Data Science, AI, and Machine Learning with R

Gain practical experience in R for Data Analysis, Machine Learning and Artificial Intelligence. Become a Data Scientist.

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Grasp the core concepts of data science and its applications in various industries.
Set up and navigate the R programming environment effectively.
Master R programming fundamentals, including data types, structures, operators, and control flow.
Understand essential statistical and probability concepts for data analysis.
Collect data from diverse sources (flat files, databases, web, APIs).
Clean, manipulate, and preprocess data to ensure its quality and suitability for analysis.
Conduct exploratory data analysis to uncover patterns and insights using visualizations.
Analyze and interpret data effectively using R's powerful statistical and visualization tools.
Build and evaluate various machine learning models for: Prediction (regression), Classification, Clustering, Association rule mining.
Apply dimensionality reduction methods like PCA and LDA.
Utilize ensemble methods (bagging and boosting) to improve model performance.
Build and deploy machine learning models using R to solve real-world problems.
Think critically about data and apply data science techniques in a variety of contexts.
Complete an end-to-end capstone project to solidify learning and demonstrate practical skills in data science and machine learning using R.

Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!

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