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Data Analytics Training

3 Days

  • Introduction to the course
  • Descriptive Statistics
  • Probability Distributions
  • Inferential Statistics through hypothesis tests
  • Regression
  • ANOVA (Analysis of Variance)
  • Differentiating algorithmic and model based frameworks
  • Regression: Ordinary Least Squares, Ridge Regression, Lasso Regression,
  • K Nearest Neighbours Regression & Classification
  • Bias-Variance Dichotomy
  • Model Validation Approaches
  • Logistic Regression
  • Linear Discriminant Analysis
  • Quadratic Discriminant Analysis
  • Regression and Classification Trees
  • Support Vector Machines
  • Ensemble Methods: Random Forest
  • Neural Networks
  • Deep learning
  • Clustering
  • Associative Rule Mining
  • Challenges for big data analytics
  • Creating data for analytics through designed experiments
  • Creating data for analytics through  Active learning
  • Creating data for analytics through Reinforcement learning