Workshop Series: Computational Skills for Physical Science (CSPS) 2024

 

4, 25 May & 8 June 2024 - The Computational Skills for Physical Science (CSPS) Workshop Series is the brainchild of three senior lecturers from the School of Physics: Dr John Soo Yue Han, Dr Muhammad Rabie Omar, and Dr Sya’rawi Muhammad Husni Mohd Sharoni. Upon observing that many fresh physics undergraduate and postgraduate students seem ill equipped with the necessary computational skills for physics laboratory and research work, they took the initiative to conduct an annual workshop series of computational skills to bridge this gap. With strong backgrounds in programming and machine learning, the trio hoped to impart these valuable soft skills to the students so that they will be well equipped for the challenging physics job market and research arena.

 

 

This year, the pilot programme is a series of three workshops. The first, entitled “Basic Machine Learning: Regression & Classification with Orange” was conducted by Dr John on 4 May 2024 to introduce students to the world of machine learning. Using a data mining software called Orange, he gave students a sneak-peak on how regression and classification problems in astronomy can be solved using machine learning. Students got to learn via an interactive lecture, and a hands-on project which brings out the power of data-driven science.

 

 

The second workshop, entitled “MATLAB: Introduction to Physical Science Data Analysis” was conducted by Dr Sya’rawi on 25 May 2024 to provide basic programming training using MATLAB. Through a series of self-learning lectures and group projects, the students were introduced to the basic syntax of MATLAB and how to use it to solve physics problems. Dr Sya’rawi also showed the students how ChatGPT could essentially help them to enhance their learning experience!

 

 

The final workshop, entitled “Python Express” was conducted by Dr Rabie on 8 Jun 2024 to introduce the students to a more in-depth training on programming. Using various real life physics and mathematical problems, he illustrated how python could be easily used to analyse and process problems. Dr Rabie also made the students work in groups, using a student-based learning system to help grade and evaluate the students’ performance in solving coding problems.

 

 

Overall, the workshop was a success. A total of 35 undergraduate and postgraduate students signed up for the class, and the students gave generally positive reviews. When asked on what topics should be covered next, students requested for classes in C++ programming, LaTeX typesetting, deep learning and AI tools. It is evident that the trio will have more work to do in the future: hopefully this workshop series will eventually be opened to students from other schools, or even other universities!