Advanced Diploma in Data Care Management

Guru Nanak Dev University
In Amritsar

Price on request
You can also call the Study Centre
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Important information

Typology Diploma
Location Amritsar
  • Diploma
  • Amritsar


Where and when

Starts Location
On request
Amritsar, Punjab, Punjab, India
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Starts On request
Amritsar, Punjab, Punjab, India
See map

Course programme

The Guru Nanak Dev University's Faculty of Engineering and Technology offers Advanced Diploma in Data Care Management to its students. The course structure for it is as follows:

Introduction to Data Mining: What is data mining, data mining process, data mining tasks, classification, regression, clustering, summarization, association rules, data mining techniques, statistics, machine learning, decision trees, artificial neural networks, genetic algorithms, The 5A process model, CRISP-DM
Process Model
Data Warehouse : Introduction, objectives of Data warehouse, Data marts, Metadata, DW Architecture, process of Designing a Data warehouse, Layered Architecture of a Data warehouse, Data warehouse components based Architecture, OLAP and its types, Relating Data warehouse and Data Mining, Data warehouse usage.

Classification: Introduction to Classification, Distance based algorithms, K Nearest Neighbors, Decision Tree based algorithms, Neural Network based algorithms, Propagation in Neural network, Rule based Algorithms,

Clustering: Introduction, Requirements of cluster analysis, types of data, Interval-scaled variables, binary variables, nominal, ordinal, ratio-scaled variables, k-means method, k-medoids method, hierarchical method, density based method, chameleon method, Grid based method, Model based method Neural network approach.

Association Rules: Introduction, Apriori Algorithm, Sampling algorithm, partitioning algorithm, parallel and distributed algorithms, count distribution algorithms, data distribution algorithm, comparing the algorithms, Various association rules,

Text Mining: Introduction, Usage, tasks, Process, Applications, methods.

Web Mining: Introduction, Tasks, Issues, Software, Web content mining, Web usage mining, Web structure mining.

Spatial Data Mining: Introduction, Application, Tools, Methods.

Multimedia Data Mining: Introduction, Types of Multimedia data mining.

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