Computer Aided Decision Systems - Industrial practices using Big Analytics
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Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
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English | Self Study | Video and Text Based |
Courses and Certificate Fees
Fees Informations | Certificate Availability | Certificate Providing Authority |
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INR 1000 | yes | IIT Kanpur |
The Syllabus
- Introduction to Systems
- System Analysis and Design
- Decision Support Systems (DSS)
- Design of Decision Support Systems
- Rational Decisions using DSS
- Introduction to Relational Database
- Relating Multiple Databases
- Case Study on DSS
- Assignment: Practice on DSS Databases
- Basics of Data Modelling
- Models for DSS
- Selecting a Right Model
- Assignment: Practice on Model Selection
- Developing Models for DSS applications
- Introduction to Big Data
- General Applications and Uses
- Big Data Analytics (BDA)
- Assignment: Additional reading material
- Case Study on Retail Industry
- Credit Modeling
- Web Analytics
- BDA in Engineering and Manufacturing
- Assignment: Additional reading material
- Enhancing Quality and Cost Control
- Improving Forecast Accuracy
- Anticipating Demand Changes
- Inventory Management
- Pricing, Market Basket Analysis
- Cost Management
- Medical Monitors, Targeted Drug Delivery
- US BRAIN Initiative
- Alzheimer’s and Parkinson’s models
- Assignment: Case study on Healthcare BDA
- Population Health Strategies
- BDA in transportation
- ATC Management
- Flat Tracking, Tyre & Fuel Usage
- Assignment: Demonstration using soft tools
- Buying Power instead of engine (RR Model)
- Assignment: Case study on Transportation BDA models
- Complaint Redressal
- UAVs, Smart Vehicle Integration
- Big Data practices in Industry
- Introduction to Simulation
- Discrete Event Simulation
- Simulation for Descriptive Analytics
- Simulation for Prescriptive Analytics
- Product Innovation, and Benchmarking
- Real-Time Performance Monitoring (Mc Laren)
- Assignment: Case study on Manufacturing
- BDA and Industry 4.0 Product Lifecycle Management, Managing Innovation
- Assignment: Demonstration on PLM software
- BDA and Healthcare
- Reducing reaction time to critical clinical events
- Back Testing Analytical Models
- Recapitulating the CADSS BDA concept
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