Course Content
1. Fundamentals
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1.1 Statistics
1.2 Probability and Probability Distributions
2. Data Science using R Programming
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2.1 Introduction: What is Data Science?
2.2 Introduction to R
2.3 Basic Operations in R Programming
2.4 Data Handling in R Programming
2.5 R data structure
2.6 Using functions in R
2.7 Introduction To Machine Learning
2.8 Machine Learning Concepts & Terminologies
2.9 Linear Regression
2.10 Hypothesis Testing
2.11 Decision Trees And Supervised Learning
2.12 Unsupervised Classification Algorithms
2.13 Introduction to Deep Learning
Data Science based on R programming
About Lesson
  • What is Machine Learning?
  • What is the Challenge?
  • Why Learn?
  • When is Learning required?
  • Data Mining
  • Application Areas and Roles
  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement learning
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