数学课程可以帮助您学习代数、微积分、统计学和离散数学。您可以培养解决问题、逻辑推理和数据分析方面的技能,从而为解读复杂信息提供支持。许多课程会介绍图形计算器、统计软件和 Python 等编程语言等工具,展示这些技能在金融、工程和数据科学等领域的应用。

University of Amsterdam
您将获得的技能: 计算逻辑, 普通数学, 演绎推理, 逻辑推理
高级设置 · 课程 · 1-3 个月

Johns Hopkins University
您将获得的技能: 回归分析, 预测建模, 统计分析, 应用数学, 统计推理, 抽样(统计), 概率分布, 数据科学, 概率与统计, 统计假设检验, 贝叶斯统计, 数学建模, 数据分析, 概率, 统计建模, 统计, 统计方法, 线性代数, 生物统计学, R 语言程序设计(中文版)
高级设置 · 专项课程 · 3-6 个月

University of Colorado Boulder
您将获得的技能: 应用数学, 系统要求, 显示设备, 电气工程, 系统设计与实施, 硬件设计, 设备设计, 医学影像, 计算机辅助设计, 工程分析, 工程计算, 工程学, 模拟和模拟软件, 系统设计, 人为因素, 图像分析, 工程设计流程, 性能调整, 技术设计, 图像质量
攻读学位
高级设置 · 专项课程 · 3-6 个月
Stanford University
您将获得的技能: 机器学习算法, 概率分布, 贝叶斯网络, 统计推理, 抽样(统计), 概率与统计, 网络分析, 图论, 决策支持系统, 机器学习, Algorithm, 计算思维, 马尔可夫模型, 自然语言处理, 统计建模, 网络模型, 统计方法, 应用机器学习
高级设置 · 专项课程 · 3-6 个月

University of Colorado Boulder
您将获得的技能: 应用数学, 定量研究, 概率分布, 机械, 热管理, 模拟, 工程学, 数学建模, 微分方程, 化学, 工程计算, 工程分析, 物理学, 数值分析, 物理科学, 统计方法, 材料科学, 化学工程, 模拟和模拟软件, 机械工程
高级设置 · 专项课程 · 3-6 个月

University of Colorado Boulder
您将获得的技能: 应用数学, 电气工程, 电子产品, 电子系统, 数学建模, 物理学, 电气与计算机工程, 半导体, 电子工程, 材料科学, 电子元件, 电子硬件
攻读学位
高级设置 · 专项课程 · 1-3 个月

University of Colorado Boulder
您将获得的技能: Control Systems, Systems Engineering, Mechanics, Numerical Analysis, Differential Equations, Mathematical Modeling, Simulation and Simulation Software, Engineering Analysis, Simulations, Advanced Mathematics, Linear Algebra, Engineering Design Process, Engineering Calculations, Mathematical Software, Applied Mathematics, Physics, Calculus, Mathematical Theory & Analysis
高级设置 · 专项课程 · 1-3 个月

Princeton University
您将获得的技能: 数据结构, 图论, 概率, 组合学, 数学建模, 数学理论与分析, Algorithm, 理论计算机科学, 高等数学
高级设置 · 课程 · 1-3 个月

EIT Digital
您将获得的技能: 数据访问, 数据结构, 文件系统, 图论, 计算机硬件, Algorithm, 数据存储技术, 性能调整, 理论计算机科学
高级设置 · 课程 · 1-3 个月
University of Colorado Boulder
您将获得的技能: Control Systems, Numerical Analysis, Simulations, Engineering Analysis, Mathematical Modeling, Linear Algebra, Differential Equations, Applied Mathematics, Mathematical Theory & Analysis
高级设置 · 课程 · 1-4 周
University of Colorado Boulder
您将获得的技能: Mechanics, Differential Equations, Mathematical Modeling, Advanced Mathematics, Linear Algebra, Engineering Calculations, Mathematical Software, Applied Mathematics, Physics, Calculus
高级设置 · 课程 · 1-4 周
Stanford University
您将获得的技能: 机器学习算法, 贝叶斯网络, 概率与统计, 统计推理, 抽样(统计), 图论, 应用机器学习, 计算思维, Algorithm, 马尔可夫模型, 统计方法
高级设置 · 课程 · 1-3 个月
Mathematics is the study of numbers, shapes, patterns, and relationships. It serves as a foundational tool for understanding the world around us and is crucial in various fields, including science, engineering, economics, and technology. The importance of mathematics lies in its ability to provide logical reasoning and problem-solving skills, which are essential for making informed decisions and innovations.
A background in mathematics opens doors to a variety of career paths. Potential job roles include data analyst, statistician, actuary, financial analyst, and operations researcher. Additionally, mathematics is integral in fields such as engineering, computer science, and academia, where analytical skills are highly valued.
To succeed in mathematics, you should develop a strong foundation in basic arithmetic, algebra, geometry, and calculus. Critical thinking and problem-solving skills are also essential. Familiarity with mathematical software and programming languages can enhance your capabilities, especially in data analysis and engineering contexts.
Some of the best online mathematics courses include the Mathematics for Engineering Specialization and the Mathematics for Machine Learning and Data Science Specialization. These courses cover essential concepts and applications, making them suitable for various learners.
es. You can start learning mathematics on Coursera for free in two ways:
If you want to keep learning, earn a certificate in mathematics, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.
Mathematics courses typically cover a range of topics, including algebra, calculus, statistics, linear algebra, and discrete mathematics. Advanced courses may explore specialized areas such as mathematical modeling, optimization, and numerical methods.
For training and upskilling employees, courses like the Mathematics for Engineers Specialization and the Foundational Mathematics for AI are excellent choices. These programs equip learners with the mathematical skills necessary for engineering and data science roles.