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。

The Hong Kong University of Science and Technology
您将获得的技能: 微积分, 高等数学, 机械工程, 数学软件, 工程分析, 模拟和模拟软件, Matlab, 有限元方法, 数学建模, 微分方程, 应用数学, 数值分析
★ 5 (44) · 中级 · 课程 · 1-4 周

Rice University
您将获得的技能: 物理学, 微积分, 机械, 电磁学, 积分微积分, 基本电气系统, 线性代数, 解决问题, 电气系统, 电子产品, 电子元件, 电气工程
★ 4.8 (34) · 中级 · 课程 · 1-4 周

Packt
您将获得的技能: 机器学习, 数据可视化, 人工智能和机器学习(AI/ML), 数据科学, 数据预处理, NumPy, 自然语言处理, 回归分析, 深度学习, 线性代数, Seaborn, 数据结构, 逻辑回归, Matplotlib, Python 编程, 数据操作
中级 · 课程 · 1-3 个月

Alberta Machine Intelligence Institute
您将获得的技能: Jupyter, 机器学习算法, Scikit Learn(机器学习库), 监督学习, 机器学习, 功能工程, 分类算法, 应用机器学习, 数据预处理, 数据处理, 决策树学习, 回归分析, Model Evaluation, 工艺优化, 性能分析, Python 编程, 业务解决方案, 模型评估
★ 4.7 (417) · 混合 · 课程 · 1-4 周

University of London
您将获得的技能: Combinatorics, Probability & Statistics, Data Analysis, Advanced Mathematics, Linear Algebra, Mathematics and Mathematical Modeling, Mathematical Theory & Analysis, Applied Mathematics, Statistics, Analysis, Statistical Analysis, Probability, Algorithms, Algebra
初级 · 课程 · 1-4 周

您将获得的技能: Model Evaluation, Tensorflow, Supervised Learning, Artificial Neural Networks, Regression Analysis, Machine Learning Methods, Applied Machine Learning, Machine Learning Algorithms, Deep Learning, Image Analysis, Machine Learning, Random Forest Algorithm, Artificial Intelligence and Machine Learning (AI/ML), Decision Tree Learning, Natural Language Processing, Scikit Learn (Machine Learning Library), Convolutional Neural Networks, Computer Vision, Data Science, Python Programming
★ 4.4 (91) · 高级设置 · 课程 · 1-4 周

您将获得的技能: Model Deployment, Apache Spark, Data Pipelines, MLOps (Machine Learning Operations), PySpark, IBM Cloud, Jupyter, Docker (Software), Machine Learning, Data Science, Python Programming, Scalability, Design Thinking
★ 4.3 (61) · 高级设置 · 课程 · 1-4 周

Duke University
您将获得的技能: Pandas (Python Package), Data Cleansing, Data Manipulation, Data Preprocessing, Data Quality, NumPy, File I/O, Query Languages, Python Programming, Data Import/Export, Data Analysis, Exploratory Data Analysis, Debugging
★ 4.3 (16) · 初级 · 课程 · 1-4 周

Alberta Machine Intelligence Institute
您将获得的技能: 机器学习, 人工智能赋能, 性能指标, 应用机器学习, 运行分析, 道德标准与行为, 数据伦理, 性能调整, MLOps(机器学习运营), 风险缓解, 负责任的人工智能, 持续监测, 业务运营, 利益攸关方沟通, Model Evaluation, 系统集成, 企业战略, 人工智能产品战略, 模型部署, 模型评估, 数据维护
★ 4.4 (51) · 混合 · 课程 · 1-4 周

您将获得的技能: Model Deployment, MLOps (Machine Learning Operations), Cloud Deployment, Unit Testing, Docker (Software), Containerization, Kubernetes, AI Workflows, IBM Cloud, Microservices, Machine Learning, Responsible AI, Business Metrics, Natural Language Processing, Time Series Analysis and Forecasting, Data Science, Python Programming
★ 4.5 (60) · 高级设置 · 课程 · 1-4 周

Rice University
您将获得的技能: Physics, Applied Mathematics, Geometry, Engineering Analysis, Advanced Mathematics, Physical Science, Mathematical Modeling, Trigonometry, Calculus, Algebra, Mathematical Theory & Analysis, Problem Solving
★ 4.8 (6) · 中级 · 课程 · 1-4 周

Illinois Tech
您将获得的技能: Model Evaluation, Statistical Analysis, Data Visualization, Data Analysis, Exploratory Data Analysis, Data Cleansing, Analytics, Machine Learning, Data Preprocessing, Regression Analysis, Data Mining, Python Programming, Scikit Learn (Machine Learning Library), Unsupervised Learning, Classification And Regression Tree (CART), Decision Tree Learning, Logistic Regression
★ 4.3 (6) · 中级 · 课程 · 1-3 个月