Data Science with R
Learn Data Science using R from scratch. Build your career as a Data Scientist. Explore knitr, buzz dataset, adv methods
What you’ll learn
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Data Science using R programming
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Become a Data Scientist
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Data Science Learning Path
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How to learn Data Science
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Data Collection and Management
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Model Deployment and Maintenance
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Setting Expectations
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Loading Data into R
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Exploring Data in Data Science and Machine Learning
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Exploring Data using R
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Benefits of Data Cleaning
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Cross Validation in R
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Data Transformation
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Modeling Methods
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Solving Classification Problems
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Working without Known Targets
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Evaluating Models
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Confusion Matrix
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Introduction to Linear Regression
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Linear Regression in R
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Simple and Multiple Regression
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Linear and Logistic Regression
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Support Vector Machines (SVM) in R
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Unsupervised Methods
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Clustering in Data Science
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K-means Algorithm in R
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Hierarchical Clustering
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Market Basket Analysis
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MBA and Association Rule Mining
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Implementing MBA
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Association Rule Learning
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Decision Tree Algorithm
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Exploring Advanced Methods
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Using Kernel Methods
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Documentation and Deployment
Requirements
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Enthusiasm and determination to make your mark on the world!
Who this course is for:
- Data Scientists
- Anyone aspiring for a career in Data Science and Machine Learning
- Machine Learning Engineers
- R Programmers
- Newbies and Beginners wishing to start their career in R Programming and Data Science
- Data Analysts & Advanced Data Analytics Professionals
- Software Engineers & Developers
- Senior Data Scientists
- Chief Technology Officers (CTOs)
- Statisticians and Data Science Researchers
- Data Engineers
- R Programmers Analytics
- Senior Data Analysts – R, Python Programming
- Data Science Engineers
