439 件ヒット (0.023秒)：
線形代数学は多成分の量を扱う上で基本的であり、数学はもちろん、
理工系にとどまらない多くの分野の基礎となり、その発展を助けている。
この講義では、行列の演算、連立一次方程式、行列式の標準的な内容を扱い、
基礎的な計算力を身につけつつ線形代数学の初歩を学ぶ。
Linear algebra is an essential tool to handle multi-component quantities, and it helps developments not only of mathematics but also of natural sciences and social sciences.
This course covers the basics of linear algebra, such as operations of matrices, systems of linear equations, determinants of matrices.
Students will acquire relevant skills to perform certain computations.
形代数はベクトルと行列についての研究を中心とした数学の一分野で，社会科学や自然科学の様々な分野で広く応用され，多次元の問題を解くのに中心的な役割を果たしています．この授業では，数ベクトル・行列・連立一次方程式・固有値などの基本理論について学びます．また，授業を通して，しっかりとした思考力と問題解決能力を高めます．
Linear algebra is a branch of mathematics centered around the study and manipulation of vectors and matrices. It is crucial for solving multidimensional problems and has wide applications in various scientific fields. In this course, students will learn about fundamental theories, including (numerical) vectors, matrices, systems of linear equations, eigenvalues, and eigenvectors. Through this course, students will develop critical thinking and problem-solving skills.
線型代数学は多成分の量を扱う上で基本的であり，数学はもちろん，自然科学や社会科学，経済学の基礎である．本講義では，行列，連立1次方程式，行列式，固有値などの線型代数学の基礎を学ぶ．
Linear algebra is an essential tool to handle multi-component quantities, and is a foundation of natural sciences, social sciences and economics, as well as mathematics. This course covers fundamentals in linear algebra, such as matrices, systems of linear equations, determinants of matrices, and eigenvalues.
線形代数学は多成分の量を扱う上で基本的であり、数学はもちろん、
理工系にとどまらない多くの分野の基礎となり、その発展を助けている。
この講義では、行列の演算、連立一次方程式、行列式の標準的な内容を扱い、
基礎的な計算力を身につけつつ線形代数学の初歩を学ぶ。
Linear algebra is an essential tool to handle multi-component quantities, and it helps developments not only of mathematics but also of natural sciences and social sciences.
This course covers the basics of linear algebra, such as operations of matrices, systems of linear equations, determinants of matrices.
Students will acquire relevant skills to perform certain computations.
行列の固有値と固有ベクトル，対角化，三角化を学ぶ．また，内積が定義されているベクトル空間について基本概念を学ぶ．さらに，線形代数の応用例を学ぶ．
Eigenvalues and eigenvectors of matrices are introduced. Using these concepts, students will learn diagonalization and triangularization of matrices. Furthermore, vector spaces with inner product will be treated. Finally, applications of linear algebra to various specialized topics
will be mentioned.
線形代数学は多成分の量を扱う上で基本的であり、数学はもちろん、
理工系にとどまらない多くの分野の基礎となり、その発展を助けている。
この講義では、行列の演算、連立一次方程式、行列式の標準的な内容を扱い、
基礎的な計算力を身につけつつ線形代数学の初歩を学ぶ。
Linear algebra is an essential tool to handle multi-component quantities, and it helps developments not only of mathematics but also of natural sciences and social sciences. This course covers fundamentals in linear algebra, such as operations of matrices, systems of linear equations, determinants of matrices. Students will acquire relevant skills to perform certain computations.
クラスコード urqyyay
経済学、経営学で用いられる数学について講義を行う。特に、線形代数、2変数(または高次の)関数、積分についての講義を行う。
This course will cover the mathematics used in economics and management, with a focus on calculus and linear algebra.
We will cover linear algebra, and calculus in the second (or higher) dimensional space and integration.
行列の固有値と固有ベクトル，対角化，三角化を学ぶ．また，内積が定義されているベクトル空間について基本概念を学ぶ．さらに，線形代数の応用例を学ぶ．
Eigenvalues and eigenvectors of matrices are introduced. Using these concepts, students will learn diagonalization and triangularization of matrices. Furthermore, vector spaces with inner product will be treated. Finally, applications of linear algebra to various specialized topics
will be mentioned.
線形代数学は多成分の量を扱う上で基本的であり、数学はもちろん、
理工系にとどまらない多くの分野の基礎となり、その発展を助けている。
この講義では、行列の演算、連立一次方程式、行列式の標準的な内容を扱い、
基礎的な計算力を身につけつつ線形代数学の初歩を学ぶ。
Linear algebra is an essential tool to handle multi-component quantities, and it helps developments not only of mathematics but also of natural sciences and social sciences.
This course covers fundamentals in linear algebra, such as operations of matrices, systems of linear equations, determinants of matrices.
Students will acquire relevant skills to perform certain computations.
行列の固有値と固有ベクトル，対角化，三角化を学ぶ．また，内積が定義されているベクトル空間について基本概念を学ぶ．さらに，線形代数の応用例を学ぶ．
Eigenvalues and eigenvectors of matrices are introduced. Using these concepts, students will learn diagonalization and triangularization of matrices. Furthermore, vector spaces with inner product will be treated. Finally, applications of linear algebra to various specialized topics
will be mentioned.