Industrial Project

GANPAT UNIVERSITY

FACULTY OF TECHNOLOGY

Programme 

Bachelor of Technology 

Branch/Spec. 

Computer Science & Engineering (BDA)

Semester 

VIII 

Version 

1.0.0.0

Effective from Academic Year 

2020-21 

Effective for the batch Admitted in 

June 2017

Subject code 

2CSE801 

Subject Name 

INDUSTRIAL PROJECT 

Teaching scheme 

Examination scheme (Marks)

(Per week) 

Lecture(D 

T)

Practical(Lab. )

Total 

CE 

SEE 

Total

L 

TU 

P 

TW

Credit 

0 

0 

16 

0 

16 

Theory 

00 

00 

000

Hours 

0 

0 

32 

0 

32 

Practical 

200 

200 

400

Pre-requisites:

Programming Languages, Web Technologies, Software Engineering, Big Data Application Development, Data  Science and Modeling , Big Data Analytics, Machine Learning, Internet of Things, Functional Programming 

Learning Outcome:

After successful completion of this subject students will be able to: 

● Understand core technical concepts related to Business Intelligence , Big Data Analytics along with  Hadoop Architecture  

● Apply relevant theoretical and practical knowledge to understand Business Analytics solutions and  highlight key capabilities of Big Data & Business Analytics  

● Apply cutting edge Analytical Tools to Find, Interpret, Analyze Business Data  

● Align Big Data technology to the need of business

Guidelines for Project: 

- Students have to do project work individually / in the team of max 2 persons. - Individual evaluation will be done. 

- There will be 3 midterm evaluation along with the presentation on a monthly basis.. One of them  is conducted by an external examiner. 

- Final evaluation will be done by external examiner. 

Guidelines for Industrial Project: 

- Students have to do project work individually / in the team of max 2 persons. - Individual evaluation will be done. 

- Students will have to come for first reporting within first four weeks of semester.

- There will be 3 midterm evaluations along with presentation on a monthly basis. First midterm  evaluation will be within 6 weeks and second midterm evaluation will be within 10 weeks from  starting of the semester. 

Final evaluation and 1 midterm evaluation will be done by external examiner.

Course Outcomes:

Cos 

Description

CO1 

Give exposure of Industry and real time project experience

CO2 

Learn and gain experience for collaborating in team for problem solving

CO3 

To development skills like technical communication, presentations, software development life  cycle activities

CO4 

Enhance and/or expand the student's knowledge of a particular area(s) of big data analytics.

COs 

PO1 

PO2 

PO3 

PO4 

PO5 

PO6 

PO7 

PO8 

PO9 

PO10 

PO11 

PO12

CO1 

3 

3 

3 

3 

3 

3 

2 

2 

2 

3 

2 

3

CO2 

2 

2 

2 

2 

2 

3 

3 

2 

2 

2 

3 

3

CO3 

3 

2 

2 

3 

2 

2 

2 

3 

3 

2 

2 

2

CO4 

2 

3 

3 

2 

3 

3 

3 

3 

2 

2 

3 

3