[{"id":220,"title":"Start Coding without Hesitation: Programming Languages Showdown","url":"https://staging.dresa.org.au/materials/start-coding-without-hesitation-programming-languages-showdown.json","description":"Programming is becoming more and more popular, with many researchers using programming to perform data cleaning, data manipulation, data analytics, as well as creating publication quality plots. Programming can be really beneficial for automating processes and workflows. In this webinar, we are exploring four of the most popular programming languages that are widely used in academia, namely Python, R, MATLAB, and Julia.\n\nWhy use Programming  \n An overview of Python, R, MATLAB, and Julia  \n Code comparison of the four programming languages  \n Popularity and job opportunities  \n Intersect’s comparison  \n General guidelines on how to choose the best programming language for your research\n\nThe webinar has no prerequisites.","doi":"10.5281/zenodo.6423516","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":231,"title":"Learn to Program: Julia","url":"https://staging.dresa.org.au/materials/learn-to-program-julia.json","description":"Julia is a high-level, high-performance dynamic programming language with more than 4,000 external libraries available. Julia allows you to range from tight low-level loops and conditionals, up to a high-level programming style, with its performance approaching and often matching the performance of the fastest programming languages!  \n  \n This workshop expects that you are coming to Julia with some experience in the basic concepts of programming in another language. It is designed to help you migrate the basic concepts of programming that you already know to the Julia context.  \n  \n Join us for this live coding workshop where we write programs that produce results, using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly.\n\nIntroduction to the JupyterLab interface for programming  \n Basic syntax and data types in Julia  \n How to load external data into Julia  \n Creating functions (FUNCTIONS)  \n Repeating actions and analysing multiple data sets (LOOPS)  \n Making choices (IF STATEMENTS – CONDITIONALS)  \n Ways to visualise data using the Plots library in Julia\n\nSome experience with the basic concepts of programming in another language needed to attend this course. It is an intensive course that is designed to help you migrate the basic concepts of programming that you already know to the Julia context in half a day instead of a full day. If you don’t have any prior experience in programming, please consider attending one of the \\Learn to Program: Python\\, \\Learn to Program: R\\ or \\Learn to Program: MATLAB\\ prior to this course.   \n  \n We also strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found \\here\\.","doi":"10.5281/zenodo.6423662","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":232,"title":"Beyond the Basics: Julia","url":"https://staging.dresa.org.au/materials/beyond-the-basics-julia.json","description":"Julia is a high-level, high-performance dynamic programming language with more than 4,000 external libraries available. Julia allows you to range from tight low-level loops and conditionals, up to a high-level programming style, with its performance approaching and often matching the performance of the fastest programming languages!  \n  \n This workshop explores the more advanced features of functions in Julia, introduces widely used tools within Julia, as well as demonstrates the speed of Julia by benchmarking functions and different styles of scripting within Julia.  \n  \n Join us for this live coding workshop where we write programs that produce results, using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly.\n\nUnderstand the role of Types within Julia  \n Create functions with complex arguments  \n Demonstrate programming patterns of list comprehension, pipes, and anonymous functions.  \n Benchmark Julia code and understand how to make it fast\n\nIf you already have experience with programming, please check the topics covered in the \\Learn to Program: Julia\\ to ensure that you are familiar with the knowledge needed for this course.","doi":"10.5281/zenodo.6423664","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]}]