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Syllabus

Predictive analytics in R

  • Introduction to Analytics
  • Fundamentals of R
  • Basic Statistics in R
  • Data Cleaning & Visualization in R
  • Linear Regression in R
  • Logistic Regression in R
  • Segmentation for marketing analytics in R
  • Time series forecasting in R
  • Decision Trees in R
  • Random Forest & XGBoost in R
  • Solving an actual business problem through analytics

Machine learning in Python

  • Introduction to Data Science
  • Fundamentals of Python
  • Data summary & visualization in Python
  • Data Handling in Python using NumPy & Pandas
  • Basics of Machine Learning
  • Generalised Linear Models in Python
  • Tree Models using Python
  • Boosting Algorithms in Python
  • SVM and kNN in Python
  • Unsupervised learning in Python
  • Neural Networks in Python
  • Text Mining in Python
  • Ensemble Methods in Python & Bokeh

Data Analysis in SQL

  • Introduction to SQL
  • SQL data types & operators
  • Useful operations in SQL
  • Aggregating Data in SQL
  • Functions and sub-queries in SQL
  • DML and DDL statements in SQL
  • Joins and views in SQL

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