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.

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

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

Supervised Learning, Machine Learning, Text Mining, Artificial Neural Networks, Forecasting, Exploratory Data Analysis, Unsupervised Learning, Probability & Statistics, Time Series Analysis and Forecasting, Predictive Modeling, Dimensionality Reduction, Applied Machine Learning, R Programming, 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 Analysis, Statistical Hypothesis Testing, Predictive Modeling, Data Visualization, Regression Analysis, Statistical Methods, Supervised Learning, Feature Engineering, Data Validation, R Programming, and Statistical Modeling

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

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

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

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

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

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

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Instructor

EDUCBA
EDUCBA
515 Courses126,695 learners

Offered by

EDUCBA

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