EDUCBA
AI Machine Learning with R & Python Projects 专项课程
EDUCBA

AI Machine Learning with R & Python Projects 专项课程

Master Machine Learning with R and Python. Gain hands-on experience building ML models in R and Python through real-world projects.

EDUCBA

位教师:EDUCBA

包含在 Coursera Plus

深入学习学科知识
初级 等级

推荐体验

2 月 完成
在 10 小时 一周
灵活的计划
自行安排学习进度
深入学习学科知识
初级 等级

推荐体验

2 月 完成
在 10 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Apply machine learning algorithms in R and Python to analyze and predict real-world data.

  • Optimize, validate, and interpret models using statistical and computational techniques.

  • Build end-to-end ML projects, from preprocessing to deployment-ready solutions.

要了解的详细信息

可分享的证书

添加到您的领英档案

授课语言:英语(English)
最近已更新!

October 2025

了解顶级公司的员工如何掌握热门技能

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

精进特定领域的专业知识

  • 向大学和行业专家学习热门技能
  • 借助实践项目精通一门科目或一个工具
  • 培养对关键概念的深入理解
  • 通过 EDUCBA 获得职业证书

专业化 - 6门课程系列

您将学到什么

  • Apply ML foundations, probability, and statistical concepts in R.

  • Implement regression, classification, and decision tree models.

  • Use ensemble methods like random forests and boosting in R.

您将获得的技能

类别:Regression Analysis
类别:Random Forest Algorithm
类别:Predictive Modeling
类别:R Programming
类别:Decision Tree Learning
类别:Statistical Analysis
类别:Probability Distribution
类别:Statistical Modeling
类别:Exploratory Data Analysis
类别:Machine Learning
类别:Statistical Methods
类别:Supervised Learning
类别:Applied Machine Learning
类别:Data Analysis
类别:Data Manipulation

您将学到什么

  • Apply clustering, Naive Bayes, PCA, and neural networks in R.

  • Forecast time series with ARIMA, Prophet, and boosting methods.

  • Implement market basket analysis and optimize predictive models.

您将获得的技能

类别:Machine Learning
类别:R Programming
类别:Predictive Modeling
类别:Time Series Analysis and Forecasting
类别:Supervised Learning
类别:Text Mining
类别:Artificial Neural Networks
类别:Dimensionality Reduction
类别:Data Mining
类别:Unsupervised Learning
类别:Applied Machine Learning
类别:Exploratory Data Analysis
类别:Probability & Statistics
类别:Forecasting

您将学到什么

  • Define regression concepts and build simple/multiple models in R.

  • Apply dummy variables, statistical tests, and model validation.

  • Optimize models with backward elimination for predictive accuracy.

您将获得的技能

类别:Regression Analysis
类别:Predictive Modeling
类别:Statistical Hypothesis Testing
类别:Statistical Methods
类别:R Programming
类别:Feature Engineering
类别:Data Analysis
类别:Supervised Learning
类别:Data Visualization
类别:Statistical Modeling
类别:Data Validation

您将学到什么

  • Prepare datasets, handle missing values, and apply imputation.

  • Perform correlation analysis and manage data imbalance.

  • Implement clustering with caret and validate ML workflows.

您将获得的技能

类别:Data Processing
类别:Correlation Analysis
类别:R Programming
类别:Data Quality
类别:Unsupervised Learning
类别:Data Cleansing
类别:Data Integrity
类别:Data Manipulation
类别:Machine Learning Algorithms
类别:Statistical Analysis
类别:Analysis
类别:Data Validation
类别:Exploratory Data Analysis
类别:Feature Engineering
类别:Machine Learning
类别:Applied Machine Learning

您将学到什么

  • Apply probability, sampling, and distributions to datasets.

  • Use linear algebra and hypothesis testing for data analysis.

  • Build and validate ML models with Python in real-world contexts.

您将获得的技能

类别:Probability
类别:Statistics
类别:Python Programming
类别:Linear Algebra
类别:Data Mining
类别:Statistical Inference
类别:Machine Learning
类别:Statistical Hypothesis Testing
类别:Probability Distribution
类别:Sampling (Statistics)
类别:Machine Learning Algorithms
类别:Data Analysis
类别:Statistical Analysis

您将学到什么

  • Apply NumPy, Pandas, and Matplotlib for data analysis & visualization.

  • Build, train, and validate supervised & unsupervised ML models.

  • Implement NLP, face recognition, and text classification projects.

您将获得的技能

类别:NumPy
类别:Applied Machine Learning
类别:Text Mining
类别:Matplotlib
类别:Scikit Learn (Machine Learning Library)
类别:Feature Engineering
类别:Natural Language Processing
类别:Pandas (Python Package)
类别:Unsupervised Learning
类别:Machine Learning
类别:Supervised Learning
类别:Python Programming
类别:Data Manipulation
类别:Data Visualization
类别:Performance Tuning

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位教师

EDUCBA
EDUCBA
560 门课程162,354 名学生

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EDUCBA

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