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Keywords: eresearch skills 

and

Authors: Tang, Titus  or Wang, Jingbo 


Successful data training stories from NCI

NCI Australia manages a multi-petabyte sized data repository, collocated with its HPC systems and data services, which allows high performance access to many scientific research datasets across many earth science domains.
An important aspect is to provide training materials that proactively...

Keywords: skills, training, eresearch skills, HPC training, domain-specific training, reproducible workflows, training material

Successful data training stories from NCI https://dresa.org.au/materials/successful-data-training-stories-from-nci-33f110e3-0c06-492e-9cc5-fa0f886ca1b8 NCI Australia manages a multi-petabyte sized data repository, collocated with its HPC systems and data services, which allows high performance access to many scientific research datasets across many earth science domains. An important aspect is to provide training materials that proactively engages with the research community to improve their understanding of the data available, and to share knowledge and best practices in the use of tools and other software. We have developed multiple levels of training modules (introductory, intermediate and advanced) to cater for users with different levels of experience and interest. We have also tailored courses for each scientific domain, so that the use-cases and software will be most relevant to their interests and needs. For our training, we combine brief lectures followed by hands-on training examples on how to use datasets, using working examples of well-known tools and software that people can use as a template and modify to fit their needs. For example, we take representative use-cases from some scientific activities, from our collaborations and from user support issues, and convert to Jupyter notebook examples so that people can repeat the workfIow and reproduce the results. We also use the training as an opportunity to raise awareness of growing issues in resource management. Some examples include a familiarity of the FAIR data principles, licensing, citation, data management and trusted digital repositories. This approach to both our online training materials and workshops has been well-received by PhD students, early careers, and cross disciplinary users. contact@ardc.edu.au skills, training, eresearch skills, HPC training, domain-specific training, reproducible workflows, training material
Accelerating skills development in Data science and AI at scale

At the Monash Data Science and AI  platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities...

Keywords: AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material

Accelerating skills development in Data science and AI at scale https://dresa.org.au/materials/accelerating-skills-development-in-data-science-and-ai-at-scale-2d8a65fa-f96e-44ad-a026-cfae3f38d128 At the Monash Data Science and AI  platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities within and outside Monash University. In this talk, we will discuss the principles and purpose of establishing collaborative models to accelerate skills development at scale. We will talk about our approach to identifying gaps in the existing skills and training available in data science, key areas of interest as identified by the research community and various sources of training available in the marketplace. We will provide insights into the collaborations we currently have and intend to develop in the future within the university and also nationally. The talk will also cover our approach as outlined below •        Combined survey of gaps in skills and trainings for Data science and AI •        Provide seats to partners •        Share associate instructors/helpers/volunteers •        Develop combined training materials •        Publish a repository of open source trainings •        Train the trainer activities •        Establish a network of volunteers to deliver trainings at their local regions Industry plays a significant role in making some invaluable training available to the research community either through self learning platforms like AWS Machine Learning University or Instructor led courses like NVIDIA Deep Learning Institute. We will discuss how we leverage our partnerships with Industry to bring these trainings to our research community. Finally, we will discuss how we map our training to the ARDC skills roadmap and how the ARDC platforms project “Environments to accelerate Machine Learning based Discovery” has enabled collaboration between Monash University and University of Queensland to develop and deliver training together. contact@ardc.edu.au AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material