Events

Thursday, September 26, 2019 - 11:00am to 12:00pm
at IDRE Visualization Portal MS 5628

16% of UCLA undergraduate students have a disability. Help empower this growing population through accessible curriculum design and web content. In this session, you will learn the challenges for people with disabilities, understand the impact of assistive technology and screenreading software to “read text out loud”, and receive hands-on experience building an accessible document. We will also discuss some of the principals of Universal Design for Learning and how they might be applied in your course and research documents.

 

For all trainings, please bring your laptop. If needed, a laptop can be provided for you.


Monday, September 30, 2019 - 9:00am to Wednesday, October 2, 2019 - 5:00pm
at UCLA Math Sciences Building

The IDRE Statistical Consulting Group is excited to present two new statistical analysis training seminars from our partners at Stats Camp, which will be held here at UCLA from September 30 to October 2, 2019. Take advantage of this opportunity to build your data analysis skillset and to discuss your own research with two world-renowned experts! The two workshops are Structural Equation Modeling (SEM) Foundations, taught by Professor Todd D. Little (Texas Tech University) and Missing Data Analysis, taught by Professor Craig Enders (UCLA). 


Wednesday, October 9, 2019 - 2:00pm to 4:00pm
at IDRE Portal

We will discuss how to effectively run jobs on Hoffman2 cluster which serves a wide spectrum of user applications and is almost always heavily loaded. We will first review the model and policy of Hoffman2’s job scheduling, followed by fundamentals of using its job scheduler, Univa Grid Engine. A number of common use cases will be discussed in details, including: (1) Single-CPU jobs, (2) Multi-CPU, same-node jobs, (3) Multiple-node (MPI-style) jobs, (4) Job arrays and (5) High-priority jobs.

 

If you have questions regarding the workshop, please contact Shao-Ching Huang.


Thursday, October 10, 2019 - 9:00am to 12:00pm
at IDRE Visualization Portal, Math Sciences 5628

R is a programming environment that runs on Windows, Macintosh and UNIX platforms. This class is designed for people who are just starting to use R. The students in the class will have a hands-on experience using R for doing statistics, graphics, and data management. The class notes are the scripts for the class. The R class notes do not contain any of the computer output. The class notes are not meant to be an R textbook or a reference manual. However, it is possible for individuals to use the class notes to help them learn R even if they don’t enroll in the class. 

Students should bring their own laptop computers with R 3.6.1 (https://cran.r-project.org/ ) installed.  Installation of R-Studio (https://www.rstudio.com/products/rstudio/download/ ) is also strongly recommended. 


Tuesday, October 15, 2019 - 10:00am to 11:00am
at IDRE Portal

Learning PowerShell scripting is essential if you want to create virtual images or Docker containers on a Windows environment. In this demo you will be introduced to PowerShell scripting so that you can execute command line instructions similar to a bash environment in Linux.

Learn more about PowerShell.

If you have questions regarding the workshop, please contact Prakashan Korambath.


Tuesday, October 15, 2019 - 1:00pm to 3:00pm
at IDRE Portal

Git is a software tool that helps users manage changes to their software over time. Git will allow you to maintain a complete change history of every file, create branches for concurrent streams of changes, trace changes with annotations, and collaborate and share work with others. This interactive introduction will demonstrate how to use Git to track changes, to explore history, and to use web-based Git repositories to share work with others and collaborate.

If you have questions regarding the workshop, please contact Ben Winjum.


Thursday, October 17, 2019 - 9:00am to 12:00pm
at IDRE Visualization Portal, Math Sciences 5628

SAS is a powerful statistical package that runs on many platforms, including Windows and Unix. This class is designed for people who are just getting started using SAS. The students in the class will have a hands-on experience using SAS for statistics, graphics, and data management. The SAS class notes do not contain any of the computer output. The class notes are not meant to be a SAS textbook or a reference manual. However, it is possible for individuals to use the class notes to help in learning SAS even if they don’t enroll in the classes.

Students should bring their own laptop computers with SAS installed.  SAS can be purchased from the computer store in the book store in Ackerman, or students can download SAS University Edition (https://www.sas.com/en_us/software/university-edition.html ), which is free.


Tuesday, October 22, 2019 - 1:00pm to 4:00pm
at CLICC Classroom A (third floor of Powell Library)

Stata is a powerful and yet easy-to-use statistical package that runs on Windows, Macintosh and Unix platforms.  This class is designed for people who are just getting started using Stata.  The students in the class will have a hands-on experience using Stata for statistics, graphics and data management.  The class notes are the scripts for the class available to the students in the class and to others on the Internet.  The Stata class notes do not contain any of the output.  The class notes are not meant to be a Stata textbook or a reference manual.  However, it is possible for individuals to use the class notes to help in learning Stata even if they don’t enroll in the class.


Wednesday, October 23, 2019 - 9:00am to 12:00pm
at IDRE Portal

It is said that more than 80% of all data has a spatial component to it. As more and more research is leaning towards spatial analysis, this course offers an introduction to Geographic Information Systems (GIS) and spatial thinking, as a means to spatialize and analyze your data. As a hands-on course, you will learn how to download data, manipulate and join data to existing geographic boundaries, and create stunning cartographic representations. There are no pre-requisite requirements to take this workshop.

 

If you have questions regarding the workshop, please contact the instructor Yoh Kawano.


Thursday, October 24, 2019 - 9:00am to 12:00pm

SPSS is a very easy-to-use statistical package that runs on Windows, Macintosh and UNIX platforms. This class is designed for people who are just starting to use SPSS. The students in the class will have a hands-on experience using SPSS for doing statistics, graphics, and data management. The class notes are the scripts for the class. The SPSS class notes do not contain any of the computer output. The class notes are not meant to be an SPSS textbook or a reference manual. However, it is possible for individuals to use the class notes to help them learn SPSS even if they don’t enroll in the class.  These notes were developed using SPSS version 22, but most of the material should work with earlier or later versions of SPSS.


Thursday, October 24, 2019 - 11:00am to 12:00pm
at IDRE Portal

In Fall 2019, IDRE RTG will offer a series of classes on machine learning to the campus. The objective of the series is to present overviews to the exciting machine learning techniques and to provide a practical guide for general audience to step into the field. This series is primarily appropriate for the beginners who want to learn the techniques and apply to their future research activities. Researchers with machine learning experiences are expected to get benefits from related discussions as well.

In the first session in the series, we will present the following topics:

1. Syllabus and expectations for the whole class series
2. General introduction on machine learning
3. Introduction to Google Colaboratory and Kaggle Challenges

No specific prerequisite is required for the first session.

 

If you have any questions regarding the workshop, please contact Qiyang Hu.


Wednesday, October 30, 2019 - 1:00pm to 3:00pm
at IDRE Portal

The Jupyter Notebook is a computing tool that allows users to edit and run Python, R, Julia (and many other programming languages) inside a web browser. Furthermore, it is a powerful tool that allows users to combine live code, text, and visualizations in an interactive, shareable, reproducible document. It has been growing in popularity in many scientific and research disciplines as a data exploration and analysis tool that encourages collaboration and reproducible science. This class will provide an interactive demonstration showing what the Jupyter Notebook is, how to use it, and how it is being used in many different fields.

 

If you have questions regarding the workshop, please contact Ben Winjim.


Thursday, October 31, 2019 - 11:00am to 1:00pm
at IDRE Portal

In Fall 2019, IDRE RTG will offer a series of classes on machine learning to the campus. The objective of the series is to present overviews to the exciting machine learning techniques and to provide a practical guide for general audience to step into the field. This series is primarily appropriate for the beginners who want to learn the techniques and apply to their future research activities. Researchers with machine learning experiences are expected to get benefits from related discussions as well.

As the second session in the series, we will look into the Titanic Kaggle Challenge as a case study for classification problem in machine learning. Specifically we will focus on the following topics:

1. Data preparation and exploration for Titantic Kaggle Challenge
2. Introduction to the modeling of regression and classification problems.
3. Techniques on modeling classification problem using Scikit-learn library.
4. Prediction and submission to the Titanic challenge.

No specific prerequisite is required to understand most parts of the talks. The second session assumes the knowledge of topics covered in the first session. Working experience of Python, Jupyter Notebooks and linear algebra will be helpful.

 

If you have any questions regarding the workshop, please contact Qiyang Hu.


Thursday, November 7, 2019 - 11:00am to 12:00pm
at IDRE Portal

In Fall 2019, IDRE RTG will offer a series of classes on machine learning to the campus. The objective of the series is to present overviews to the exciting machine learning techniques and to provide a practical guide for general audience to step into the field. This series is primarily appropriate for the beginners who want to learn the techniques and apply to their future research activities. Researchers with machine learning experiences are expected to get benefits from related discussions as well.

In the third session in the series, we will focus on deep learning and use Dogs-vs-Cats Kaggle Challenge as the case study. The topics will include:

1. Introduction to deep learning and neural network.
2. Introduction to convolutional neural network.
2. Applying CNNs using Tensorflow to studying the Dogs-vs-Cats Kaggle Challenge.

No specific prerequisite is required to understand most parts of the talks. The current session assumes the knowledge of topics covered in the first and second session. Working experience of Python, Jupyter Notebooks and linear algebra will be helpful.

 

If you have any questions regarding the workshop, please contact Qiyang Hu.


Thursday, November 7, 2019 - 5:30pm to 9:00pm
at Carnesale Commons; 350 De Neve Dr, Los Angeles, CA 90095

Open to IS Associates members and UCLA staff, faculty and students only. 

About IS Associates: UCLA IS Associates leads the SoCal technology community with exceptional networking, quality professional education and informed insights into innovative and disruptive technologies. ISA’s programs are delivered through close collaboration with world-renowned UCLA faculty, Silicon Beach entrepreneurs and tech leaders from member organizations.

For more information about IS Associates, go to isassociates.ucla.edu.

To sign up visit the event page.


Thursday, November 14, 2019 - 11:00am to 1:00pm
at IDRE Portal

In Fall 2019, IDRE RTG will offer a series of classes on machine learning to the campus. The objective of the series is to present overviews to the exciting machine learning techniques and to provide a practical guide for general audience to step into the field. This series is primarily appropriate for the beginners who want to learn the techniques and apply to their future research activities. Researchers with machine learning experiences are expected to get benefits from related discussions as well.

In the third session in the series, we will focus on deep learning and use Dogs-vs-Cats Kaggle Challenge as the case study. The topics will include:

1. Introduction to Data Augmentation techniques.
2. Using Data Augmentation to improve the solution for the Dogs-vs-Cats Kaggle Challenge.
3. Introducing transfer learning techniques to the Dogs-vs-Cats Kaggle Challenge.

No specific prerequisite is required to understand most parts of the talks. The current session assumes the knowledge of topics covered in the third session. Working experience of Python, Jupyter Notebooks and linear algebra will be helpful.

 

If you have any further questions regarding the workshop, please contact Qiyang Hu.