文章目录课程Parallel Computing(Stanford CS149,Fall 2023)Scientific Python(Stanford CME 193)Computational Methods of Scientific Programming(MIT Fall 2024)Python Programming And Numerical Methods: A Guide For Engineers And Scientists(伯克利免费教程)课程Parallel Computing(Stanford CS149,Fall 2023)主页From smart phones, to multi-core CPUs and GPUs, to the world’s largest supercomputers and web sites, parallel processing is ubiquitous in modern computing. The goal of this course is to provide a deep understanding of the fundamental principles and engineering trade-offs involved in designing modern parallel computing systems as well as to teach parallel programming techniques necessary to effectively utilize these machines. Because writing good parallel programs requires an understanding of key machine performance characteristics, this course will cover both parallel hardware and software design.Scientific Python(Stanford CME 193)主页This course is recommended for students who are familiar with programming at least at the level of CS106A and want to translate their programming knowledge to Python with the goal of becoming proficient in the scientific computing and data science stack. Lectures will be interactive with a focus on real world applications of scientific computing. Technologies covered include Numpy, SciPy, Pandas, Scikit-learn, and others. Topics will be chosen from Linear Algebra, Optimization, Machine Learning, and Data Science. Prior knowledge of programming will be assumed, and some familiarity with Python is helpful, but not mandatory.Computational Methods of Scientific Programming(MIT Fall 2024)主页This introductory course exposes students to modern programming methods and techniques used in practice by physical scientists today. Emphasis is placed on code design, algorithm development/verification, and comparative advantages/disadvantages of different languages (including Python, Julia, and C/C) and tools (including Jupyter, machine learning from data or models, and cloud and high-performance computing workflows). Students are introduced to and work with common programming tools, types of problems, and techniques for solving a variety of>Python Programming And Numerical Methods: A Guide For Engineers And Scientists(伯克利免费教程)主页This notebook contains an excerpt from the Python Programming and Numerical Methods - A Guide for Engineers and Scientists, the content is also available at Berkeley Python Numerical Methods.