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Difficulty level: Beginner  or Not specified 

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Keywords: AI  or Machine learning  or Command line 

WEBINAR: Getting started with deep learning

This record includes training materials associated with the Australian BioCommons webinar  ‘Getting started with deep learning’. This webinar took place on 21 July 2021.

Are you wondering what deep learning is and how it might be useful in your research? This high level overview introduces deep...

Keywords: Deep learning, Neural networks, Machine learning

WEBINAR: Getting started with deep learning https://dresa.org.au/materials/webinar-getting-started-with-deep-learning-986aa2d2-594a-4a7f-836c-44d6e9d5d017 This record includes training materials associated with the Australian BioCommons webinar  ‘Getting started with deep learning’. This webinar took place on 21 July 2021. Are you wondering what deep learning is and how it might be useful in your research? This high level overview introduces deep learning ‘in a nutshell’ and provides tips on which concepts and skills you will need to know to build a deep learning application. The presentation also provides pointers to various resources you can use to get started in deep learning. The webinar is followed by a short Q&A session. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. Getting Started with Deep Learning - Slides (PDF): Slides used in the presentation   Materials shared elsewhere: A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/I1TmpnZUuiQ Melissa Burke (melissa@biocommons.org.au) Deep learning, Neural networks, Machine learning
WEBINAR: Getting started with command line bioinformatics

This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with command line bioinformatics’. This webinar took place on 22 June 2021. 

Bioinformatics skills are in demand like never before and biologists are stepping up to the challenge of...

Keywords: Bioinformatics, Command line, Workflows, Bash, Computational biology

WEBINAR: Getting started with command line bioinformatics https://dresa.org.au/materials/webinar-getting-started-with-command-line-bioinformatics-248027d1-0773-485a-b511-831e2fd4cc64 This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with command line bioinformatics’. This webinar took place on 22 June 2021.  Bioinformatics skills are in demand like never before and biologists are stepping up to the challenge of learning to analyse large and ever growing datasets. Learning how to use the command line can open up many options for data analysis but getting started can be a little daunting for those without a background in computer science. Parice Brandies and Carolyn Hogg have recently put together ten simple rules for getting started with command-line bioinformatics to help biologists begin their computational journeys. In this webinar Parice walks you through their hints and tips for getting started with the command line. She covers topics like learning tech speak, evaluating your data and workflows, assessing computational requirements, computing options, the basics of software installation, curating and testing scripts, a bit of bash and keeping good records. The webinar will be followed by a short Q&A session. The slides were created by Parice Brandies and are based on the publication ‘Ten simple rules for getting started with command-line bioinformatics’ (https://doi.org/10.1371/journal.pcbi.1008645). The slides are shared under a Creative Commons Attribution 4.0 International unless otherwise specified and were current at the time of the webinar. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. Getting started with command line bioinformatics - slides (PDF): Slides presented during the webinar Materials shared elsewhere: A recording of the webinar is available on the Australian BioCommons YouTube Channel https://youtu.be/p7pA4OLB2X4 Melissa Burke (melissa@biocommons.org.au) Hogg, Carolyn (type: Supervisor) Bioinformatics, Command line, Workflows, Bash, Computational biology
WEBINAR: AlphaFold: what's in it for me?

This record includes training materials associated with the Australian BioCommons webinar ‘WEBINAR: AlphaFold: what’s in it for me?’. This webinar took place on 18 April 2023.

Event description 

AlphaFold has taken the scientific world by storm with the ability to accurately predict the...

Keywords: Bioinformatics, Machine Learning, Structural Biology, Proteins, Drug discovery, AlphaFold, AI, Artificial Intelligence, Deep learning

WEBINAR: AlphaFold: what's in it for me? https://dresa.org.au/materials/webinar-alphafold-what-s-in-it-for-me-4d1ea222-4240-4b68-b9ae-7769ac664ee0 This record includes training materials associated with the Australian BioCommons webinar ‘WEBINAR: AlphaFold: what’s in it for me?’. This webinar took place on 18 April 2023. Event description  AlphaFold has taken the scientific world by storm with the ability to accurately predict the structure of any protein in minutes using artificial intelligence (AI). From drug discovery to enzymes that degrade plastics, this promises to speed up and fundamentally change the way that protein structures are used in biological research.  Beyond the hype, what does this mean for structural biology as a field (and as a career)? Dr Craig Morton, Drug Discovery Lead at the CSIRO, is an early adopter of AlphaFold and has decades of expertise in protein structure / function, protein modelling, protein – ligand interactions and computational small molecule drug discovery, with particular interest in anti-infective agents for the treatment of bacterial and viral diseases. Craig joins this webinar to share his perspective on the implications of AlphaFold for science and structural biology. He will give an overview of how AlphaFold works, ways to access AlphaFold, and some examples of how it can be used for protein structure/function analysis. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/4ytn2_AiH8s Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Machine Learning, Structural Biology, Proteins, Drug discovery, AlphaFold, AI, Artificial Intelligence, Deep learning
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
Monash University - University of Queensland training partnership in Data science and AI

We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning,...

Keywords: data skills, training partnerships, data science, AI, training material

Monash University - University of Queensland training partnership in Data science and AI https://dresa.org.au/materials/monash-university-university-of-queensland-training-partnership-in-data-science-and-ai-8082bf73-d20f-4214-ad8c-95123e25a36c We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning, visualisation, and computing tools, we have established a series of over 20 workshops over the year where either Monash or QCIF hosts the event for some 20-40 of their researchers and students, while some 5 places are offered to participants from the other institution. In the longer term we aim to share material developed at one institution and have trainers present it at the other. In this talk we will describe the many benefits we have found to this approach including access to a wider range of expertise in several rapidly developing fields, upskilling of trainers, faster identification of emerging training needs, and peer learning for trainers. contact@ardc.edu.au data skills, training partnerships, data science, AI, training material
Introduction to Unix

A hands-on workshop covering the basics of the Unix command line interface.

Knowledge of the Unix operating system is fundamental to the use of many popular bioinformatics command-line tools. Whether you choose to run your analyses locally or on a high-performance computing system, knowing...

Keywords: Unix, Command line, Command-line, CLI

Resource type: tutorial

Introduction to Unix https://dresa.org.au/materials/introduction-to-unix A hands-on workshop covering the basics of the Unix command line interface. Knowledge of the Unix operating system is fundamental to the use of many popular bioinformatics command-line tools. Whether you choose to run your analyses locally or on a high-performance computing system, knowing your way around a command-line interface is highly valuable. This workshop will introduce you to Unix concepts by way of a series of hands-on exercises. This workshop is designed for participants with little or no command-line knowledge. Tools: Standard Unix commands, FileZilla Topic overview: Section 1: Getting started Section 2: Exploring your current directory Section 3: Making and changing directories Section 4: Viewing and manipulating files Section 5: Removing files and directories Section 6: Searching files Section 7: Putting it all together Section 8: Transferring files Tutorial instructions available here: https://www.melbournebioinformatics.org.au/tutorials/tutorials/unix/unix/ For queries relating to this workshop, contact Melbourne Bioinformatics (bioinformatics-training@unimelb.edu.au). Find out when we are next running this training as an in-person workshop, by visiting the Melbourne Bioinformaitcs Eventbrite page: https://www.eventbrite.com.au/o/melbourne-bioinformatics-13058846490 For queries relating to this workshop, contact Melbourne Bioinformatics (bioinformatics-training@unimelb.edu.au). Unix, Command line, Command-line, CLI ugrad masters mbr phd ecr researcher support professional
Deep Learning for Natural Language Processing

This workshop is designed to be instructor led and consists of two parts.
Part 1 consists of a lecture-demo about text processing and a hands-on session for attendees to learn how to clean a dataset.
Part 2 consists of a lecture introducing Recurrent Neural Networks and a hands-on session for...

Keywords: Deep learning, NLP, Machine learning

Resource type: presentation, tutorial

Deep Learning for Natural Language Processing https://dresa.org.au/materials/deep-learning-for-natural-language-processing This workshop is designed to be instructor led and consists of two parts. Part 1 consists of a lecture-demo about text processing and a hands-on session for attendees to learn how to clean a dataset. Part 2 consists of a lecture introducing Recurrent Neural Networks and a hands-on session for attendees to train their own RNN. The Powerpoints contain the lecture slides, while the Jupyter notebooks (.ipynb) contain the hands-on coding exercises. This workshop introduces natural language as data for deep learning. We discuss various techniques and software packages (e.g. python strings, RegEx, NLTK, Word2Vec) that help us convert, clean, and formalise text data “in the wild” for use in a deep learning model. We then explore the training and testing of a Recurrent Neural Network on the data to complete a real world task. We will be using TensorFlow v2 for this purpose. datascienceplatform@monash.edu Deep learning, NLP, Machine learning
Introduction to Deep Learning and TensorFlow

This workshop is intended to run as an instructor guided live event and consists of two parts. Each part consists of a lecture and a hands-on coding exercise.
Part 1 - Introduction to Deep Learning and TensorFlow
Part 2 - Introduction to Convolutional Neural Networks
The Powerpoints contain...

Keywords: Deep learning, convolutional neural network, tensorflow, Machine learning

Resource type: presentation, tutorial

Introduction to Deep Learning and TensorFlow https://dresa.org.au/materials/introduction-to-deep-learning-and-tensorflow This workshop is intended to run as an instructor guided live event and consists of two parts. Each part consists of a lecture and a hands-on coding exercise. Part 1 - Introduction to Deep Learning and TensorFlow Part 2 - Introduction to Convolutional Neural Networks The Powerpoints contain the lecture slides, while the Jupyter notebooks (.ipynb) contain the hands-on coding exercises. This workshop is an introduction to how deep learning works and how you could create a neural network using TensorFlow v2. We start by learning the basics of deep learning including what a neural network is, how information passes through the network, and how the network learns from data through the automated process of gradient descent. Workshop attendees would build, train and evaluate a neural network using a cloud GPU (Google Colab). In part 2, we look at image data and how we could train a convolution neural network to classify images. Workshop attendees will extend their knowledge from the first part to design, train and evaluate this convolutional neural network. datascienceplatform@monash.edu Deep learning, convolutional neural network, tensorflow, Machine learning