CSE – Artificial Intelligence & Machine Learning

CSE - Artificial Intelligence & Machine Learning

KOMMURI PRATAP REDDY INSTITUTE OF TECHNOLOGY

About Department of CSE - Artificial Intelligence & Machine Learning

The Department of Computer Science And Engineering was established in the year 2008. Experienced professors guide the department aiming at educating and training students with sound knowledge and awareness in the fields of Computers, Communication, and Information Technology.

The major goal of the Department of Computer Science And Engineering is to produce highly knowledgeable, competent and resourceful young engineers who can perform well in a wide variety of job profiles. To achieve this, curriculum provides a strong foundation in both the analytic, computing and technological aspects of Computer Science Engineering.

It also provides ample opportunities to students to work on mini-projects, develop communication skills, explore internship opportunities in industry and world-class universities and take part in national and international design contests.

The Department of CSE also organizes Workshops, Expert Talks, Project Expo, Poster Presentation competitions for the students. The department has established the Remote Centre in Supported with IIT Bombay.

Core Companies offering Computer Science And Engineering IMCS group , Madhees Techno Pvt Ltd, Proto Tech Solutions, SIG, ERT Technologies, Multiplier, Stealth Technologies, BYJU’s, Aliens Developers Pvt Ltd.

Vision of the Department

To produce excellent standard, quality education of professionals by imparting cognitive learning environment, ethical, research and industrial orientation to become pioneering Data Scientists

Mission of the Department

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge by using structured and unstructured data.
Data science which depend on the application. More recently, full-featured, end-to-end platforms have been developed and heavily used for data science and machine learning.
To facilitate the programming skills by imparting the qualitative technicality in theoretical and pragmatically approaches.
Enabling students to get expertise in critical skills with data science education and facilitate socially responsive research and innovation.

Syllabus

Faculty

S.No.	Name of the Faculty	Qualification	Designation	JNTU ID	Details
1.	Dr T KISHANRAO	PhD	Professor	7314-220704-170801	View
2.	POWN KAMARAJAPANDIAN	PhD	Professor	6264-221201-143335	View
3.	P SHANTHI KUMARI	M.Tech	Asst.Professor	9823-200307-161006	View
4.	J SWATHI	M.Tech	Asst.Professor	7043-220121-123311	View
5.	P SOUJANYA	M.Tech	Asst.Professor	1749-150422-130013	View
6.	MD PASHA	M.Tech	Asst.Professor	6374-210819-145155	View
7.	T DEEPIKA	M.Tech	Asst.Professor	6260-220328-143855	View
8.	B RAJESH REDDY	M.Tech	Asst.Professor	9294-220331-112428	View
9.	V HARSHITHA	M.Tech	Asst.Professor	3906-161222-134435	View
10.	A HAREESHA	M.Tech	Asst.Professor	8123-161227-115221	View
11.	B SHOBARANI	M.Tech	Asst.Professor	3892-230119-153526	View
12.	A ASHOK KUMAR	M.Tech	Asst.Professor	6649-150411-155740	View
13.	N ANUSHA	M.Tech	Asst.Professor	7551-230605-191859	View
14.	INDIRA SAMALA	M.Tech	Asst.Professor	84150406-132500	View
15.	HEMALATHA P	M.Tech	Asst.Professor	3708-230602-105537	View
16.	K SWATHI	M.Tech	Asst.Professor	6683-170125-124551	View
17.	R DINESH KUMAR	M.Tech	Asst.Professor	5772-230321-114439	View
18.	A ASHARANI	M.Tech	Asst.Professor	6585-230618-123011	View
19.	T RAVINDER	M.Tech	Asst.Professor	5610-230804-120723	View
20.	P MANEMMA	M.Tech	Asst.Professor	0187-150419-123425	View
21.	V SONY	M.Tech	Asst.Professor	1819-240217-164140	View
22.	A AMARESHWAR	M.Tech	Asst.Professor	34150407-111157	View
23.	I VASANTHA KUMARI	M.Tech	Asst.Professor	9190-220705-171631	View
24.	CHEKKILLA NAVYA	M.Tech	Asst.Professor	9009-250311-155656	View
25.	S CHANDRASHEKAR	M.Tech	Asst.Professor	3796-150506-173342	View
26.	SAMREEN	M.Tech	Asst.Professor	2820-211102-125433	View

Course Outcomes

Course Outcomes are statements that describe significant and essential learning that the Students have achieved, and can reliably demonstrate at the end of a course. A Course outcome makes clear the intended result of the learning rather than what form the instruction will take. A good course outcome states what a student will know or be able to do at the end of instruction. It focuses on student performance. Other synonyms are learning outcome or Course learning outcome.

The advantages of CourseOutcomes:

Benefits for the course and module designer

In terms of course and module design, the use of explicit course outcome statements can help ensure consistency of delivery across modules or programs. They can aid curriculum design by clarifying areas of overlap between existing modules, program and qualifications.

Benefits for quality assurance and standards

Quality assurance benefits from the adoption of learning outcomes via the resulting increase in transparency and better comparability of standards between and within qualifications.

Benefits for Students and employers

Students benefit from a comprehensive set of statements of exactly what they will be able to achieve after successful study. Course outcomes provide Students with clear information that can help them with their choice of module/unit/program/qualification to study and can lead to more effective learning.

Benefits for national and international educational transparency

Internationally, Course outcomes contribute to the mobility of students by facilitating the recognition of their qualifications and improving the transparency of qualifications and thus simplifying credit transfer.

Course Outcomes for the Department of Computer Science and Engineering

Laboratories

ACADEMIC LABS			COMPUTING FACILITIES WITHIN THE DEPARTMENT
Name of Academic Lab		Room No	Major Equipment	No.of Systems	Printers	Other if any
1	Python Programming lab	B203/A	computer systems	36	1	UPS,LinuxServer,Internet facility
2	Database Lab	B203/B	computer systems	36	1	Projector, Internet facility
3	Data Structures Lab	B204	computer systems	36	1	Internet facility
4	Java Programming Lab	B306	computer systems	36	1	Internet facility
5	IT Workshop Lab	B308	computer systems	36	1	Internet facility
6	Operating Systems Lab	B309	computer systems	36	1	Internet facility
7	Operating Systems Lab	B203/C	computer systems	36	1	Internet facility
8	Projects Lab	A002	computer systems	36	1	Internet facility

LIST OF PROJECT LAB

Sno	Name of the Lab	Room No	No of Projects Done
Sno	Name of the Lab	Room No	Major	Mini
1	Project Lab	A002	09	09

Expert Talks/ Guest Lectures/ Workshops

Academic year	Number of Events Organized
2024-2025	10
2023-2024	8
2022-2023	9
2021-2022	8
2020-2021	10

Industrial visit

S.no	Name of the industry visited	Date of Visit
1	L&T Metro	23-01-2019
2	BSNL Regional Telecom Training Centre	23-07-2018
3	BSNL-Regional Telecom Training Centre	23-1-2018
4	Doordarshan Kendra	11-08-2017
5	Doordarshan Kendra, Ramanthapur	06-09-2016
6	T-Hub	18-02-2017

Course file

Course File Contents

Sr. No.	Contents
1	Institute V & M , Department V&M, PEO’s, PO’s, PSO’s
2	University Syllabus
3	Course Outcomes
4	CO-PO mapping with Justification
5	Is Syllabus Changes Listed?
6	Gaps Identified during Mapping if any
7	Topics beyond syllabus
8	Evidence of (Seminar/ Guest lecture/ Workshop, etc.) conducted for fulfilment of Gap
9	Revised CO-PO Mapping if any
10	Student Customization based on previous year/ semester result
11	Student Customization based on Mid-I & Mid-II
12	Course outcome assessment sheet
13	Lecture notes
14	PPT’s, Videos (in CD), Self Learning Material
15	Web references
16	Charts
17	Assignments
18	Tutorial evidence
19	Unit wise Question bank
20	Is Gate Question bank present?
21	Mid 1- Question papers
22	Mid 1 – Question paper – Key
23	Mid 1 – Question paper – Scheme of Evaluation
24	Mid 2- Question papers
25	Mid 2 – Question paper – Key
26	Mid 2 – Question paper – Scheme of Evaluation
27	University Question papers (Last three years)
28	Remedial Classes
29	Result Analysis (After Completion of course )
30	Student Feedback Analysis
31	Lesson plan
32	Time table
33	Department Calendar
34	University Calendar
35	Attendance Register -Teacher Log updated with signature of faculty and HOD
36	Internal, Assignment Marks entry in Attendance Register
37	Sample Answer Sheets
38	Sample Assignment Sheets
39	Sample Tutorial Sheets
40	Audited by IQAC

Signature of the faculty

Sponsored Research

Sno	Name of the Faculty	Academic year	Project Title	Approximate. Cost	Sponsored Company	Status	Duration
1	Dr. Dilip Kumar Mahapatra	2015-16	Novel Recommender system model for online social voting using matrix factorization and nearest neighbor approach(Data Mining)	4.55 Lakhs	SRK Travels	Completed	1 Year
	Dr.K. Jagan Mohan
2	Dr. SaratChadraNayak	2016-17	A supervised joint topic modeling for sentiment analysis in one go(Data Mining)	5.75 Lakhs	SAK Informatics	Completed	2 Years
	A.Venugopal
3	Dr.D..Eswar	2017-18	Archiving Efficient and secure data acquisition for cloud supported internet of things in smart grid .	7.00 Lakhs	SAK Informatics	Completed	2 Years
	R.KrishnaNayak
4	Dr. Marlene Grace Verghese	2017-18	A network based spam detection framework for reviews in online social media(Inform ation forensics and security)	6.10 Lakhs	HACKBOATS	In progress	3 Years
	K. Suparna
5	Dr. D.Eshwar	2018-19	Vehicle detection and classification	7.25 Lakhs	SAK INFORMATICS	In progress	3 Years
	Dr. Marlene Grace Verghese
6	Dr. D.Eshwar	2018-19	Vehicle detection and classification	7.75 Lakhs	SAK INFORMATICS	In progress	3 Years
	Dr. Marlene Grace Verghese

Consultancy Projects : A.Y: 2015-16

Sno	Name of the Faculty	Academic year	Project Title	Approximate. Cost	Sponsored Company	Status	Duration
1	Dr.Dileep Kumar	2015-16	Content Development	4 Lakhs	HEBEON TECHNOLOGIES	Completed	1 Year
	Dr.Dileep Kumar

Consultancy Projects : A.Y: 2016-17

Sno	Name of the Faculty	Academic year	Project Title	Approximate. Cost	Sponsored Company	Status	Duration
1	Dr.k.kiran Kumar	2016-17	Design and Develop of websites, office automation	2.9 Lakhs	SRS Technologies	Completed	1 Year
	Dr.k.kiran Kumarr
2	K.Suparna		Content Development	5 Lakhs	Completed	Completed	2 Years
	K.Suparna

Consultancy Projects : A.Y: 2017-18

Sno	Name of the Faculty	Academic year	Project Title	Approximate. Cost	Sponsored Company	Status	Duration
1	Dr.Sarath Chandra Nayak	2017-18	Content Development	5.4 Lakhs	HEBEON Technologies	Completed	2 Years
	K.BalaThipuraSundari
2	A.Prakash		office automation and front office automation	4 Lakhs	MahadweeepPharma	Completed	2 Years
	R.Krishnanayak
3	A.Prakash		Bus Tracker application	6.7 Lakhs	SRK Travels	On Going	3 Years
	B.Ramesh

Consultancy Projects : A.Y: 2018-19

Sno	Name of the Faculty	Academic year	Project Title	Approximate. Cost	Sponsored Company	Status	Duration
1	Dr.Marlene Grace	2018-19	Third Party Project Development	3.85 Lakhs	Code Kindle	On Going	2 Years
	G.Saritha
2	G.Saritha		Content Development	6.95 Lakhs	Learn IT Hub	On Going	3 Years
	A.Venugopal
3	K.BalaThripurasundari		Driver Safety Index Using Integrated Computing system	8 Lakhs	SRK Travels	On Going	3 Years
	K.Suparna

Product Development

Sno	Product Development	Faculty Name	Tittle	Student 1	Student 2	Student 3	Student 4
1	2015-2016	Dr.Dilip Kumar Mahapatra	Dr.Dilip Kumar Mahapatra	Sneha ReddySneha Reddy	AnkitRai	Gayatri	Rahul Singh
2	2016-2017	K.Suparna	Rock paper scissors	K.BindhuPriya	M.Leela	Shaik AbdulSahilMajeed	Manoj Kumar
3	2016-2017	Dr.K.Kiran Kumar	Space Fighter	V. Anusha Reddy	Y. Shravya	B.Anil	B.Sravan
4	2017-2018	Dr.K.Kiran Kumar	E-Commerce Application	VikramPreek	Nawaz	Shankar	Pooja Reddy
5	2017-2018	G.Saritha	Space Fighter	CH.Rajesh	NishaKumari	G.Bhanava	Dwarakanath
6	2018-2019	Dr.D.Eshwar	Network pen testing project	Harivamshi	Lakshman	Kavitha	Anikrutha
7	2018-2019	Dr.D.Marlene Grace	Block chain real time voting	VikramPareek	Shanka	Swetha	Pranavi
8	2018-2019	Dr.D.Eshwar	A distributed publisher driven secure data sharing for information	Sushmitha	K.BindhuPriya	Ch.Samhith	Ch.Samhith

Internal Quality of Question Paper

A sample of mid semester question paper is specified below.

Academic Year: 2017-18

Scheme for Weak and Advanced Learners

The department has a well defined process of monitoring, guiding and assisting the students and to identify them as weak or bright students and providing them necessary support in improving their performance.

Process of identification of students as weak/ bright students:

Appropriate care has taken by the faculty in monitoring the performance of a student in the class, attendance, assignment, mid semester and external examination results.
The mentors regularly conduct meeting with the students and identify weak and bright students.
The mentors regularly conduct meeting with the students and identify weak and bright students.
Faculty will analyze and identify the weak students and bright students based on their previous performance before the start of the semester.
After the 3rd week of classes based on the observation and previous semester result the identification of weak and bright students will be done.

Scheme

Students who got below 60% or less than or equal to 14/25 marks in mid semester are considered as weak students, Students who scored above 72 % or more than 18/25 Marks are considered as bright students.

Contact Us

DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING,
Kommuri Pratap Reddy Institute of Technology,
Email: aimlhod@kpritech.ac.in,
Ghanpur [V], Near NTPC, Ghatkesar [M],
Medchal [D], Telangana, India. Pin: 500088.