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SWC July 2018 workshop

Start date: July 16, 2018

End date: July 18, 2018

Time: 9am-5pm

Location: B216:201

SWC July 2018 workshop

Course Content:

  • Introduction to the Unix Shell
  • Introduction to version control (using Git)
  • Data analysis and visualisation in Python
  • Data analysis and visualisation in R

Who: The course is aimed at postgraduate students and researchers who want to learn more about automation and reproducibility of their research. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed here). They are also required to abide by Software Carpentry's Code of Conduct.

Registration via Eventbrite

 

April SWC workshop – R

Start date: April 23, 2018

End date: April 24, 2018

Time: 9am-5pm

Location: B216:201

April SWC workshop – R

Software Carpentry's (SWC) mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems. For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".

Who: The course is aimed at graduate students and researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Content: We will be teaching introductions to the Unix shell, version control with Git as well as programming with R. For the syllabus and schedule see the workshop webpage.

When: Monday 23 & Tuesday 24 April 2018, 9am - 5pm

Where: B216:201, Curtin University, Bentley Campus
RVSP: You can register via Eventbrite, there is a registration fee which will cover morning and afternoon tea.
Contact: Please email rebecca.lange@curtin.edu.au for more information.

March SWC workshop – Python

Start date: March 19, 2018

End date: March 20, 2018

Time: 9am-5pm

Location: 216:202 (tentative)

March SWC workshop – Python

Software Carpentry's (SWC) mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems. For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".

Who: The course is aimed at graduate students and researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Content: We will be teaching introductions to the Unix shell, version control with Git as well as programming with Python. For the syllabus and schedule see the workshop webpage.

When: Monday 19 & Tuesday 20 March 2018, 9am - 5pm

Where: B216:202 (room tentative), Curtin University, Bentley Campus
RVSP: You can register via Eventbrite, there is a registration fee which will cover morning and afternoon tea.
Contact: Please email rebecca.lange@curtin.edu.au for more information.

ADACS – Introduction to computing and data science for astronomers

Start date: November 13, 2017

End date: November 15, 2017

Time: 9am-5pm

Location: B407:307, Curtin University

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ADACS – Introduction to computing and data science for astronomers

ADACS - Introduction to computing and data science for astronomers

In the era of big telescopes and big data, data analysis practices need to scale to the volume of data processing and analysis needed for researchers to compete in a world-class arena.

This 3-day workshop is aimed at postgraduate students and ECRs who might not have had formal computational training and would like to get up to speed. Practical examples in the workshop are taken from observational astronomy, however, participation is open to all Australian-based astronomers.

Contact: Please email rebecca.lange@curtin.edu.au or visit the ADACS event page for more information.

This workshop is offered by the Astronomy Data and Computing Services (ADACS) initiative. ADACS is funded under the Astronomy National Collaborative Research Infrastructure Strategy (NCRIS) Program via Astronomy Australia Ltd (AAL).

SWC workshop November 2017

Start date: November 7, 2017

End date: November 9, 2017

Time: 9am-5pm

Location: B204:119

SWC workshop November 2017

Software Carpentry's mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems. For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".

Who: The course is aimed at graduate students and researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Content: We will be teaching introductions to the Unix shell, version control with Git as well as programming with Python and R. For the syllabus and schedule see the workshop webpage.

When: Tuesday 7 to Thursday 9 November 2017, 9am to 5pm

Where: Building 204 : Room 119
RVSP: You can register via Eventbrite, there is a registration fee which will cover morning and afternoon tea.
Contact: Please email rebecca.lange@curtin.edu.au for more information.

Software Carpentry Workshop August 2017

Start date: August 28, 2017

End date: August 30, 2017

Time: 09:00 - 17:00

Location: B300:219

Software Carpentry Workshop August 2017

Software Carpentry's mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems. For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".

Who: The course is aimed at graduate students and researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Content: We will be teaching introductions to the Unix shell, version control with Git as well as programming with Python and R. For the syllabus and schedule see

When: Monday 28 to Wednesday 30 August 2017, 9am to 5pm

Where: Building 300 : Room 219
RVSP: You can register via Eventbrite, there is a registration fee which will cover morning and afternoon tea.
Contact: Please email rebecca.lange@curtin.edu.au for more information.

Introduction to Machine Learning

Date: September 14, 2017

Time: 09:00 - 17:00

Location: B100:Council Chamber (Level 3)

Introduction to Machine Learning
This workshop will introduce machine learning concepts through a mixture of lecture and hands-on coding. The aim is to teach a basic understanding of designing machine learning workflows for supervised and unsupervised learning approaches, classification and regression methods and model tuning. The workshop will be taught by Dr. Kevin Chai and Dr. Rebecca Lange from the Curtin Institute for Computation.
Who: The course is aimed at postgraduate students, researchers and professionals looking at taking their analytics skills to the next level.
Prerequisites: A working knowledge of Python and Jupyter notebooks is essential for this workshop. i.e. knowledge of basic data structures, operations and how to write scripts. The notebooks used throughout the workshop have been developed to be compatible with Python 2.7x and 3.x but may require some Python packages to be updated to the most recent version (e.g. scikit-learn). No prior knowledge of machine learning is expected.
Content: We will be giving a general overview on machine learning followed by worked examples of how to build machine learning pipelines.

Topics covered:

  • Data preparation
  • Exploratory data analysis
  • Classification
    • Cross validation
    • Learning curves
    • Model tuning
    • Reporting
  • Regression
  • Clustering
  • Dimensionality reduction
RVSP: You can register via Eventbrite, there is a small registration fee which will cover morning and afternoon tea.
Contact: Please email rebecca.lange@curtin.edu.au for more information.
If you have any special requirements to enable you to participate at this event please advise when you RSVP or email the Curtin Institute for Computation. We will contact you to provide assistance.
For information about disability services at Curtin, please visit disability.curtin.edu.au.

Introduction to R

Start date: July 24, 2017

End date: July 25, 2017

Time: 9am-5pm

Location: B216:202

Introduction to R

The goal of this introductory workshop is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis.
A variety of third party packages are used throughout this workshop. These are not necessarily the best, nor are they comprehensive, but they are packages we find useful, and have been chosen primarily for their usability.
This workshop is based on the Software Carpentry lesson "R for reproducible scientific analysis" and covers:
  1. Introduction to R and RStudio
  2. Project Management With RStudio
  3. Data Structures
  4. Exploring and sub-setting your data
  5. Writing functions
  6. Introduction to the tidyverse (dplyr, tidyr, ggplot2)
    1. Dataframe manipulation with dplyr and tidyr
    2. Creating Publication-Quality Graphics with ggplot2
  7. Producing reports

This lesson assumes you have R and RStudio installed on your computer.

R can be downloaded here.

RStudio is an environment for developing using R. It can be downloaded here. You will need the Desktop version for your computer.

Software Carpentry workshop (R)

Start date: November 7, 2016

End date: November 10, 2016

Time: 9:00 - 13:00

Location: Building 216 - Room 201

Software Carpentry workshop (R)

Who: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: Room 216:201, Curtin Bentley Campus. Get directions with OpenStreetMap or Google Maps.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (see here). They are also required to abide by Software Carpentry's Code of Conduct.

Contact: Please mail andrea.bedini@curtin.edu.au for more information.

Content:

  • The Unix Shell
  • R for Reproducible Scientific Analysis - part 1
  • R for Reproducible Scientific Analysis - part 2
  • Version Control with Git

Registration Fee: $50 (includes morning tea and refreshments)

For more information and to register: https://curtinic.github.io/SWC-2016-11-07-Curtin/