A recently emerging field known as Artificial Intelligence and Data Science (AI&DS) delves into methods, procedures, and techniques aimed at extracting insights from both structured and unstructured data, drawing upon a variety of scientific disciplines.
In the academic year 2022-2023, Indira College of Engineering and Management launched a four-year Bachelor of Engineering (B.E.) program in AI & DS, accredited by AICTE, New Delhi, and administered by Savitribai Phule Pune University (SPPU). The curriculum, outlined by SPPU, is elaborated upon in the program's structure section.
The department prides itself on its experienced faculty, contemporary infrastructure, and provision of all necessary equipment and software with the latest configurations.
The primary goal of this program is to furnish students with hands-on experience in intelligence and data engineering, preparing them for the rigors of the professional arena.
ICEM has been accredited with ‘B++’ grade by “National Accreditation and Assessment Council” (NAAC)
Second Year Course Structure
| Savitribai Phule Pune University Second Year of Artificial Intelligence and Data Science (2020 Course) (With effect from Academic Year 2021-22) |
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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Semester-III | ||||||||||||||
| Course Code | Course Name | Teaching Scheme (Hours/Week) | Examination Scheme and Marks | Credit Scheme | ||||||||||
| Lecture | Practical | Tutorial | Mid-Sem | End-Sem | Team Work | Practical | Oral | Total | Lecture | Practical | Tutorial | Total | ||
| 210241 | Discrete Mathematics | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 |
| 210242 | Fundamentals of Data Structures | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 |
| 210243 | Object Oriented Programming (OOP) | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 |
| 210244 | Computer Graphics | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 |
| 217521 | Operating System | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 |
| 210246 | Data Structures Laboratory | -- | 04 | -- | -- | -- | 25 | 50 | -- | 75 | -- | 02 | -- | 02 |
| 210247 | OOP and Computer Graphics Laboratory | -- | 04 | -- | -- | -- | 25 | 25 | -- | 50 | -- | 02 | -- | 02 |
| 217524 | Operating System Laboratory | -- | 02 | -- | -- | -- | 25 | -- | -- | 25 | -- | 01 | -- | 01 |
| 210249 | Business Communication Skills | -- | 02 | -- | -- | -- | 25 | -- | -- | 25 | -- | 01 | -- | 01 |
| 210250 | Humanity and Social Science | -- | -- | 01 | -- | -- | 25 | -- | -- | 25 | -- | -- | 01 | 01 |
| 210251 | Audit Course 3 | -- | 02 | -- | -- | -- | -- | 25 | -- | 125 | -- | 01 | -- | 01 |
| Total | 15 | 12 | 01 | 150 | 350 | 125 | 75 | -- | 700 | -- | -- | -- | -- | |
| Total Credit | 15 | 06 | 01 | 22 | ||||||||||
| Semester-IV | ||||||||||||||
| Course Code | Course Name | Teaching Scheme (Hours/Week) | Examination Scheme and Marks | Credits | ||||||||||
| Lecture | Practical | Tutorial | Mid-Sem | End-Sem | Team Work | Practical | Oral | Total | Lecture | Practical | Tutorial | Total | ||
| 217528 | Statistics | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 |
| 217529 | Internet of Things | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 |
| 210252 | Data Structures and Algorithms | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 |
| 210253 | Software Engineering | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 |
| 217530 | Management Information System | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 |
| 217531 | Internet of Things Laboratory | -- | 04 | -- | -- | -- | 50 | 25 | -- | 75 | -- | 02 | -- | 02 |
| 217532 | Data Structures and Algorithms Laboratory | -- | 04 | -- | -- | -- | 25 | 25 | -- | 50 | -- | 02 | -- | 02 |
| 210258 | Project Based Learning II | -- | 04 | -- | -- | -- | 50 | -- | -- | 50 | -- | 02 | -- | 02 |
| 210259 | Code of Conduct | -- | -- | 01 | -- | -- | 25 | -- | -- | 25 | -- | -- | 01 | 01 |
| 210260 | Audit Course 4 | |||||||||||||
| Total | 15 | 12 | 01 | 150 | 350 | 150 | 50 | -- | 700 | -- | -- | -- | -- | |
| Total Credit | 15 | 06 | 01 | 22 | ||||||||||
Abbreviations= TW:Term Work ,TH: Theory ,OR: Oral ,TUT: Tutorial, PR: Practical ,Sem: Semester
Third Year Course Structure
| Savitribai Phule Pune University Third Year of Artificial Intelligence and Data Science (2020 Course) (With effect from Academic Year 2021-22) |
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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Semester V | ||||||||||||||
| Course Code | Course Name | Teaching Scheme (Hours/Week) | Examination Scheme and Marks | Credit Scheme | ||||||||||
| Lecture | Practical | Tutorial | Mid-Sem | End-Sem | Team Work | Practical | Oral | Total | Lecture | Practical | Tutorial | Total | ||
| Data Science | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Computer Networks | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Artificial Intelligence | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Cyber security | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Elective I | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Software Laboratory I (Data Science & Al) | -- | 04 | -- | -- | -- | 25 | 25 | -- | 50 | -- | 02 | -- | 02 | |
| CN Laboratory | -- | 02 | -- | -- | -- | 25 | 25 | -- | 50 | -- | 01 | -- | 01 | |
| Elective I Laboratory | -- | 02 | -- | -- | -- | 25 | -- | 25 | 50 | -- | 01 | -- | 01 | |
| Seminar I | -- | -- | 01 | -- | -- | 25 | -- | -- | 25 | -- | -- | 01 | 01 | |
| Environmental Studies | -- | -- | 01 | -- | -- | 25 | -- | -- | 25 | -- | -- | 01 | 01 | |
| Total | 15 | 08 | 02 | 150 | 350 | 125 | 50 | 25 | 700 | 15 | 04 | 02 | 21 | |
| Audit Course 5 | Grade | |||||||||||||
| Total Credit | 15 | 06 | 01 | 21 | ||||||||||
| Total | 15 | 12 | 01 | 150 | 350 | 125 | 50 | 25 | 700 | -- | -- | -- | -- | |
| Savitribai Phule Pune University Third Year of Artificial Intelligence and Data Science (2020 Course) (With effect from Academic Year 2021-22) |
||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Semester VI | ||||||||||||||
| Course Code | Course Name | Teaching Scheme (Hours/Week) | Examination Scheme and Marks | Credit Scheme | ||||||||||
| Lecture | Practical | Tutorial | Mid-Sem | End-Sem | Team Work | Practical | Oral | Total | Lecture | Practical | Tutorial | Total | ||
| Data Warehousing & Mining | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Web Technology | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Neural Networks & Fuzzy Logic | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Elective II | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Software Laboratory II (Neural Networks & Fuzzy Logic and Web Technology) | -- | 04 | -- | -- | -- | 50 | 25 | -- | 75 | -- | 02 | -- | 02 | |
| Software Lab III (DWM &Elective II) | -- | 04 | -- | -- | -- | 50 | 25 | -- | 75 | -- | 02 | -- | 02 | |
| Internship | -- | 08 | -- | -- | -- | 50 | -- | 50 | 100 | -- | 04 | -- | 04 | |
| Seminar II | -- | -- | 01 | -- | -- | 25 | -- | 25 | 50 | -- | -- | 01 | 01 | |
| Total | 12 | 18 | 01 | 120 | 280 | 175 | 50 | 75 | 700 | 12 | 08 | 01 | 21 | |
| Audit Course 6 | ||||||||||||||
| Total Credit | 12 | 08 | 01 | 21 | ||||||||||
Final Year Course Structure
| Savitribai Phule Pune University Forth Year of Artificial Intelligence and Data Science (2020 Course) (With effect from Academic Year 2021-22) |
||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Semester VII | ||||||||||||||
| Course Code | Course Name | Teaching Scheme (Hours/Week) | Examination Scheme and Marks | Credit Scheme | ||||||||||
| Lecture | Practical | Tutorial | Mid-Sem | End-Sem | Team Work | Practical | Oral | Total | Lecture | Practical | Tutorial | Total | ||
| Machine Learning | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Data Modeling & Visualization | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Elective III | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Elective IV | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Computer Laboratory I | -- | 04 | -- | -- | -- | 50 | 25 | -- | 75 | -- | 02 | -- | 02 | |
| Computer Laboratory II | -- | 04 | -- | -- | -- | 50 | 25 | -- | 75 | -- | 02 | -- | 02 | |
| Project Stage l | -- | 04 | -- | -- | -- | 50 | -- | 50 | 100 | -- | 02 | -- | 02 | |
| MOOC | 02 | 50 | 50 | 02 | 02 | |||||||||
| Audit Course 7 | = | |||||||||||||
| Total Credit | 12 | 06 | 02 | 20 | ||||||||||
| Savitribai Phule Pune University Forth Year of Artificial Intelligence and Data Science (2020 Course) (With effect from Academic Year 2021-22) |
||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Semester VIII | ||||||||||||||
| Course Code | Course Name | Teaching Scheme (Hours/Week) | Examination Scheme and Marks | Credit Scheme | ||||||||||
| Lecture | Practical | Tutorial | Mid-Sem | End-Sem | Team Work | Practical | Oral | Total | Lecture | Practical | Tutorial | Total | ||
| Computational Intelligence | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Distributed Computing | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Elective V | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Elective VI | 03 | -- | -- | 30 | 70 | -- | -- | -- | 100 | 03 | -- | -- | 03 | |
| Computer Laboratory III | -- | 02 | -- | -- | -- | 50 | 25 | -- | 75 | -- | 01 | -- | 01 | |
| Computer Laboratory IV | -- | 02 | -- | -- | -- | 50 | 25 | -- | 75 | -- | 01 | -- | 01 | |
| Project II | -- | 12 | -- | -- | -- | 100 | -- | 50 | 150 | -- | 06 | -- | 06 | |
| Total | 12 | 16 | -- | 120 | 280 | 200 | 50 | 50 | 700 | 12 | 08 | 20 | ||
| Audit Course 8 | ||||||||||||||
| Total Credit | 12 | 05 | 02 | 20 | ||||||||||
ICEM has been accredited with ‘B++’ grade by “National Accreditation and Assessment Council” (NAAC)
| Sr. No. | Lab Name | Total PCs | Configuratione | Software Installed |
|---|---|---|---|---|
| 1 | Programming Lab | 37 | Lenovo Think Station, Core i7, 7th Generation, 8 GB RAM, 1TB HDD, 19.5’ LED MONITOR & Lenovo, Intel Core i5 8400 processor, 8 GB RAM, 1TB HDD, 19.5’ LED MONITOR | UBUNTU OS : Python,g++, Lamp Server(apache, mysql, php), Netbeans, Eclipse, JDK, flex, yacc, sbcl, nasm, TASM,Umbrello,QTCreator,samba |
| 2 | Artificial Intelligence and Research Lab | 31 | Lenovo Think Station & Centre, Core i7, 7th Generation, 8 GB RAM, 1TB HDD, 19.5’ LED MONITOR | UBUNTU OS : g++, Lamp Server(apache, mysql, php), Netbeans, Eclipse, JDK, flex, yacc, sbcl, nasm, TASM,Umbrello,Oracle,,samba, Packet Tracer,NS2 |
| 3 | Operating system and Networking Lab | 20 | HCL, Infinity BL 1330 Intel G41, Intel C2D E-7500.2.93 GHz Processor, 2 GB RAM DDR3, 320 GB HDD, 18.5' INCH HCL MONITOR | UBUNTU OS : JDK,g++, Netbeans, Eclipse, flex, yacc, sbcl, nasm, TASM,Wireshark, Packet Tracer |
| 4 | Project Lab | 22 | HCL, Infinity BL 1330 Intel G41, Intel C2D E-7500.2.93 GHz Processor, 2 GB RAM DDR3, 320 GB HDD, 18.5' INCH HCL MONITOR | UBUNTU OS : Eclipse,g++, Netbeans, JDK, flex, yacc, sbcl, nasm, TASM |
| 5 | Database Management System Lab | 39 | Lenovo Think Centre, Core i7, 7th Generation, 8 GB RAM, 1TB HDD, 19.5’ LED MONITOR & HCL, Infinity BL 1330 Intel G41, Intel C2D E-7500.2.93 GHz Processor, 2 GB RAM DDR3, 320 GB HDD, 18.5' INCH HCL MONITOR | UBUNTU OS : Python,g++, Lamp Server(apache, mysql, php), Netbeans, Eclipse, JDK, flex, yacc, sbcl, nasm, TASM,Umbrello,Oracle,samba, Packet Tracer,NS2 |
| Total PCs | 149 | |||
ICEM has been accredited with ‘B++’ grade by “National Accreditation and Assessment Council” (NAAC)
Department:Artificial Intelligence and Data Science
Qualification: Ph.D. Computer Science and Engineering
Area Of Interest: Machine Learning, Security, Artificial Intelligence, Data Analytics
Total Experience In Years: 22.8 yrs
Research :10
Research Papers: Scopus indexed: 7 ,Journal papers: 30, Conference papers: 20+
Artificial Intelligence and Data Science
Qualification: M.E. (Computer Engineering)
Subject: Artificial Intelligence, Machine Learning
Area Of Interest: High Performance Computing, Artificial Intelligence, Cyber Security, NLP
Total Experience In Years: 6 yrs, Industrial: 0.8
Research :2
Research Papers: Journal papers: 7, Conference papers: 4
Artificial Intelligence And Data Science
Qualification: Pursing Phd (Computer Engineering) M.Tech (Computer Engineering)
Area Of Interest: Data Science, Artificial Intelligence, Machine Learning
Total Experience In Years: 4 years, Industrial:1 year
Research :0.5
Research Papers: Journal papers: 7, Conference papers: 4
Artificial Intelligence And Data Science
Qualification: Pursing Phd (Computer Engineering) M.Tech (Computer Engineering)
Area Of Interest: Data Science, Artificial Intelligence, Machine Learning, Image Processing
Total Experience In Years: 7 years, Industrial:1 year
Research :2.5
Research Papers: Journal papers: 2, Conference papers: 5
Artificial Intelligence And Data Science
Qualification: M.E. (Information Technology)
Area Of Interest: Data Science, Cloud Computing, Image Processing
Total Experience In Years: 6 years, Industrial:0.6 year
Research :1
Research Papers: Journal papers: 4, Conference papers: 2
Artificial Intelligence And Data Science
Qualification: M.E E&TC(CN)
Area Of Interest: Communication Network, Logic Design, Digital Electronics
Total Experience In Years: 7 years
Research :
Research Papers:
| Category | Scholarship Eligibility | Nature of Scholarship |
| ST/SC/Neo-Buddhist/VJNT | · For SC/ST- No income limit, · For others income < 8.00 Lacs | Tuition Fee and Exam Fees |
| SBC | Parent’s annual income < 8.00 Lacs. | Tuition Fee and Exam Fees |
| OBC | Parent’s annual income < 8.00 Lacs. | 50 % of Tuition and Exam Fee |
| EBC | · EBC students admitted through (CAP) · Parent’s annual income < 8.00 Lacs. | 50 % of Tuition and Exam Fee |
| Dr. Panjabrao Deshmukh (Hostel Scheme) | Students whose parents are certified as a marginal farmer or whose parents are registered laborers. | · For child of Registered Labor / Alpabhudharak (Marginal Land Holder). - For institute in MMRDA - Rs.30,000/- for 10 months. · For Annual Family income up to 8 Lakhs. - For institute in MMRDA- Rs.10,000/- for 10 months. |
| Minority Communities (Muslim, Buddhist, Christian, Sikh, Parsi, Jain & Jews Community)- | Parent’s annual income < 8.00 Lacs. | Scholarship Amount Maximum Rs.25,000/- Per Annum or Actual Tuition Fees whichever is less |
| TFWS | parent’s annual income less than Rs. 8 Lakh | Waiver is limited to the tuition fee |
| Indira Scholar Scholarship | Applicable to Meritorious students of Civil and Mechanical only (For First year and DSE students) | Please Contact: Prof. Ashwin Dharme 9764408057 |
ICEM has been accredited with ‘B++’ grade by “National Accreditation and Assessment Council” (NAAC)
The event aimed to provide a warm welcome to the new students and create an atmosphere of camaraderie within the college community for Second Year Artificial Intelligence and Data Science Students. The program was organized by Department of Artificial Intelligence and Data Science students.
The Tech Fest held at ICEM was a dynamic showcase of innovation, creativity, and collaboration. It provided a platform for students to demonstrate their technical prowess, explore emerging technologies, and engage in meaningful interactions.
ICEM has been accredited with ‘B++’ grade by “National Accreditation and Assessment Council” (NAAC)
Date: 07/01/2025
An enriching session on “Project Based Learning and its importance” is organized by Department of Artificial Intelligence and Data Science and it was conducted by Dr. Nilesh Uke, Principal - ICEM, focusing on the transformative power of project-based learning.
Students explored real-world problem-solving while gaining hands-on experience with advanced tools and technologies. Dr. Uke’s expert insights showcased how AI and data science are reshaping industries, inspiring critical thinking and innovation.
Date: 09/01/2025
Department of Artificial Intelligence and Data Science (AI and DS) celebrated National Youth Day on January 10, 2025, as part of an activity under the Institute's Innovation Cell. The event was designed to honor the ideals of Swami Vivekananda and inspire the youth through innovative and engaging activities.
Date: 11/01/2025
The Department of AI and Data Science organized Sports Activities: Cricket and Carrom on 11th January 2025 for 60+ students. The event provided an opportunity for students to engage in physical fitness, teamwork, and strategic games, promoting overall well-being and social interaction through friendly cricket matches and a carrom tournament.
Date: 17/02/2025
The Department of Artificial Intelligence and Data Science successfully conducted the Tech Fest "DhurvaTech 2024" on 17th February 2025, The event witnessed enthusiastic participation from over 100 students, who took part in two main activities—Technova (AI Creativity) and Code Hustle. Participants were provided with a platform to showcase their creativity using AI tools and demonstrate their technical and problem-solving skills through coding challenges. The event concluded with a Prize Distribution Ceremony, recognizing the winners for their innovation and excellence.
ICEM has been accredited with ‘B++’ grade by “National Accreditation and Assessment Council” (NAAC)
Date(09/02/24) "Learn, grow, and be amazed during an exposure visit!" Students of SE AI and DS visited to Top Harnesses Pvt.Ltd. - a Wiring Harnesses Manufacturer as an exposure visit to pre-incubation unit. Mr. Mahesh Mahajan (MMS, DBM, DME, DMM), the Founder of Top Harnesses Pvt. Ltd. guided all the students with his inspiring speech. Along with his qualified executives committed towards delivering quality services and seeking opportunities in the challenges.
ICEM has been accredited with ‘B++’ grade by “National Accreditation and Assessment Council” (NAAC)
ICEM has been accredited with ‘B++’ grade by “National Accreditation and Assessment Council” (NAAC)
ICEM has a wonderful group of faculties who have a great bonding with students and parents. Various good companies come to college for campus interview, placement is also good. College has very nice environment. Thanks ICEM for the great opportunity. There's a lot that I learned when I was working in the placement cell.
Role of placement cell in my campus selection: First of all, I must thank one of the most active & helpful groups of ICEM - Placement cell. Placement cell played vital role in our preparation for the interviews, GDs & soft skills development. Interviews are to be faced with full confidence & that key to the success is taught through various activities held by placement cell in ICEM.
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