A recent field of study called Artificial Intelligence and Data Science (AI&DS) examines how to extract knowledge from both structured and unstructured data using scientific methods, procedures, and techniques that are drawn from a variety of fields.
The department of Computer Engineering of Indira College of Engineering and Management started the course of AI & DS in the academic year 2022-2023. This is a 4-year degree course (B.E.) approved by AICTE, New Delhi under Savitribai Phule Pune University (SPPU) and the curriculum is prescribed by SPPU. The detailed course structure is highlighted in the structure section.
The Department has experienced faculty members, state-of- the-art infrastructure and all the necessary equipment’s/software’s with latest configurations.
This course's goal is to provide students with hands-on experience in AI & DS to prepare them for the workforce.
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 | |||
Mrs. Deepa Vishal Padwal
Assistant Professor
Department: Artificial Intelligence and Data Science
Qualification: ME- Computer Engineering, BE- Computer Science and Engineering
Total Experience: 5 Years
Areas of Interests: HPC, AI, CC
Research Papers: 5
Mrs. Pallavi Chavan
Assistant Professor
Department: Artificial Intelligence And Data Science
Qualification: MTech Computer Engg, BTech Computer Engg
Total Experience: 3 Years
Areas of Interests: Database,AI
Research Papers: 2
Mr. Aditya Mahasalakar
Lab Assistant
Department: Artificial Intelligence And Data Science
Qualification: MCA
Total Experience: Fresher
Areas of Interests: AI and DS, Python, Hardware and Networking
| 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)
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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