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Introduction to Data Science
• Data
Science life Cycle
• Business
Statistics
Mastering R Programming
• R and
Python programming
• Exploratory
data analysis
• Visualization
• Data
pre-processing
Supervised Learning
• Linear
regression
• Logistic
regression
• Decision
trees
• Naive
Bayes
• Support
Vector Machines
• Random
Forest
• Gradient
Boosting Machine
• Neural
Network
Unsupervised Learning
• Clustering
• Principal
component analysis
Time Series Forecasting
Text Mining
Association Rule Learning
Deep Learning
Dimensionality Reduction
Resume and Interview Preparation
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