Welcome to join our studio for learning! Through in-depth research projects, you will have the opportunity to acquire knowledge spanning multiple disciplines such as mathematics, physics, computer science, chemistry, chemical engineering, materials science, energy, and environmental studies. In this learning environment, you will gain insights into interdisciplinary knowledge and skills through practical projects and case studies.
Mathematics will help you establish a fundamental framework for analysis and problem-solving, while physics will provide you with a profound understanding of the laws governing the natural world. Computer skills will enable you to handle large datasets and conduct simulation experiments. Additionally, disciplines like chemistry, chemical engineering, and materials science will equip you with laboratory skills and knowledge in material science. Exploring the fields of energy and environment will deepen your understanding of sustainable development and the importance of environmental conservation.
This comprehensive coverage of various disciplines will provide you with a holistic and in-depth academic experience, laying a solid foundation for your future career development. The knowledge covered by the project includes the following:
Exploring the Nanoworld
By introducing the wonders of the nanoworld, this aims to inspire high school students’ interest in nanoscience while guiding them to understand the applications of molecular simulation in nanoscience research.
Computer Hardware Fundamentals and Buying/Installation Guide
This helps students understand the basic components of computer hardware, considerations for hardware selection, and develops their basic ability to purchase and install hardware within a limited budget.
Building Scientific Computing Servers
Covering the installation and basic configuration of the Linux system, installation and configuration of the Fortran compiler, installation and configuration of computational task scheduling software, and installation and configuration of molecular simulation software.
Fundamentals of Molecular Simulation
This helps students understand the basic principles, methods, and applications of molecular simulation, cultivating their interest and basic skills in molecular-scale science.
Numerical Algorithms
Providing high school students with foundational knowledge of numerical algorithms, this aims to develop their ability to apply numerical methods to solve practical problems. Through theoretical explanations and practical programming exercises, students gain an understanding of the principles and applications of numerical algorithms.
Introduction to Academic Journals and Literature Retrieval
This helps students understand the importance of academic papers, characteristics of academic journals, and cultivates their basic ability to use academic databases for literature retrieval and reading academic papers.
Fortran Programming Basics
This helps students understand the basic syntax, program structure, data types, and control structures of the Fortran programming language, fostering their ability to write simple scientific computing programs.
Linux Operating System Basics
This helps students understand the basic concepts, installation process, basic commands, and common applications of the Linux operating system, cultivating their interest and skills in using open-source systems.
Python Programming and Scientific Plotting
This helps students understand the basic syntax, data types, and control structures of the Python programming language, cultivating their ability to use Python for scientific computing and plotting, especially using Matplotlib for scientific plotting.
Shell Programming Basics
This helps students understand the basic concepts of Shell programming, basic commands, flow control, and script writing, cultivating their ability to write simple Shell scripts to solve practical problems.
Machine Learning
Providing foundational knowledge in machine learning, this aims to develop students’ understanding and application of machine learning algorithms. Through theoretical explanations, practical cases, and simple programming exercises, students build an initial understanding of machine learning.