EDUCBA
AI Machine Learning with R & Python Projects Specialization
EDUCBA

AI Machine Learning with R & Python Projects Specialization

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

EDUCBA

Instructor: EDUCBA

Included with Coursera Plus

Get in-depth knowledge of a subject
Beginner level

Recommended experience

2 months to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Earn a Certificate
With paid plans
Get in-depth knowledge of a subject
Beginner level

Recommended experience

2 months to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Earn a Certificate
With paid plans

What you'll learn

  • 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.

Details to know

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Taught in English
Recently updated!

October 2025

71 practice exercises

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Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from EDUCBA

Specialization - 6 course series

What you'll learn

  • 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.

Skills you'll gain

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

What you'll learn

  • 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.

Skills you'll gain

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

What you'll learn

  • 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.

Skills you'll gain

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

What you'll learn

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

  • Perform correlation analysis and manage data imbalance.

  • Implement clustering with caret and validate ML workflows.

Skills you'll gain

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

What you'll learn

  • 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.

Skills you'll gain

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

What you'll learn

  • 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.

Skills you'll gain

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

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Instructor

EDUCBA
EDUCBA
515 Courses126,695 learners

Offered by

EDUCBA

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