6th Semester Is Here — The Final Semester
The 6th semester is the final semester of the diploma — and it is dominated by one thing: the In House Project, worth 400 marks and 12 credits. It is the project you build yourself, bringing together everything you learned in three years: programming, databases, web technologies, networks and more. Around it sit two choices — a Program Elective-4 and an Open Elective-3 — plus Entrepreneurship and Start-ups, and SCA.
There is also a completely different way to do this semester: the Industrial Pathway — one semester of industrial training (not less than 14 weeks) worth the same 20 credits and 650 marks, with Entrepreneurship online, Industrial Hands On Practice, an Industrial Project and a Seminar. Whichever route you take, this is the semester that decides how you leave the polytechnic — with a project, a report and a viva behind you.
6th Semester At A Glance — The Full Picture
A total of 650 marks and 20 credits. The In House Project is 400 marks and 12 credits — more than half the semester. Program Elective-4 (Artificial Intelligence or Data Science and Machine Learning) is 100 marks and 4 credits, Entrepreneurship and Start-ups is 100 marks and 2 credits, and SCA adds 50 marks. Open Elective-3 (Disaster Management or Renewable Energy Technologies) is 50 marks internal only and is not counted in the total.
| Code | Subject | Type | Credits | Marks |
|---|---|---|---|---|
| 6.1 | Program Elective-4: Fundamentals of Artificial Intelligence | Theory | 4 | 100 |
| 6.1 | Program Elective-4: Data Science and Machine Learning | Theory | 4 | 100 |
| 6.2 | Entrepreneurship and Start-ups | Theory | 2 | 100 |
| 6.3 | In House Project | Project | 12 | 400 |
| 6.4 | Open Elective-3: Disaster Management | Theory | 2 | 50* (Q) |
| 6.4 | Open Elective-3: Renewable Energy Technologies | Theory | 2 | 50* (Q) |
| — | Student Centred Activities (SCA) | Activity | — | 50 |
| Total (6th Semester) | 20 | 650 marks | ||
Note: * Open Elective-3's 50 internal marks are qualifying — you must appear and pass, but they are not counted in the 650-mark total. Internal total 370 = Theory 80 (6.1 40 + 6.2 40) + Practical 290 (6.3 240 + SCA 50); External total 280 = Theory 120 (6.1 60 + 6.2 60) + Practical 160 (6.3).
What You Study In Each Subject — In Simple Words
1. Program Elective-4 (Theory)
To let students specialise in one of two directions — artificial intelligence, or data science and machine learning — through a single 4-credit theory elective examined for 100 marks.
2. Entrepreneurship and Start-ups (Theory)
Explore the objectives of Entrepreneurship, including innovation, wealth creation, and societal impact, and learn how entrepreneurs foster economic growth. Entrepreneurship drives the economy and is fundamental to all innovation and development.
3. In House Project (Project)
In House Project Work aims at developing innovative skills in the students whereby they apply in totality the knowledge and skills gained through the course work in the solution of a particular problem or by undertaking a project.
4. Open Elective-3 (Theory, Qualifying)
To let students take one qualifying open elective — disaster management or renewable energy technologies — or an Advance Skill Development certification course in its place, with 50 internal marks that do not count towards the semester percentage or division.
The Project — 400 Marks, And An Industrial Alternative
The In House Project is the biggest single subject of the whole diploma — 400 marks and 12 credits, more than half of the 6th semester. It is where you apply, in totality, the knowledge and skills you have gained through the course work: programming, databases, web technologies, networks and everything else, brought together to solve one real problem or build one working project.
There is no fixed syllabus of units to memorise here. You identify the type of project you would like to execute — a customer-based application, a dynamic website, a database application or a software product — at least two to three months in advance, and a teacher guides your work. Projects done in collaboration with industry are preferred, and each teacher guides 5–6 students.
The Industrial Pathway — An Alternative To The Classroom Route
Instead of the Normal Pathway, a student may take the Industrial Pathway (also 650 marks, 20 credits): 6.1 Entrepreneurship and Start-ups (Online) — 100 marks; 6.2 Industrial Hands On Practice — 350 marks (150 by faculty mentor + 200 by industry); 6.3 Industrial Project — 100 marks (50 by faculty mentor + 50 by industry); 6.4 Seminar — 100 marks. The industrial training tenure should not be less than 14 weeks, the industry must be registered with MSME / Directorate of Industries / a Limited Organisation / State or Central Government establishments, and monthly progress reports of the intern/trainee should be attested and forwarded by the industrial supervisor during the internship/training.
How To Prepare For The 6th Semester — A Practical Approach
Treat the project as a weekly habit, not a last-month panic: identify your project type at least two to three months in advance, and keep the work growing from the first week, because it is worth more than half the semester. Choose your Program Elective-4 by the work you want to do — Artificial Intelligence if you like algorithms, logic and intelligent systems, Data Science and Machine Learning if you like data and models that learn. And if you are considering the Industrial Pathway, arrange it early: the training must be not less than 14 weeks, the industry must be registered, and a faculty mentor must be deputed.
Complete Syllabus
The full examination scheme for the 6th semester, with lecture and practical hours and internal and external marks, followed by the unit-wise topics and the reference books of every subject.
Examination Scheme — Full Detail
| Code | Paper | Type | L – P | Credits | Internal | External | Total |
|---|---|---|---|---|---|---|---|
| 6.1 | Program Elective-4 (choose ONE of 6.1.1 / 6.1.2) | Theory | 4 – 0 | 4 | Theory 40 | Theory 60 (3 hrs) | 100 |
| 6.2 | Entrepreneurship and Start-ups | Theory (Humanities) | 2 – 0 | 2 | Theory 40 | Theory 60 (3 hrs) | 100 |
| 6.3 | In House Project | Project | 4 – 16 | 12 | Internal 240 | Practical 160 | 400 |
| 6.4 | Open Elective-3 (choose ONE of 6.4.1 / 6.4.2) OR Advance Skill Development | Theory | 2 – 0 | 2 | 50 | — | — (Q) |
| — | Student Centred Activities (SCA) | Activity | — | — | 50 | — | 50 |
| Total (6th Semester) | 20 | 370 | 280 | 650 | |||
Note: * Open Elective-3's 50 internal marks are qualifying — you must appear and pass, but they are not counted in the 650-mark total. Internal total 370 = Theory 80 (6.1 40 + 6.2 40) + Practical 290 (6.3 240 + SCA 50); External total 280 = Theory 120 (6.1 60 + 6.2 60) + Practical 160 (6.3).
Program Elective-4
6.1.1 — Fundamentals of Artificial Intelligence
Units at a Glance
| Unit | Topic | Periods | Marks Share |
|---|---|---|---|
| 1 | Introduction | 8 | 20% |
| 2 | Searching | 8 | 20% |
| 3 | Finding Optimal Paths, Problem Decomposition and Game Playing | 10 | 20% |
| 4 | Planning and Constraint Satisfaction | 8 | 20% |
| 5 | Logic and Inferences | 8 | 20% |
Reference Books
As listed in the syllabus:
- Deepak Khemani. A First Course in Artificial Intelligence, McGraw Hill Education (India).
- https://nptel.ac.in/courses/106106126/
- Stefan Edelkamp and Stefan Schroedl. Heuristic Search, Morgan Kaufmann.
- Pamela McCorduck, Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence, A K Peters/CRC Press.
- Elaine Rich and Kevin Knight. Artificial Intelligence, Tata McGraw Hill.
- Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach, Prentice Hall.
- M.C. Trivedi, A classical approach to Artificial Intelligence, Khanna Publishing House.
6.1.2 — Data Science and Machine Learning
Units at a Glance
| Unit | Topic | Periods | Marks Share |
|---|---|---|---|
| 1 | Introduction of Data Science and Machine Learning | 10 | 22% |
| 2 | Data Preprocessing, Analysis and Visualization | 6 | 16% |
| 3 | Statistical Inference & Exploratory Data Analysis and the Data Science Process | 10 | 22% |
| 4 | Machine Learning Algorithms | 8 | 20% |
| 5 | Mining Social-Network Graphs, Data Science and Ethical Issues | 8 | 20% |
Reference Books
As listed in the syllabus:
- Jiawei Han, Micheline Kamber, Jian Pei, Data Mining: Concepts and Techniques, Elsevier.
- Margaret H Dunham, Data Mining Introductory and Advanced Topics, Pearson Education.
- Amitesh Sinha, Data Warehousing, Thomson Learning, India.
- Xingdong Wu, Vipin Kumar, the Top Ten Algorithms in Data Mining, CRC Press, UK.
Entrepreneurship and Start-ups
Units at a Glance
| Unit | Topic | Periods | Marks Share |
|---|---|---|---|
| 1 | Introduction to Entrepreneurship and Start-Ups | 2 | 17% |
| 2 | Business Ideas and their implementation | 6 | 14% |
| 3 | Ideas to Start-up | 6 | 20% |
| 4 | Management | 4 | 17% |
| 5 | Financing and Protection of Ideas | 6 | 21% |
| 6 | Succession, Dissolution and Harvesting strategy | 4 | 11% |
Reference Books
As listed in the syllabus:
- The Startup Owner's Manual: The Step-by-Step Guide for Building a Great Company — Steve Blank and Bob Dorf, K & S Ranch, ISBN 978-0984999392.
- Entrepreneurship Development (A new Venture creation) — Vasant Desai, Himalaya Publication.
- Entrepreneurship Development — Khanka S.S., S Chand & Company Limited, New Delhi.
- Entrepreneurship Development — Gupta and Srinivasan, S Chand & Company Limited, New Delhi.
- Demand: Creating What People Love Before They Know They Want It — Adrian J. Slywotzky with Karl Weber, Headline Book Publishing, ISBN 978-0755388974.
- The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses — Eric Ries, Penguin UK, ISBN 978-0670921607.
- The Innovator's Dilemma: The Revolutionary Book That Will Change the Way You Do Business — Clayton M. Christensen, Harvard Business Review Press, ISBN 978-142219602.
In House Project
No unit-wise topics, practical list or reference books are given in the official syllabus for the In House Project.
Open Elective-3
6.4.1 — Disaster Management
Units at a Glance
| Unit | Topic | Periods | Marks Share |
|---|---|---|---|
| I | Understanding Disaster | 6 | 17% |
| II | Types, Trends, Causes, Consequences and Control of Disasters | 10 | 22% |
| III | Disaster Management Cycle and Framework | 10 | 22% |
| IV | Disaster Management in India | 10 | 22% |
| V | Applications of Science and Technology for Disaster Management | 6 | 17% |
Reference Books
As listed in the syllabus:
- Publications of National Disaster Management Authority (NDMA) on Various Templates and Guidelines for Disaster Management.
- Bhandani, R. K., An overview on natural & man-made disasters and their reduction, CSIR, New Delhi.
- Srivastava, H. N., and Gupta G. D., Management of Natural Disasters in developing countries, Daya Publishers, Delhi.
- Alexander, David, Natural Disasters, Kluwer Academic London.
- Ghosh, G. K., Disaster Management, A P H Publishing Corporation.
- Murthy, D. B. N., Disaster Management: Text & Case Studies, Deep & Deep Pvt. Ltd.
6.4.2 — Renewable Energy Technologies
The official syllabus gives no period counts or marks distribution table for this option — only course outcomes. The units are listed without periods or weightage.
Reference Books
As listed in the syllabus:
- O.P. Gupta, Energy Technology, Khanna Publishing House, Delhi (ed. 2018).
- Renewable Energy Sources, Twidell, J.W. & Weir, A., EFN Spon Ltd., UK, 2006.
- Solar Energy, Sukhatme. S.P., Tata McGraw Hill Publishing Company Ltd., New Delhi, 1997.
- Renewable Energy, Power for a Sustainable Future, Godfrey Boyle, Oxford University Press, U.K., 1996.
- Fundamental of Renewable Energy Sources, GN Tiwari and MK Ghoshal, Narosa, New Delhi, 2007.
- Renewable Energy and Environment — A Policy Analysis for India, NH Ravindranath, UK Rao, B Natarajan, P Monga, Tata McGraw Hill.
- Energy and The Environment, RA Ristinen and J J Kraushaar, Second Edition, John Willey & Sons, New York, 2006.
- Renewable Energy Resources, JW Twidell and AD Weir, ELBS, 2006.
Frequently Asked Questions
How many total marks are there in the 6th semester?
650 marks, 20 credits. The In House Project is 400 marks, Program Elective-4 is 100, Entrepreneurship and Start-ups is 100, and SCA is 50. Open Elective-3 (50 marks internal only) is not counted in the total.
How is the In House Project marked?
400 marks: 240 internal + 160 practical (external). There is no written theory paper — the project is assessed on the work you produce and present. The official syllabus gives no unit-wise topics, practical list or reference books for it.
What is the Industrial Pathway in the 6th semester?
An optional alternative to the regular classroom route: one semester of industrial training (not less than 14 weeks) worth 20 credits and 650 marks — Entrepreneurship and Start-ups online (100 marks), Industrial Hands On Practice (350 marks: 150 by faculty mentor + 200 by industry), Industrial Project (100 marks: 50 + 50) and a Seminar (100 marks).
Which electives do I have to choose in the 6th semester?
Two choices. Program Elective-4: Fundamentals of Artificial Intelligence OR Data Science and Machine Learning (100 marks, 4 credits). Open Elective-3: Disaster Management OR Renewable Energy Technologies (50 marks internal only, qualifying, not counted in the total) — or an Advance Skill Development certification course of not less than 20 hours instead.
What does (Q) mean next to Open Elective-3?
Qualifying. You must appear for the examination and pass it, but the 50 internal marks are not included in your percentage or division. The subject still carries 2 credits.
How can I download the subject-wise syllabus PDFs?
Use the download link in the Download section below for the complete CSE syllabus PDF, or open any subject post from the Related Syllabus Posts list — each subject post has its own PDF download.
Related Syllabus Posts
- BTEUP CSE Complete Syllabus 2026-27 — All Years, All Semesters
- BTEUP CSE 5th Semester Syllabus 2026-27
- Program Elective-4 — BTEUP CSE 6th Semester Syllabus 2026-27
- Entrepreneurship and Start-ups — BTEUP CSE 6th Semester Syllabus 2026-27
- In House Project — BTEUP CSE 6th Semester Syllabus 2026-27
- Open Elective-3 — BTEUP CSE 6th Semester Syllabus 2026-27
Download The Complete Syllabus PDF
Download the complete CSE syllabus PDF below — all years, all semesters in one file, prepared by KAMALDNP Academy.
Download The Complete CSE Syllabus PDF
Source: BTEUP 3rd Year curriculum (folder2627), approved in C.D.C. meeting held on 16.07.2026. Topic lists follow the official syllabus; short explanations are the author's own plain-English summaries, not syllabus text. Please confirm with your own polytechnic for any local changes.
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