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Data Science Online Training course content by IT experts

 

Introduction to Data Science and Statistical Analytics • Introduction to Data Science, Use cases
• Need of Business Analytics
• Data Science Life Cycle
• Different tools available for Data Science
Introduction to R • Installing R and R-Studio, R packages, R Operators, if statements and loops (for, while, repeat, break, next), switch case
Data Exploration, Data Wrangling and R Data Structure • Data exploratory analysis
• R Data Structure (Vector, Scalar, Matrices, Array, Data frame, List), Functions, Apply Functions
Data Visualization • Bar Graph (Simple, Grouped, Stacked)
• Histogram, Pi Chart
• Line Chart
• Box (Whisker) Plot, Scatter Plot,
Introduction to Statistics Terminologies of Statistics
• Measures of Centers
• Measures of Spread
• Probability
• Normal Distribution
• Binary Distribution
• Hypothesis Testing
• Chi Square Test
• ANOVA
Predictive Modeling – 1 • Supervised Learning – Linear Regression ,Bivariate Regression, Multiple Regression Analysis, Correlation( Positive, negative and neutral)

• Machine Learning Use-Cases, Machine Learning Process Flow, Machine Learning Categories

Predictive Modeling – 2 • Logistic Regression
Decision Trees What is Classification and its use cases?
• What is Decision Tree?
• Algorithm for Decision Tree Induction
• Creating a Perfect Decision Tree
• Confusion Matrix
Random Forest • Random Forest
• What is Naive Bayes?
Unsupervised learning What is Clustering & its Use Cases?
• What is K-means Clustering?
• What is Hierarchical Clustering?,
Association Analysis and Recommendation engine • Market Basket Analysis (MBA)
• Association Rules
• Apriori Algorithm for MBA
• Introduction of Recommendation Engine
• Types of Recommendation – User-Based and Item-Based
• Recommendation Use-case
Python, Datawarehouse , Big data, Process, Documentation,  ,

 

 

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