Numerical Simulation Methods (in Russian)
Course Overview
This course provides a fast-paced introduction to scientific computing using Python. It covers the essential tools required for modern research in thermophysics, ranging from basic numerical analysis with NumPy and SciPy to introductory Machine Learning techniques.
The goal is to provide students with a practical toolkit for data analysis and numerical simulation, enabling them to automate calculations and uncover insights in their future research projects.
Course Resources
Access the companion computational code and notebooks.
Access the companion computational code and notebooks.
Syllabus
| Date / Week | Topic | Description | Materials |
|---|---|---|---|
| December 10 Week 1 | Python Scientific Computing | Introduction to Python ecosystem for science (NumPy, SciPy, Matplotlib). | Lecture 1 (Slides) |
| December 17 Week 2 | Fundamentals of Machine Learning | Introduction to basic ML concepts, algorithms, and training processes. | Lecture 2 (Slides) |
| December 19 Week 3 | Practical Applications | Application of numerical methods and ML in thermophysics problems. | Lecture 3 (Slides) |