• Introduction to data science • Applications of data science • Importance of data science • Difference between Machine Learning, Deep Learning and Ai • Introduction to Deep learning • Introduction to Ai

• Data and Data types • Measures of central tendency • Variance, Standard Deviation and Range • Skewness & Kurtosis • Various distributions • Basic plots

• Clustering • Principal Component Analysis • Association Rules • Recommender systems • Singular value Decomposition • Text Mining • Processing the text • Positive word clouds • Negative word cloud • Applications of positive & negative word cloud

• Installation of R & R-studio • Introduction to R • Usage of packages • How to deal with outliers • How to overcome overfitting and Underfitting • Hands-on sessions • Building a model • How to improve accuracy of a model