To analyse and apply deep leaning building blocks in the development of business solutions
To evaluate and create neural netwrok models to solve business related issues
To choose a model to describe the type of data in business related issues and allied sectors
To design and implement various machine learning algorithms for a range of real world problems in business and allied domains and sectors
To evaluate and create neural netwrok models to solve business related issues
To choose a model to describe the type of data in business related issues and allied sectors
To design and implement various machine learning algorithms for a range of real world problems in business and allied domains and sectors
Catalogue Code: T3653
Course Type: Generic Core Course
Total Credit: 2
Credits (Theory): 2
No. of Hours: 30
Internal Marks: 60
External Marks : 40
Total Marks: 100
Experiential Learning: Yes
Course Code: 212410223
Floating Credit: No
Audit Course: No
Course Needs: Global
To analyse and apply sentiment and opinion analysis in the development of business solutions.
To evaluate and create social CRM network models to solve business related issues.
To describe the type fof data in social networks for business related issues in allied sectors
To implement context mining based natural language processing algorithms for data extraction in SN for business related fields
To evaluate and create social CRM network models to solve business related issues.
To describe the type fof data in social networks for business related issues in allied sectors
To implement context mining based natural language processing algorithms for data extraction in SN for business related fields
Catalogue Code: T2692
Course Type: Generic Core Course
Total Credit: 2
Credits (Theory): 2
No. of Hours: 30
Internal Marks: 60
External Marks : 40
Total Marks: 100
Experiential Learning: Yes
Primary Purpose of Course: Skill Development
Course Code: 212410225
Floating Credit: No
Audit Course: No
Course Needs: Global
To analyse and visualise the data
To visualise the data by applying data mining techniques such as clustering, classification
To analyse the content by creating data models, aggregated tables, reports, dashboards
To visualise data by creating reports and dashboards
To visualise the data by applying data mining techniques such as clustering, classification
To analyse the content by creating data models, aggregated tables, reports, dashboards
To visualise data by creating reports and dashboards
Catalogue Code: T2693
Course Type: Generic Core Course
Total Credit: 2
Credits (Theory): 2
No. of Hours: 30
Internal Marks: 60
External Marks : 40
Total Marks: 100
Experiential Learning: Yes
Course Code: 212410224
Floating Credit: No
Audit Course: No
Course Needs: Global