Machine Learning and Data Science


Machine Learning and Data Science


An Overview of Analytics and Data Science

  • Prominence of Analytics in the current world

  • Application of Analytics

  • Analytics Technologies and Resources

  • Models and Algorithms


Business Statistics and Application


  • An introduction to statistics

  • Descriptive Statistics

  • Probability and Sampling

  • Inferential Statistics

  • Hypothesis Testing


Introduction to Python


  • Understanding Analytics & Exploring Python

  • Syntax in Python

  • Data Manipulation in Python

  • Data Visualization in Python


Art of solving a business problem


    • Data Science Life Cycle

    • Exploratory Data Analysis

    • Visualisation

    • Data Pre-processing and imputation

    • Feature Engineering


Predictive Models and Machine Learning


  • Supervised Machine Learning

  • Linear Regression Models

  • Classification Models

  • Unsupervised Machine Learning

  • K-Means Clustering Models


Capstone Project


  • Understand the business problem for the use case provided

  • Participate in a formal group discussion on the underlying premises and the hypothesis

  • Work in groups to analyze the data and come-up with inferences and insights

  • Individually build a suitable data analytics model

  • Measure the accuracy of the model and develop an Analytics Project Report


Connecting the dots - Story Telling for your Project