provided for HHS staff via the HHS Virtual Library.   

By the end of this training, attendees will be able to: 

• Demonstrate how to remotely access and login to the HHS Virtual Library online 

• Identify the NIH Librarian assigned to their agency 

• Describe information resources and services available for HHS staff 

• Search for and link to full text journal articles 

• Create a document delivery account and order documents 

Attendees are not expected to have prior knowledge of resources and services provided by the NIH Library for HHS staff.  This training is an excellent jumping off point for those interested in learning to use resources introduced in this class, such as an Introduction to EndNote Desktop, an Introduction to PubMed, and an Introduction to Scopus.  

This one-hour online training is an introduction to the collection of NIH Library resources and services available to NIH staff. The NIH Library serves as the staff library for NIH. This training is designed to instruct attendees on the range of information support and how to navigate the Library’s website to access the information required to support their work. 

By the end of this training, attendees will be able to:  

• Explain the different missions of the NIH Library and the National Library of Medicine (NLM) 

• Access the NIH Library online catalog, journals, databases, PubMed @ NIH, and other resources 

• Identify Library services including Training, Translations, Literature searching, Editing, Bibliometrics, Data management, Publication support, etc. 

• Find and download Endnote (free for NIH staff) to laptop or computer 

Attendees are not expected to have prior knowledge of NIH Library products/tools to be successful in this training.  

This one and a half hour online training focuses on the practical use of NVivo by importing data, coding data, and then analyzing and visualizing textual data using NVivo, an analysis and visualization software for qualitative and mixed-methods research, evaluation, and literature reviews. 

By the end of this training, attendees will be able to:  

• Explain how to import various data types into NVivo software  

• Differentiate between codes and case attributes

• Describe options for querying and visualizing data in NVivo  

• Identify options for structuring code themes or code books within NVivo 

• Distinguish methods for coding textual data  

• Discuss options for comparing coding among collaborators 

 Requirement(s): 

• Attendees are expected to have basic familiarity with NVivo software. If new to NVivo, please attend Part 1 of the NIH Library NVivo series or review NVivo 15 Tutorials: Intro and Import . 

• Attendees are expected to have basic knowledge of qualitative analysis methods. For further reading on qualitative research, see the NIH Library webpage Qualitative Data Resources 

 Before this training, think about an upcoming project. What type(s) of data will you collect? How will you analyze the data? What will results look like?  

By the end of this training, attendees will be able to:  

• Describe key concepts in statistical procedures

• Understand the steps involved in hypothesis testing 

• Define p-values and be familiar with their appropriate uses 

• Describe confidence intervals and their uses

• Understand differences in types of data and how to summarize them 

• Describe bias and confounding

This one-hour online training will cover an overview of patent search tools, with a focus on search and analysis options in a variety of patent databases: Espacenet, Google Patents, PATENTSCOPE, Derwent Innovations Index, and Lens.org. During this training, the instructor will review patent search concepts including patent families, patent classification systems, and kind codes. Chemical structure and genetic sequence search options will also be covered. 

By the end of this training, attendees will be able to:  

This one-hour online training provides researchers with an overview of online resources for locating research datasets, data repositories, and data publications for data sharing and re-use. Participants will learn search strategies for locating datasets through federated data search portals and generalist data repositories, including directories for locating discipline-specific and institutional data repositories. An overview of key issues to consider when re-using datasets or when locating a data repository for sharing and preservation purposes will be discussed. 

By the end of this training, attendees will be able to:  

• Locate different types of data repositories and datasets 

• Identify issues to consider with data repositories 

• Discuss how data repositories can improve reproducibility

• Identify issues to consider when re-using datasets 

• Describe guidelines and resources for citing datasets 

Attendees are not expected to have any prior knowledge of these resources to be successful in this training. 

This one hour and fifteen-minute online training will provide an overview of databases and author profile websites to help locate experts in a research field. During this training, the instructor will review how to use tools to locate authors related to a specific topic, find algorithmically generated author profiles, and how to find author-maintained profiles. The instructor will also share how to identify additional citation and publication metrics for authors using InCites, including international and industry collaborations, first and last author positions, number of publications in high-impact journals, and more. The training will also address how to identify potential conflicts of interest when locating potential reviewers for grants and contracts.  

By the end of this training, attendees will be able to:  

• Locate top authors related to a topic 

• Find algorithmically generated author profiles 

• Find author-maintained profiles 

• Identify additional citation and publication metrics on authors 

• Describe potential conflicts of interest 

Attendees are not expected to have any prior knowledge of these resources to be successful in this training. 

In partnership with the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES), the NIH Library is offering this two-hour online training to assist researchers in writing a manuscript. Participants will become familiar with statistical issues that can arise as well as recommendations to prevent them. Most of the examples will be related to clinical research; however, anyone can benefit from the tips shared. 

By the end of this training, attendees will be able to:  

• Gain a better understanding of the structure of the statistical methods section in the manuscript 

• Relate the results section to the statistical methods section 

• Exercise caution in the interpretation of the analysis results 

Attendees are not expected to have any prior knowledge to be successful in this training. This class complements, How to Write a Research Paper Parts 1 & 2, as it specifically covers key points in writing the statistical portion of a manuscript – particularly for clinical research.  

In partnership with the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES), the NIH Library is offering this two-part online training for non-statisticians interested in understanding the basic, intuitive thinking behind the two schools of statistical inference: frequentist (known as classical) and Bayesian. 

Part 1 is a  two-hour online training that will address the frequentist approach and will cover the concepts of hypothesis testing, confidence intervals, Type I and Type II errors, statistical power, and p-values. Technical details will be kept to an absolute minimum.    

By the end of this training, attendees will be able to:  

• Understand how to use statistical concepts to test hypotheses 

• Interpret the results of statistical tests 

• Make informed decisions about the significance of findings while considering the potential for errors in the analysis 

Attendees are not expected to have any prior knowledge to be successful in this training. Although you may attend only one part of this series, attending both parts will give you a better sense of the contrast between these two statistical approaches. 

You must register separately for Part 2 of this class series.

This one and a half hour online training equips participants with powerful data wrangling techniques using R and the tidyverse ecosystem. The tidyverse is a cohesive ecosystem of R packages designed to make data science workflows more intuitive and efficient through consistent syntax and design principles. Designed for both beginners and those looking to refine their skills, this training addresses the challenges posed by messy datasets.  

By the end of this training, attendees will be able to

• Diagnose and address common data quality issues in clinical datasets.
• Apply systematic approaches to clean and standardize text, dates, and numerical values.
• Transform messy data and handle missing values using tidyverse functions, including appropriate imputation strategies.
• Design reproducible, automated data-cleaning workflows with tidyverse tools for transformation and aggregation.

Requirements 

Attendees are expected to have a basic understanding of R and RStudio. To proceed, attendees should have done the following:

• Installed R and RStudio.
• Have a basic understanding of R and RStudio.
• Reviewed our R basics training on the NIH Data Services: On Demand Content YouTube Playlist, if you are new to R.

This one-hour online training will cover how to sign up and access complimentary SAS training resources available to NIH and HHS employees. The instructor will demonstrate how to enroll in recommended SAS 9.4 trainings. 

By the end of this training, attendees will be able to:  

• Enroll in recommended SAS 9.4 trainings 

• Navigate complimentary tutorials, programming courses, and eLearning for SAS 

Attendees are not expected to have any prior knowledge of SAS to be successful in this training. 

This one and a half hour online training in the NIH Library Evidence Synthesis Review series provides an overview on how to use Covidence, a web-based tool, for your review. The training covers the basic features of Covidence, including set-up, importing and exporting records, screening, data collection, and risk of bias assessment. 

By the end of this training attendees will be able to: 

• Describe what Covidence is and how to request access 

• Setup Covidence prior to starting your review 

• Explain how to conduct title/abstract and full text screening, data collection, and risk of bias assessment 

• Understand how to pilot your methods with Covidence 

• Identify the process for exporting records 

Attendees are not expected to have prior knowledge of how to conduct a review.  It is recommended that those planning to undertake a review, should register for the Evidence Synthesis series that take a deeper dive into the required methods for each step in a review.