Evaluation Scheme and Syllabus - Bachelor of Technology - Computer Science and Engineering (Artificial Intelligence and Machine Learning) - Third Year - Semester-V & Semester-VI

Sep 17, 2026

Evaluation Scheme & Syllabus for the Bachelor of Technology program in Computer Science and Engineering (Artificial Intelligence and Machine Learning) for Third Year, effective from Session 2025-26, provided for Semester-V and Semester-VI. The scheme lists course codes, subject names, subject types (mandatory, departmental elective, open elective, labs), lecture/tutorial/practical periods, class test and teacher assessment components, end-semester evaluation parts, totals and credits. It also includes compulsory audit rules, internship assessment guidance, and a recommended MOOCs list with partner and hours.

LanguageEnglish

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Reading Time2 h 54 min

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Evaluation Scheme and Syllabus

Semester-V

Departmental Electives and MOOCs (Semester-V)

Notes, Abbreviations, and Internship/Compulsory Audit Rules

Semester-VI

Departmental Electives and MOOCs (Semester-VI)

NOIDA INSTITUTE OF ENGINEERING AND TECHNOLOGY, GREATER NOIDA, G.B. NAGAR (AN AUTONOMOUS INSTITUTE) Affiliated to DR. A.P.J. ABDUL KALAM TECHNICAL UNIVERSITY, UTTAR PRADESH, LUCKNOW Evaluation Scheme & Syllabus For Bachelor of Technology Computer Science and Engineering (Artificial Intelligence and Machine Learning) Third Year (Effective from the Session: 2025-26) NOIDA INSTITUTE OF ENGINEERING & TECHNOLOGY, GREATER NOIDA, GAUTAM BUDDH NAGAR (AN AUTONOMOUS INSTITUTE) Bachelor of Technology Computer Science and Engineering (Artificial Intelligence and Machine Learning) Evaluation Scheme SEMESTER-V | Sl.
No
. | Subject
Codes | Subject | Types of
Subjects | Periods | | Evaluation Schemes | | | | | End
Semester | | Total | Credit | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | | | | | L | T | P | CT | TA | TOTAL | PS | TE | PE | | | | 1 | BCSCC0501 | Design Thinking-II | Mandatory | 2 | 1 | 0 | 30 | 20 | 50 | | 100 | | 150 | 3 | | 2 | BCSE0502 | Computer Networks | Mandatory | 3 | 1 | 0 | 30 | 20 | 50 | | 100 | | 150 | 4 | | 3 | | Departmental Elective –I | Departmental
Elective | 3 | 0 | 0 | 30 | 20 | 50 | | 100 | | 150 | 3 | | 4 | | Departmental Elective –II | Departmental
Elective | 3 | 0 | 0 | 30 | 20 | 50 | | 100 | | 150 | 3 | | 5 | BCSE0552 | Computer Networks Lab | Mandatory | 0 | 0 | 4 | | | | 50 | | 50 | 100 | 2 | | 6 | BCSML0552 | Deep Learning | Mandatory | 0 | 0 | 6 | | | | 50 | | 100 | 150 | 3 | | 7 | BCSE0555 | Web Technologies | Mandatory | 0 | 0 | 6 | | | | 50 | | 100 | 150 | 3 | | 8 | BCSE0559 | Internship Assessment-II | Mandatory | 0 | 0 | 2 | | | | 50 | | | 50 | 1 | | 9 | BNC0501/
BNC0502 | Constitution of India, Law and Engineering / Essence of Indian Traditional Knowledge | Compulsory
Audit | 2 | 0 | 0 | 30 | 20 | 50 | | 50 | | 100 | NA | | 10 | | *Massive Open Online Courses (For B.Tech. Hons. Degree) | MOOCs | | | | | | | | | | | | | | | TOTAL | | 13 | 2 | 18 | 120 | 80 | 200 | 200 | 400 | 250 | 1050 | 22 | List of MOOCs Based Recommended Courses for Third year (Semester-V) B. Tech Students | Sr. No. | Subject
Code | Course Name | University / Industry Partner Name | No of Hours | Credits | | --- | --- | --- | --- | --- | --- | | 1 | BMC0077 | Deep Learning for Developers | Infosys Wingspan (Infosys Springboard) | 34h 51m | 2.5 | | 2 | BMC0095 | ReactJS | Infosys Wingspan (Infosys Springboard) | 61h 2m | 4 | PLEASE NOTE: - • A 3–4-week Internship shall be conducted during summer break after semester-IV and will be assessedduring semester-V. • Compulsory Audit (CA) Courses (Non-Credit-BNC0501/BNC0502) ➢ All Compulsory Audit Courses (a qualifying exam) do not require any credit. ➢ The total and obtained marks are not added to the grand total. Abbreviation Used: L: Lecture, T: Tutorial, P: Practical, CT: Class Test, TA: Teacher Assessment, PS: Practical Sessional, TE: Theory End Semester Exam., CE: Core Elective, OE: Open Elective, DE: Departmental Elective, PE: Practical End Semester Exam, CA: Compulsory Audit, MOOCs: Massive Open Online Courses. DEPARTMENTAL ELECTIVES | Sl.
No. | Subject Codes | Subject Name | Types of Subjects Bucket Name | | Branch | Semester | | --- | --- | --- | --- | --- | --- | --- | | 1 | BCSE0511 | CRM Fundamentals | Departmental Elective-I | CRM-RPA | CSE (AIML) | 5 | | 2 | BCSE0513 | CRM Administration | Departmental Elective-II | | CSE (AIML) | 5 | | 3 | BCSDS0511 | Data Analytics | Departmental Elective-I | Data Analytics | CSE (AIML) | 5 | | 4 | BCSAI0519 | Business Intelligence and Data Visualization | Departmental Elective-II | | CSE (AIML) | 5 | | 5 | BCSE0512 | Python Web Development with Django | Departmental Elective-I | Full Stack
Development | CSE (AIML) | 5 | | 6 | BCSE0514 | Design Patterns | Departmental Elective-II | | CSE (AIML) | 5 | | 7 | BCSAI0515 | Mobile Applicatio

FAQs

Which courses are listed under Semester-V for B.Tech CSE (AIML) Third Year?

Semester-V includes Design Thinking-II, Computer Networks, two departmental electives, Computer Networks Lab, Deep Learning, Web Technologies, Internship Assessment-II, and Compulsory Audit courses including BNC0501/BNC0502.

How are internship and compulsory audit assessed across the semesters?

A 3–4-week internship is conducted during summer break after Semester-IV and assessed during Semester-V. Compulsory Audit (CA) courses use a qualifying exam approach: no credit is required, and total/obtained marks are not added to the grand total.

What are the mandatory and major course components in Semester-VI?

Semester-VI lists mandatory courses such as Natural Language Processing, Generative AI, Software Engineering and Design, and Mini Project, along with Natural Language Processing Lab. It also includes departmental electives, open elective I, and MOOCs for essential honors requirements.

Sep 17, 2026

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