1. To analyse and apply deep leaning building blocks in the development of business solutions
2. To evaluate and create neural netwrok models to solve business related issues
3. To choose a model to describe the type of data in business related issues and allied sectors
4. To design and implement various machine learning algorithms for a range of real world problems in business and allied domains and sectors
CO1- The student will be able to analyze deep leaning building blocks in the development of business solutions
CO2- The student will be able to evaluate neural netwrok models to solve business related issues
CO3- The student will be able to choose a model to analyze the type of data in business related issues and allied sectors
CO4- The student will be able to design various machine learning algorithms for a range of real world problems in business and allied domains and sectors
CO5- The student will be able to assess how the advanced machine learning tools support the analysis and visualisation of data
2. To evaluate and create neural netwrok models to solve business related issues
3. To choose a model to describe the type of data in business related issues and allied sectors
4. To design and implement various machine learning algorithms for a range of real world problems in business and allied domains and sectors
CO1- The student will be able to analyze deep leaning building blocks in the development of business solutions
CO2- The student will be able to evaluate neural netwrok models to solve business related issues
CO3- The student will be able to choose a model to analyze the type of data in business related issues and allied sectors
CO4- The student will be able to design various machine learning algorithms for a range of real world problems in business and allied domains and sectors
CO5- The student will be able to assess how the advanced machine learning tools support the analysis and visualisation of data
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
1. To analyse and apply sentiment and opinion analysis in the development of business solutions.
2. To evaluate and create social CRM network models to solve business related issues.
3. To describe the type fof data in social networks for business related issues in allied sectors
4. To implement context mining based natural language processing algorithms for data extraction in SN for business related fields
CO1- The students will be able to analyze sentiment and opinion analysis in the development of business solutions
CO2- The students will be able to create social CRM network models to solve business related issues
CO3- The students will be able to explain the types of data in social networks for business related issues in allied sectors
CO4- The students will be able to implement context mining based natural language processing algorithms for data extraction in SM for business related fields
CO5- The students will be able to examine the ethical and legal implications of leveraging social media data
2. To evaluate and create social CRM network models to solve business related issues.
3. To describe the type fof data in social networks for business related issues in allied sectors
4. To implement context mining based natural language processing algorithms for data extraction in SN for business related fields
CO1- The students will be able to analyze sentiment and opinion analysis in the development of business solutions
CO2- The students will be able to create social CRM network models to solve business related issues
CO3- The students will be able to explain the types of data in social networks for business related issues in allied sectors
CO4- The students will be able to implement context mining based natural language processing algorithms for data extraction in SM for business related fields
CO5- The students will be able to examine the ethical and legal implications of leveraging social media data
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
1. To analyse and visualise the data
2. To visualise the data by applying data mining techniques such as clustering, classification
3. To analyse the content by creating data models, aggregated tables, reports, dashboards
4. To visualise data by creating reports and dashboards
CO1- The student will be able to analyze and visualise the data.
CO2- The student will be able to analyze the data mining techniques such as clustering, classification.
CO3- The student will be able to analyze the content by creating data models, aggregated tables, reports, dashboards.
CO4- The student will be able to create reports and dashboards.
CO5- The student will be able to analyze the data to solve business issues and concerns.
2. To visualise the data by applying data mining techniques such as clustering, classification
3. To analyse the content by creating data models, aggregated tables, reports, dashboards
4. To visualise data by creating reports and dashboards
CO1- The student will be able to analyze and visualise the data.
CO2- The student will be able to analyze the data mining techniques such as clustering, classification.
CO3- The student will be able to analyze the content by creating data models, aggregated tables, reports, dashboards.
CO4- The student will be able to create reports and dashboards.
CO5- The student will be able to analyze the data to solve business issues and concerns.
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