代数课程
代数课程可以帮助您学习解方程、处理不等式、理解函数及其图形。您还可以培养处理代数表达式、分解多项式以及将代数概念应用于实际问题的技能。许多课程都会介绍一些工具，如图形计算器和函数 Visualization 软件，这些工具可以提高您分析数据和建立关系模型的能力。
热门代数课程和认证
状态：新状态：免费试用您将获得的技能: Data Import/Export, NumPy, Pandas (Python Package), Pivot Tables And Charts, Business Reporting, Data Manipulation, Analytics, Data Processing, Management Reporting, Data Wrangling, Business Analytics, Data Cleansing, Data Analysis, Data Transformation, Statistical Analysis, Data Management, Descriptive Statistics, Linear Algebra
状态：免费试用Johns Hopkins University
您将获得的技能: Precision Medicine, Clinical Trials, Data Analysis, Data-Driven Decision-Making, Analytics, Data Science, Strategic Decision-Making, Root Cause Analysis, Random Forest Algorithm, Treatment Planning, Personalized Service, A/B Testing, Machine Learning, Online Advertising
状态：免费试用Duke University
您将获得的技能: Python Programming, Simulations, Debugging, Pandas (Python Package), Program Development, Unit Testing, Test Case, Data Science, Software Design, Computational Thinking, Integration Testing, Computer Programming, Object Oriented Programming (OOP), Data Manipulation, Software Development
状态：免费试用Johns Hopkins University
您将获得的技能: Data Visualization, Network Analysis, Relational Databases, Data Visualization Software, Social Network Analysis, Data Storytelling, Data Analysis, Data Manipulation, Social Impact, Human Factors, Innovation
状态：预览您将获得的技能: Algorithms, Technical Communication, Computational Thinking, Solution Design, Programming Principles, Software Design, Theoretical Computer Science, Data Structures, Problem Management, Mathematical Modeling, Applied Mathematics, Computer Science, Performance Tuning
状态：免费试用您将获得的技能: Dimensionality Reduction, Unsupervised Learning, Deep Learning, Model Evaluation, Machine Learning Algorithms, Applied Machine Learning, Random Forest Algorithm, Feature Engineering, Artificial Neural Networks, Supervised Learning, Statistical Machine Learning, Anomaly Detection, Classification Algorithms, Performance Tuning
状态：免费试用DeepLearning.AI
您将获得的技能: 卷积神经网络, 微积分, 监督学习, 人工神经网络, 深度学习, Python 程序设计, 线性代数, 递归神经网络 (RNN), 应用机器学习
状态：预览The University of Sydney
您将获得的技能: 衍生产品, 工程计算, 微积分, 算术, 制图, 代数, 几何学, 数学建模, 三角法, 高等数学, 积分微积分, 估算
状态：预览Johns Hopkins University
您将获得的技能: 微软Excel, 商业分析, 数据建模, 资源分配, 运筹学, 财务分析, 线性代数, 统计分析, 数学建模, 统计方法, 分析, 解决复杂问题, 业务流程建模, 预测分析, 回归分析, 工艺优化, 运输业务, 业务建模, 风险模型, 风险分析
状态：预览Erasmus University Rotterdam
您将获得的技能: 时间序列分析和预测, 模型评估, 线性代数, 统计分析, 案例研究, 统计, 概率, 数据分析, 逻辑回归, 计量经济学, 回归分析, 预测, 分析, 同行评审
状态：预览University of Washington
您将获得的技能: 监督学习, Machine Learning 方法, 线性代数, 人工神经网络, Matlab, 数学建模, 生物学, 机器学习算法, 网络模型, 强化学习, 计算机科学, 神经学, 计算思维, 递归神经网络 (RNN), 概率分布, 生理学
状态：预览Georgia Institute of Technology
您将获得的技能: 概率与统计, 液压, 微积分, 水文学, 土木工程, 统计, 代数, 微分方程, 概率, 几何学, 工程学, 三角法, 机械, 高等数学, 机械工程, 结构分析
总之，以下是 10 最受欢迎的 algebra 课程
- NumPy & Pandas: Analyze & Manage Retail Data: EDUCBA
- Data Science Decisions in Time: Using Causal Information: Johns Hopkins University
- Designing Larger Python Programs for Data Science: Duke University
- Network Visualization and Intervention: Johns Hopkins University
- Algorithmic Solutions: Design, Problem Solving, Reporting: Coursera
- Advanced ML Algorithms & Unsupervised Learning: Packt
- 神经网络与深度学习: DeepLearning.AI
- 微积分入门: The University of Sydney
- 使用 Excel 进行商业分析：初级到高级: Johns Hopkins University
- 计量经济学：方法与应用: Erasmus University Rotterdam
