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Certificate Course in Advance Analytics & Statistical Modeling

Next Dates Asia/Kolkata
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Coverage

Basic Concept of Statistics, Introduction of Analytics, Data & Variable Definition, Concept of Supervised and Unsupervised Learning, Descriptive Statistics - Mean, Median, Mode, Standard Deviation and Variance, Coefficient of Variation, Covariance Analysis, Cor- relation Analysis, Concept of Graphs & Charts - Histogram, Boxplot, Scatter Plot, Line Chart, Bar Diagram, Pie Chart, Statistical Distributions - Normal, Binomial, Poisson Distribution, Concept of Hypothesis Testing, Types of Statistical Testing - T-Test, ANOVA, Chi-Square Test, Regression Analysis, Multiple Linear Regression Analysis, Model Accuracy Checking, Logistic Regression, Confusion Matrix, Overall Accuracy, Recall (Sensitivity), Precision, F-Score, Decision Tree, Ensemble Models, Bagging Technique, Random Forest,Gradient Boosting Algorithm (GBM), Unsupervised Techniques - Principal Component Analysis (PCA), How PCA Works in Real Dataset, Cluster Analysis - K-Means Clustering.

Who Can Attend

  • Science
  • Statistics Aspirants
  • Mathematics Graduates
  • Commerce
  • Faculty members
  • data Engineers
  • IT Professionals
  • Administrators
  • Job seekers