Basics of Statistics : Concepts such as Data Distribution, Types of Graphs, Standard Deviation and Variance
Advanced Statistics : Get introduced to Sampling, Probability Distribution, Bayes’ Theorem, Hypothesis Testing
Exploratory Data Analysis : Learn Missing Value Treatment, Feature Engineering, Univariate and Bivariate Analysis
Python & R : Algorithms will be taught using Python, with introduction to R
Regression Analysis : Apply Linear and Logistic Regression, Model Building, Model Analysis on Industry-based case studies
Time Series : Learn different components of Time Series, Forecasting Techniques and Model Validation
Clustering : Perform Hierarchical Clustering, K-means Clustering, Scaling
Classification : Apply Decision Tree, Random Forest, KNN, Naïve Bayes’
SQL : Learn about Data Types in SQL and how to manipulate data in SQL to make it analysis ready
Tableau : Learn to prepare interactive dashboards with active filters