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Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery | Frequency Of Classes |
|---|---|---|---|
| English | Self Study, Virtual Classroom, Campus Based/Physical Classroom | Video and Text Based | Weekends |
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | IIM 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
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31 Aug'23, 12:10 PM
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