医学统计课程
医学统计学课程可以帮助您学习数据分析技术、研究设计原则、假设检验和临床试验结果的解释。您可以掌握分析患者数据、了解流行病学方法以及应用统计软件解决实际健康问题的技能。许多课程都会介绍 R、SAS 或 SPSS 等工具，这些工具支持有效地执行统计分析和实现健康数据的可视化。
热门医学统计学课程和认证
状态：新状态：预览您将获得的技能: Customer Analysis, Statistical Visualization, Unsupervised Learning, Customer Insights, Correlation Analysis, Data Preprocessing, Pandas (Python Package), Heat Maps, Data Manipulation, Seaborn, Histogram, Scatter Plots, Matplotlib, Exploratory Data Analysis, Applied Machine Learning, Data Visualization Software
状态：新状态：预览Microsoft
您将获得的技能: Data Manipulation, Data Transformation, Tidyverse (R Package), Data Wrangling, R Programming, Exploratory Data Analysis, Data Analysis, Data Cleansing
状态：新状态：免费试用Empower School of Health
您将获得的技能: Healthcare Project Management, Internet Of Things, Cybersecurity
状态：预览您将获得的技能: Benchmarking, Search Engine Optimization, Content Performance Analysis, Keyword Research, Marketing Analytics, Key Performance Indicators (KPIs), Performance Analysis, Web Analytics and SEO, Performance Measurement, Content Strategy, Performance Improvement, Driving engagement, Trend Analysis, Customer Insights
状态：预览您将获得的技能: Deep Learning, Applied Machine Learning, Artificial Intelligence, Computer Vision, Image Analysis, Natural Language Processing, Model Evaluation, Exploratory Data Analysis, Interactive Data Visualization, Performance Tuning, Data Import/Export
状态：免费试用Arizona State University
您将获得的技能: Exploratory Data Analysis, Decision Making, Unstructured Data, Data-Driven Decision-Making, Data Literacy, Data Management, Solution Design, Data Analysis, Needs Assessment, Requirements Analysis
状态：新状态：预览您将获得的技能: Model Evaluation, Exploratory Data Analysis, Data Preprocessing, Predictive Modeling, Decision Tree Learning, Credit Risk, Random Forest Algorithm, Feature Engineering, Financial Modeling, Logistic Regression, Data Analysis, Statistical Machine Learning, Applied Machine Learning, Scikit Learn (Machine Learning Library), Pandas (Python Package), Machine Learning Methods, Classification Algorithms
Coursera
您将获得的技能: Exploratory Data Analysis, R Programming, Data Manipulation, Statistical Programming, Data Analysis, File Management, Integrated Development Environments, Programming Principles, Data Science, Data Structures, Computer Programming
状态：预览Northwestern University
您将获得的技能: Robotics, Machine Controls, Mechanics, Torque (Physics), Automation Engineering, Mathematical Modeling, Engineering Analysis, Engineering Calculations, Structural Analysis, Mechanical Design, Numerical Analysis, Applied Mathematics, Trigonometry, Control Systems, Linear Algebra, Visualization (Computer Graphics), Spatial Analysis
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
您将获得的技能: Dashboard, Kibana, Google Cloud Platform, Cloud Computing, Data Import/Export, Financial Data, Mainframe Computing, Dataflow, Big Data, Exploratory Data Analysis, SQL, Data Analysis
状态：新状态：免费试用您将获得的技能: Exploratory Data Analysis, Data Storytelling, Dashboard, Data Presentation, Data Analysis, Data Literacy, No-Code Development, Data Science, Predictive Modeling, Data Ethics, Data Capture, Data Modeling, Data Processing, Data Transformation, Data Integrity, Data Cleansing, Applied Machine Learning, Data Governance, Data Collection, Data Integration
总之，以下是 10 最受欢迎的 medical statistics 课程
- Customer Segmentation with K-Means: Model & Visualize: EDUCBA
- Mastering Data Wrangling with dplyr: Microsoft
- Digital Transformation in Healthcare: Empower School of Health
- YouTube Analytics: Optimize Performance: Coursera
- H2O Hydrogen Torch Starter Course: H2O.ai
- Extracting Value from Dark Data: ULEADD: Arizona State University
- Credit Default Prediction with Python: Apply & Analyze: EDUCBA
- R أساسيات لغة البرمجة: Coursera
- 현대 로봇공학, 강좌 2: 로봇 기구학: Northwestern University
- Advanced ML Algorithms & Unsupervised Learning: Packt
