2026 nanocourses

FALL

Please use the button below to register for a Fall nanocourse. You will select the nanocourse that you wish to register for from a dropdown menu. Once you have submitted the registration form for one nanocourse, you will see an option to go back to the beginning and submit another one.

Register for a Fall Nanocourse (link coming soon)

For course information including registration close dates, pleas expand your nanocourse of interest from accordion list below.

• Data Science using R

  Data Science using R

  Dates: September 1 & 3, 2026 [dates are non-consecutive]
  Time: 9 AM to 5 PM both days
  Location: G9.250A

  This course would benefit students who pursue advanced R programing techniques for data science. We will provide information about key elements for data science and machine learning, including how to properly preprocess data, how to select meaningful features from the data, how to identify data clusters, and how to build a predictive model. We will then cover statistical test basics and provides hands-on sessions on how to utilize the statistics for biomarker discoveries. We will cover Data preprocessing, Feature selection/dimensionality reduction, Data clustering, and Predictive models on Day 1. Day 2 will cover Statistical test basics, Biomarker discovery I (metabolomics/proteomics data), and Biomarker discovery II (RNA-seq data).

  Prerequisite: Fluency with R programming language.

  Registration closes 8/4/2026, 5 PM. Any entries submitted for this nanocourse after this date and time will not be considered.

  Academic credit (1 credit hour) is available.
  UTSW PostDocs - PDRT 5095-01
  UTSW Grad Students - course number coming soon!

  Lead Instructor: Jeon Lee, Ph.D. 
  Other Instructors: Ermis-loannis Michail Delopoulos, M.S., Omar Halawa, M.S.

• Science Communication

  Science Communication

  Dates: September 14 & 16, 2026 [dates are non-consecutive]
  Time: 9 AM to 5 PM both days
  Location: NL3.114

  This two-day hands-on nanocourse, offered in collaboration with the Teaching & Science Communication Club (TaSC) at UTSW, provides participants with essential skills for effective scientific communication. Topics covered include fundamentals of science communication, best practices for clear and impactful messaging, and key themes across various communication formats. The workshop will also highlight appropriate use of AI in communication and responsible reporting of AI. Participants will apply learned principles to refine their own projects such as presentations, posters, manuscripts, or grant proposals with personalized feedback and real-time guidance. By the end of this course, participants will be equipped to communicate their research more effectively to diverse audiences.

  Prerequisite: Familiarity with MS Office - Word, PPT, Excel.

  Registration closes 8/7/2026, 5 PM. Any entries submitted for this nanocourse after this date and time will not be considered.

  Academic credit (1 credit hour) is available.
  UTSW PostDocs - PDRT 5096-01
  UTSW Grad Students - course number coming soon!

  Lead Instructor: Prapti Mody, Ph.D. 
  Other Instructors: Stuart Ravnik, Ph.D., Sarah Jobbins, Innesa Leonovich, Brandon Smith.

• Introduction to Linux

  Introduction to Linux

  Dates: September 22 & 23, 2026
  Time: 9 AM to 5 PM both days
  Location: G9.102

  Linux is a robust and versatile operating system favored by programmers and system administrators. Known for its stability and adaptability, it powers devices ranging from smartphones to supercomputers. Linux is particularly popular in academic and scientific fields due to its customizability and extensive suite of integrated tools. This two-day workshop welcomes beginners interested in learning Linux. It will introduce fundamental concepts to get you started on your Linux journey. This workshop lays the groundwork for anyone new to Linux. Those working in research, scientific computing, or computationally demanding fields will particularly benefit from its HPC emphasis.

  Prerequisite: None.

  Registration closes 8/17/2026, 5 PM. Any entries submitted for this nanocourse after this date and time will not be considered.

  Academic credit (1 credit hour) is available.
  UTSW PostDocs - PDRT 5095-02
  UTSW Grad Students - course number coming soon!

  Lead Instructor: Liqiang Wang, M.S. 
  Other Instructors: BioHPC staff.

• Time Series Analysis

  Time Series Analysis

  Dates: September 22 & 24, 2026 [dates are non-consecutive]
  Time: 9 AM to 5 PM both days
  Location: G9.250A

  This nanocourse provides an interdisciplinary introduction to time series analysis, combining statistical modeling, signal processing, and applications in biomedical and neuroscience data. Participants will build a foundation in key concepts such as stationarity, autocorrelation, and ARIMA modeling to understand temporal structure in real-world datasets. The course also introduces a signal processing perspective, including time & frequency analysis, digital filtering, and physiological signal processing. Building on these foundations, the course explores analysis of brain data (EEG and fMRI data) with a focus on biomarker and functional connectivity. Participants will also learn advanced approaches for modeling neural activity. Hands-on sessions will guide learners through real examples, enabling them to apply concepts to real data.

  Prerequisite: Familiarity with MATLAB and time series data.

  Registration closes 8/17/2026, 5 PM. Any entries submitted for this nanocourse after this date and time will not be considered.

  Academic credit (1 credit hour) is available.
  UTSW PostDocs - PDRT 5095-03
  UTSW Grad Students - course number coming soon!

  Lead Instructor: Jeon Lee, Ph.D. 
  Other Instructors: Wenhao Zhang, Ph.D., Srinivas Kota, Ph.D., Sameer Rajesh.

• Introduction to Python

  Introduction to Python

  Dates: September 30 & October 1, 2026
  Time: 9 AM to 5 PM both days
  Location: G9.102

  This two-day intensive course is designed to introduce Python programming to graduate students and postdocs in biomedical fields. The course aims to provide a solid foundation in Python, emphasizing practical applications relevant to research. Participants will learn about Python's structures, flow control, data handling, basic analysis techniques, and how to write clean, reusable code.

  Prerequisite: None.

  Registration closes 8/17/2026, 5 PM. Any entries submitted for this nanocourse after this date and time will not be considered.

  Academic credit (1 credit hour) is available.
  UTSW PostDocs - PDRT 5143-01
  UTSW Grad Students - course number coming soon!

  Lead Instructor: Kevin Dean, Ph.D. 
  Other Instructors: Conor McFadden.

• Introduction to ATAC-seq

  Introduction to ATAC-seq

  Dates: October 7 & 8, 2026
  Time: 9 AM to 5 PM both days
  Location: J1.700

  This wet lab nanocourse provides an intensive introduction to Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq), a powerful epigenomic method used to map open chromatin regions, transcription factor occupancy, and regulatory elements genome-wide. Participants will learn the biological principles underlying chromatin accessibility and how ATAC-seq can be applied to study gene regulation and enhancer dynamics. The course will cover experimental design, sample preparation, nuclei isolation, transposition reactions, library construction, sequencing considerations, and quality control metrics. In addition, trainees will be introduced to computational analysis workflows, including read alignment, peak calling, differential accessibility analysis, motif enrichment analysis, and integration with RNA-seq and ChIP-seq datasets. Common technical challenges, troubleshooting strategies, and emerging applications including single-cell ATAC-seq and multiomic approaches will also be discussed. By the end of the course, participants will understand both the experimental and computational foundations of ATAC-seq and be prepared to design, execute, and interpret ATAC-seq experiments in their own research programs.

  Prerequisite: Familiarity with micropipetting.

  Registration closes 8/31/2026, 5 PM. Any entries submitted for this nanocourse after this date and time will not be considered.

  Academic credit (1 credit hour) is available.
  UTSW PostDocs - PDRT 5095-04
  UTSW Grad Students - course number coming soon!

  Lead Instructor: Edward Grow, Ph.D. 
  Other Instructors: Camila Perez Lujan, Lei Wang, Ph.D., Purbita Saha, Ryan O'Hara, Chenqian Liu, M.D., Sneh Koul, Tulip Nandu.

• Introduction to Diffusion/Flow Models

  Introduction to Diffusion/Flow Models

  Dates: October 20, 22, 27 & 29, 2026 [dates are non-consecutive]
  Time: 1 to 5 PM all four days
  Location: G9.102

  Diffusion and flow generative models have achieved remarkable results in generating images, videos, DNA sequences, and modeling proteins. This course explores the key principles behind diffusion and flow models. During the first part of course, participants will gain a theoretical understanding behind the original diffusion and flow models and become familiar with score-based generative stochastic differential equation models, flow matching ode models, and few step counter parts. During the second part of the course, students will learn about conditional diffusion/flow models and how to steer and finetune diffusion/flow models for conditional generation tasks. As a result of the course, participants will learn how to implement diffusion/flow models and how to generate various data modalities including images, proteins, and beyond.

  Prerequisite: Familiarity with deep learning principles, ability to train models on GPUs using python machine learning libraries such as Pytorch or Jax, and ideally some understanding of generative modeling.

  Registration closes 9/14/2026, 5 PM. Any entries submitted for this nanocourse after this date and time will not be considered.

  Academic credit (1 credit hour) is available.
  UTSW PostDocs - PDRT 5095-05
  UTSW Grad Students - course number coming soon!

  Lead Instructor: Satwik Rajaram, Ph.D. 
  Other Instructors: Dushyant Mehra, Ph.D.

• The AI Ready Scientist

  The AI Ready Scientist

  Dates: November 4 & 6, 2026 [dates are non-consecutive]
  Time: 9 AM to 5 PM both days
  Location: NL3.120

  This is a hands-on nanocourse designed to help graduate students, postdocs, and other biomedical researchers use artificial intelligence thoughtfully, effectively, and responsibly throughout the research process. Through short presentations, live demonstrations, and applied activities, participants will explore how AI can support literature discovery, scientific writing, data analysis, coding, experimental design, and visual communication while also learning to recognize its limitations, risks, and ethical challenges. The course emphasizes critical evaluation of AI-generated content, responsible use of sensitive data, transparency in research workflows, and the importance of maintaining human judgment. By the end of the course, participants will be better prepared to integrate AI into their work in ways that strengthen productivity, rigor, and scientific integrity.

  Prerequisite: Access to UTSW O365 and familiarity with popular chat-based LLMs as a user.

  Registration closes 9/21/2026, 5 PM. Any entries submitted for this nanocourse after this date and time will not be considered.

  Academic credit (1 credit hour) is available.
  UTSW PostDocs - PDRT 5096-02
  UTSW Grad Students - course number coming soon!

  Lead Instructor: Prapti Mody, Ph.D. 
  Other Instructors: John Carter, Ph.D., Will Bryant, Kevin Dean, Ph.D., Sourav Patnaik, Ph.D., Neha Ahuja, Ph.D.

New for Fall 2026 - Automated Process and Workflow

We have automated our workflow from REDCap to Sharepoint Lists to MS Excel, etc. Big kudos to our Senior Department Data Analyst, Sol Vedovato, for streamlining the flow with her superb coding skills!

1. Registering for upcoming nanocourses

   Registration opens mid-July for all nanocourses. Please view registration deadlines in individual course descriptions within accordion list above as they are staggered. 
   
   View nanocourses information in accordion list above → Go to registration via button on top of page → Choose nanocourse from dropdown menu → Fill out form → Submit form
   
   

2. Admission into a nanocourse (1 month before course date)

   Course instructors view registrants → Decisions added

   Accepted into applied nanocourse → Supervisor receives email + teams message to approve participation → If granted, registrant added to class roster

   Waitlisted → Notified if space opens by one week before class start → Supervisor approval → Added to class roster

   Not admitted → emailed notification
   
   

3. During and after the nanocourse

   Full attendance of all sessions documented on printed roster in classroom → Indicate if seeking credit and/or completion certificate → Complete mandatory course evaluation → Academic credit added to transcript by semester end and/or completion certificate issued
   
   

SUMMER

There are no nanocourses this Summer. We have moved the nanocourses administration to the Graduate School of Biomedical Sciences and are finalizing policies and procedures.

SPRING