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Quick Facts

Medium Of InstructionsMode Of LearningMode Of DeliveryFrequency Of Classes
EnglishSelf Study, Virtual Classroom, Campus Based/Physical ClassroomVideo and Text BasedWeekends

Courses and Certificate Fees

Certificate AvailabilityCertificate Providing Authority
yesIIM Bodh Gaya

The Syllabus

  • Introduction to Data Modelling for Business
  • Fundamentals of Statistics
  • Inferential Statistics
  • Descriptive Statistics with R
  • Concept and Application of Sampling Theory
  • Hypothesis and Testing with R
  • Multivariate Analysis with R
  • Principal Component Analysis and Linear Algebra

  • Data Analytics with Python
  • Python Libraries – NumPy, Pandas, Matplotlib, Scikit
  • Data Visualisations with Tableau

  • Idea of Supervised and Unsupervised Machine Learning
  • Simple & Multiple Linear Regression
  • Logistic Regression
  • Cross-validation and Hyperparameter Tuning
  • Decision Trees and Random Forest
  • Boosting Algorithms
  • Support Vector Machine
  • Neural Networks – Overview of ANN, CNN, RNN
  • Recommender System
  • Clustering (K-means and Hierarchical)

  • Unstructured Data Collection and Web Scrapping
  • Concepts of Text Mining
  • Natural Language Processing
  • Document Classification and Clustering
  • Document Summarisation
  • Sentiment Analysis (Aspect Extraction, Lexicon and SentiWordNet)

  • Introduction to Market Analytics
  • Concepts of Customer Analytics
  • Building Predictive Models: Sales Prediction and Price Prediction
  • Customer Churn Problem
  • Customer profitability and Customer Lifetime Value

  • Business Analytics - HR Strategy Alignment
  • Application of HR Metrics Across Talent Life Cycle
  • Dynamic Dashboarding through PowerBI
  • Organisational Network Analysis using Python
  • Emotional Analysis using Python

  • Understanding the Analytical Aspects of Operations Management
  • Supplier Selection Analytics - Goal Programming Clustering
  • Analytics for Distribution Network Design
  • Analytics for Facility Location
  • Inventory Analytics
  • Maintenance and Quality Analytics

  • Understanding Financial Data
  • Financial Time Series - Introduction & Diagnostics
  • Forecasting Models

  • Application of Analytics in Healthcare
  • Supervised ML in Healthcare - Case Study Approach
  • Survival Analysis
  • IoT in Healthcare

  • Big Data Ecosystem
  • Big Data Strategy
  • ML Using Spark

  • ML Pipeline
  • Production Environment
  • Model Deployment

Articles

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