Society for Computer Technology & Research’s (SCTR’s)
Pune Institute of Computer Technology (PICT), Pune
An Autonomous Institute affiliated to the Savitribai Phule Pune University
(SPPU)
Approved by AICTE & Government of Maharashtra,
Accredited by NAAC (A+) & NBA [All eligible UG Programs]
Syllabus Structure for
T.Y B. Tech Electronics and Computer
Engineering (E&CE)
(A.Y. 2026-2027 onwards) *
With effect from (June 25)
National Education Policy (NEP) 2020 Compliant
*Approved by the Board of Studies (BoS) and Academic Council
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Abbreviations used (Refer [1-3] for more details)
Sr. Broad Category of Sub- Category of course Category
No. the course Code
Basic Science/ Basic Science Course (BSC) 01
I. Engineering Science 02
Course (BSC/ ESC) Engineering Science Course (ESC)
Program Courses Program Core Course (PCC) 03
II.
(PC) Program Elective Course (PEC) 04
Multidisciplinary Multidisciplinary Minor (MDM) 05
III.
Courses (MC) Open Elective (OE) Other than particular program 06
IV. Skill Courses (SC) Vocational and Skill Enhancement Course (VSEC) 07
Ability Enhancement Course (AEC-01, AEC-02) 08
Humanities Social
Entrepreneurship/Economics/ Management Courses (EEM) 09
Science and
V. 10
Management Indian Knowledge System (IKS)
(HSSM) Value Education Course (VEC) 11
Research Methodology (RM) 12
Experiential Community Engagement Project (CEP) / Field Project (FP) 13
VI. Learning Courses 14
(ELC) Project (PRJ)
Internship/ On Job Training (IP/OJT) 15
VII. Liberal Learning 16
Co-curricular Activities (CCA)
Courses (LLC)
Detailed guidelines for General Instructions:
Link: General Instructions
Detailed guidelines for Evaluation and Assessment:
Link: Guidelines for Evaluation and Assessment
Detailed guidelines for examination:
Link: Guidelines for examination
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Index
Contents
Index.................................................................................................................................................................. 3
T.Y B. Tech Syllabus Structure ...................................................................................................................... 4
Annexures ......................................................................................................................................................... 6
Annexure-I........................................................................................................................................................ 7
Structure of Multi-Disciplinary Minor Courses ....................................................................................... 7
Lis of Multi-Disciplinary Minor Domains ................................................................................................. 8
Annexure -II ..................................................................................................................................................... 9
Guidelines for Open elective Courses ........................................................................................................ 9
Guidelines for MOOCs................................................................................................................................ 9
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T.Y B. Tech Syllabus Structure
Semester – V
Teaching Scheme
Semester -5 Credit scheme Examination/ Evaluation Scheme and Marks
(Hours/Week)
Category Theory Practical
Course
of ISE CIE ESE CIE ESE Total
code Name of the Course L P T Total L P T Total
Course
[20] [20] [60] TW P OR
Computer Networks
PCC 5503111 3 - - 3 3 - - 3 20 20 60 - - - 100
(CN)
Computer Networks Lab
PCC 5503212 - 2 - 2 - 1 - 1 - - - - - 25 25
(CNL)
Database Management
PCC 5503113 3 - - 3 3 - - 3 20 20 60 - - - 100
System (DBMS)
Database Management
PCC 5503214 - 2 - 2 - 1 - 1 - - - - 50 - 50
System Lab (DBMSL)
PCC 5503115 Embedded System (ES) 2 - - 2 2 - - 2 20 20 60 - - - 100
Embedded System lab
PCC 5503216 - 2 - 2 - 1 - 1 - - - - 25 - 25
(ESL)
MDM 05051X3 MDM 3 2 - - 2 2 - - 2 20 20 60 - - - 100
MDM 05052X3 MDM 3 Lab - 2 - 2 - 1 - 1 - - - 25 - - 25
PEC 55041X1 Program Elective-I 2 - - 2 2 - - 2 20 20 60 - - - 100
PEC 55042X1 Program Elective-I Lab - 2 - 2 - 1 - 1 - - - 25 - 25 50
Leadership and
AEC 0508204 Management Skills - 2 - 2 - 1 - 1 - - - 25 - - 25
(LMS)
OE 05063XX Open Elective-3 * - - 2 2 - - 2 2 - - 50 - - - 50
Total 12 12 2 26 12 6 2 20 100 100 350 75 75 50 750
#: Tutorial or laboratory as applicable. MDLX-X: First X is basket number; Second X is course number in that basket, L, P, and T has usual meaning.
Refer annexture-1 for MDM details.
*: Open elective (OE) offered by online platform such as SWAYAM/NPTEL, Refer Annexture-II for details.
Program Elective Courses-I (PEC-1)
Domain Name Course Code Course name
Electronics (E) 5504111 Mechatronics (MECHX) and Lab
Computers (C) 5504121 Web Development and Lab
Emerging Trends (ET) 5504131 Micro Electro Mechanical System (MEMS) and Lab
Advance Data Science (ADS) 5504141 Big Data Analytics (BDA) and Lab
Cyber Security (CS) 5504151 Security and Privacy (SP) and Lab
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T.Y. B. Tech, Semester - VI
Teaching Scheme
Semester-6 (Hours/Week) Credit scheme Examination/ Evaluation Scheme and Marks
Category Theory Practical
Course ISE CIE ESE CIE ESE
of Name of the Course Total
code L P T Total L P T Total
Course [20] [20] [60] TW P OR
PCC 5603117 Theory of Computation (ToC) 2 - 1 3 2 - 1 3 20 20 60 25 - - 125
Design and Analysis of
PCC 5603118 3 - - 3 3 - - 3 20 20 60 - - - 100
Algorithm (DAA)
Design and Analysis of
PCC 5603219 - 2 - 2 - 1 - 1 - - - - 50 - 50
Algorithm Lab (DAAL)
PCC 5603120 Internet of Things (IoT) 2 - - 2 2 - - 2 20 20 60 - - - 100
PCC 5603221 Internet of Things Lab (IoTL) - 2 - 2 - 1 - 1 - - - - - 25 25
MDM 06051X4 MDM 4 2 - - 2 2 - - 2 20 20 60 - - - 100
MDM 06052X4 MDM 4 Lab - 2 - 2 - 1 - 1 - - - 25 - - 25
VSEC 5607202 Mini project/seminar - 4 - 4 - 2 - 2 - - - - - 50 50
PEC 56041X2 Program Elective-II 2 - - 2 2 - - 2 20 20 60 - - - 100
PEC 56042X2 Program Elective-II Lab - 2 - 2 - 1 - 1 - - - 25 - - 25
OE 06063XX Open Elective-4 * - - 2 2 - - 2 2 - - 50 - - - 50
Total 11 12 3 26 11 6 3 20 100 100 350 100 75 75 750
Program Elective Courses-II (PEC-II)
Domain Name Course Code Course name
Electronics (E) 5604112 Sensors and Actuators (SA)
Computers (C) 5604122 Compiler Construction (CC)
Emerging Trends (ET) 5604132 Augmented and Virtual Reality (AVR)
Advance Data Science (ADS) 5604142 Generative AI (GAI)
Cyber Security (CS) 5604152 Computer Forensic and Data Recovery (CFDR)
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Annexures
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Annexure-I
Structure of Multi-Disciplinary Minor Courses
The structure for the multidisciplinary Minor courses is as follows.
Teaching
Scheme Credits Examination Scheme and Marks
(Hours/Week)
Course Name of Total
Sem code Course L P T Total L P T Theory Practical
credits Semester
CIE ISE ESE CIE ESE Total
[20] [20] [60] TW P OR 550
3 03051X1 MDM-1 2 - - 2 2 - - 2 20 20 60 - - - 100
3 03052X1 MDM-1 # - 2 - 2 - 1 - 1 - - - - - 25 25
4 04051X2 MDM-2 2 - - 2 2 - - 2 20 20 60 - - - 100
4 04052X2 MDM-2 # - 2 - 2 - 1 - 1 - - - 25 - - 25
5 05051X3 MDM-3 2 - - 2 2 - - 2 20 20 60 - - - 100
5 05052X3 MDM-3 # - 2 - 2 - 1 - 1 - - - 25 - - 25
6 06051X4 MDM-4 2 - - 2 2 - - 2 20 20 60 - - - 100
6 06052X4 MDM-4 # - 2 - 2 - 1 - 1 - - - 25 - - 25
8 08053X5 MDM-5 - - 2 2 - - 2 2 - - - 50 - - 50
Total 8 8 2 18 8 4 2 14 80 80 240 125 0 25 550
Note: In course code X is basket number. #: is laboratory or tutorial as per course requirements.
1. Students are expected to choose one of the eligible domains of MDM at the beginning of the Semester III.
2. Students will complete the chosen set of all multidisciplinary minor courses mentioned under the chosen
MDM domain.
3. Students are not permitted to change from one domain to another.
4. Refer to the last column of following table for eligibility to choose a particular MDM domain.
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Lis of Multi-Disciplinary Minor Domains
Label Multi-Disciplinary SY TY B-Tech Offered to
Minor Domains students of
MD1-1 MD2-2 MD3-3 MD4-4 MD5-5
B Tech
Program
Sem-III Sem-IV Sem-V Sem-VI Sem-VII/VIII
MD1 Smart and Sustainable Fundamentals of Smart IoT for Smart and Data Analytics for Smart Security for Smart and Smart and Sustainable ALL
Systems (SSS) and Sustainable Sustainable Systems and Sustainable Systems Sustainable Systems System Development
Systems (FSSS) & Tut (ISSS) & Lab (DASSS) & Lab (SSS&S) (SSD)
Smart and Sustainable
System Development
(SSD) Lab
MD2 Finance and Fundamentals of Banking, Financial Fundamentals of Stock Fintech: Foundations & Financial Derivatives & ALL
Management (F&M) Financial Engineering Services and Insurance Market (FSM) &Tut Applications (FFA) &Tut Risk Management
(FFE) & Tut (BFSI) &Tut (FDRM)
MD3 3D- Printing (3DP) 3D modeling and Fundamentals of 3D Printing Materials and Industry 4.0 and Digital Applied 3D Printing and ALL
Design (3MD) & Lab Additive Manufacturing Processes (3DPMP) Manufacturing (IDM) Prototyping Lab
(FAM)& Lab (A3DPPL)
MD4 Electric Vehicles (EV) EV foundation – Advanced Motor EV Powertrain Dynamics Intelligent EV Systems: AI Capstone Project in ALL
Principles and Technologies and Power and Control System (PDC) IoT and Automation (IEV) Electric Mobility
Concepts (EVPC) & Electronics for Tut/Lab
Lab EV(AMT) & Lab
MD5 Applied Mathematics Linear Algebra with Statistical Techniques Fuzzy Logic and Graph Optimization Techniques Field Study/Case Study ALL
for Engineering Python & Lab and Numerical Methods Theory with Matlab/Python & Lab
(AME) with R & Lab & Lab
MD6 Software Development Data Structures and Object Oriented Database and Management Web Development (WD) System Programming and Only
(SD) Algorithms (DSA) & Programming (OOP) Systems (DBMS) & Lab & Lab Operating System (SPOS) E&TCE
Lab &Lab
MD7 Autonomous and Digital Systems and Smart System Embedded IoT Systems Autonomous Systems Cyber Physical Systems: All except
Intelligent Systems Organization (DSO) & Engineering (SSE) & (EIS) & Lab (AS) & Lab Screen Mode (CPS) / E&TCE
(AIS) Lab Lab Capstone Project
MD8 Embedded Systems Fundamental of Embedded Processors –I Microcontrollers and IoT Embedded Systems and Capstone Project using All Except
(ES) Microcontroller (FM) (EP -I) & Lab (MI) & Lab RTOS (ES-RTOS) & Lab Microcontrollers lab E&TCE
& Lab (CPML)
MD9 AI & Machine Statistical Data Machine Learning (ML) Natural Language Artificial Intelligence (AI) Deep Learning (DL) Only
Learning (AI-ML) Analysis & Lab & Lab Processing (NLP) & Lab & Lab E&CE
Link: Detailed Syllabus
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Annexure -II
Guidelines for Open elective Courses
1. Open Elective – I will be offered in third semester as foreign language as prescribed in the structure.
2. Open Electives – II, III, IV will be offered through SWAYAM/NPTEL MOOCs of Equivalent Credits.
3. Departments shall prepare the baskets of open elective courses from discipline/faculty other than respective
major programs. Students may choose any course from the basket without adhering to any one stream.
4. Credits & Grade will be awarded based on the Marks Obtained through the certification including assignments
and proctored examination as per the MOOCs Policy.
Teaching Credits Examination Scheme and Marks
Scheme
(Hours/Week)
Sem Course Name of the Theory Practical Total
code Course L P T Total L P T Total CIE ISE ESE CIE ESE
[20] [20] [60] TW P OR
3 OE-I Foreign - - 2 2 - - 2 2 - - - 50 - - 50
Language
Studies
(FLS)
4 OE-II MOOCs - - 2 2 - - 2 2 50 - - - 50
5 OE-III MOOCs - - 2 2 - - 2 2 - - 50 - - - 50
6 OE-IV MOOCs - - 2 2 - - 2 2 - - 50 - - - 50
Guidelines for MOOCs
1. The department shall release a list of approved SWAYAM-NPTEL courses before the
commencement of every semester.
2. Students shall register for the approved Courses as per the schedule announced by
SWAYAM-NPTEL.
3. A student shall undergo the courses only from the list notified by the department through
SWAYAM/NPTEL platform and complete all the assignments and examination
requirements as specified by SWAYAM/NPTEL.
4. SWAYAM-NPTEL Courses are considered for transfer of credits only if the student
concerned has successfully completed and obtained the SWAYAM-NPTEL Certificate.
5. The credit equivalence for SWAYAM-NPTEL Courses: 12 weeks – 3credits; 8 weeks – 2
credits; 4 weeks – 1 credit.
6. Equivalent marks will be considered for awarding the grades as specified in examination
rules and regulations. The weightage for assignments is 40%, while the weightage for the
proctored examination will be 60% for award calculating SGPA/CGPA. Students must
score a minimum of 40% of the total marks by combining both assignments and proctored
examinations
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7. A student must submit the original SWAYAM-NPTEL Course Certificates to the Head of
the Department concerned, with a written request for the transfer of the equivalent credits.
On verification of the SWAYAM-NPTEL Course Certificates and approval by the head of
the department, credits will be awarded.
8. The Institute shall not reimburse any fees/expenses a student may incur for the SWAYAM-
NPTEL Courses.
9. If the SWAYAM/NPTEL course calendar does not align with the institute’s calendar, the
department shall facilitate and conduct examination of the relevant course of equivalent
credits in physical/virtual mode and award the credits accordingly.
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