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Scholarships & exams

support@collegese.com
+91 88943 57155
Pune, Maharashtra, India

Duration

4 Years

Womens Polytechnic

Government Girls Polytechnic Almora
Duration
4 Years
Womens Polytechnic UG OFFLINE

Duration

4 Years

Womens Polytechnic

Government Girls Polytechnic Almora
Duration
Apply

Fees

₹1,50,000

Placement

92.0%

Avg Package

₹4,50,000

Highest Package

₹8,00,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Womens Polytechnic
UG
OFFLINE

Fees

₹1,50,000

Placement

92.0%

Avg Package

₹4,50,000

Highest Package

₹8,00,000

Seats

200

Students

200

ApplyCollege

Seats

200

Students

200

Curriculum

Comprehensive Course List

The curriculum of the Womens Polytechnic program at Govt Girls Polytechnic Almora is meticulously structured to provide a balanced blend of theoretical knowledge and practical skills. Below is a detailed table listing all courses across 8 semesters.

SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Pre-requisites
1ENG101English for Engineering3-0-0-3-
1MAT101Mathematics I4-0-0-4-
1PHY101Physics for Engineering3-0-0-3-
1CHE101Chemistry for Engineering3-0-0-3-
1INT101Introduction to Engineering2-0-0-2-
1COM101Computer Programming3-0-0-3-
2MAT201Mathematics II4-0-0-4MAT101
2ECO201Engineering Economics3-0-0-3-
2ELE201Basic Electrical Engineering3-0-0-3-
2CSE201Object-Oriented Programming3-0-0-3COM101
2MEC201Engineering Mechanics3-0-0-3-
3MAT301Mathematics III4-0-0-4MAT201
3DLD301Digital Logic Design3-0-0-3-
3CS301Data Structures & Algorithms3-0-0-3CSE201
3ECE301Electronics Fundamentals3-0-0-3ELE201
3CIV301Engineering Drawing2-0-0-2-
4MAT401Mathematics IV4-0-0-4MAT301
4CSE401Database Management Systems3-0-0-3CS301
4MEC401Mechanics of Materials3-0-0-3MEC201
4ECE401Signals & Systems3-0-0-3ECE301
4CIV401Structural Analysis3-0-0-3CIV301
5CSE501Computer Networks3-0-0-3CS301
5ECE501Control Systems3-0-0-3ECE401
5CIV501Concrete Technology3-0-0-3CIV401
5MEC501Thermodynamics3-0-0-3MEC401
5CS501Machine Learning Fundamentals3-0-0-3CS301
6CSE601Software Engineering3-0-0-3CS501
6ECE601VLSI Design3-0-0-3ECE501
6CIV601Transportation Engineering3-0-0-3CIV501
6MEC601Manufacturing Processes3-0-0-3MEC501
6CS601Web Technologies3-0-0-3CS501
7CSE701Advanced Computer Architecture3-0-0-3CS601
7ECE701Embedded Systems3-0-0-3ECE601
7CIV701Geotechnical Engineering3-0-0-3CIV601
7MEC701Heat Transfer3-0-0-3MEC601
7CS701Deep Learning3-0-0-3CS501
8CSE801Capstone Project6-0-0-6CS701
8ECE801Final Year Research6-0-0-6ECE701
8CIV801Project Management3-0-0-3CIV701
8MEC801Industrial Training6-0-0-6MEC701
8CS801Internship & Thesis6-0-0-6CS701

Advanced Departmental Elective Courses

These advanced courses are designed to provide students with deeper insights into specialized domains within engineering. They are offered in the later semesters and are chosen based on student interest and career aspirations.

Machine Learning Fundamentals: This course introduces students to fundamental concepts of machine learning, including supervised and unsupervised learning algorithms, neural networks, and deep learning frameworks. Students will gain practical experience through hands-on labs and real-world case studies.

Web Technologies: The course covers modern web development techniques using HTML, CSS, JavaScript, and backend technologies such as Node.js and databases like MongoDB. Students will build responsive web applications and learn about cloud deployment strategies.

Advanced Computer Architecture: This course explores the design and implementation of modern computer systems, focusing on pipeline architecture, cache memory, and parallel processing techniques. It prepares students for advanced roles in hardware and software optimization.

Embedded Systems: Students will learn to design and implement embedded systems using microcontrollers and real-time operating systems. The course includes practical labs involving sensor integration and IoT development.

Deep Learning: A comprehensive study of deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers. Students will implement models for image recognition, natural language processing, and recommendation systems.

VLSI Design: This course covers the principles of very large-scale integration (VLSI) design, including logic synthesis, circuit design, and layout techniques. Students will use industry-standard tools to design integrated circuits.

Control Systems: An in-depth exploration of control theory, including feedback systems, stability analysis, and controller design. The course emphasizes practical applications in automation and robotics.

Signals & Systems: This course teaches the mathematical foundations of signal processing, including Fourier transforms, Laplace transforms, and Z-transforms. Applications include audio and image processing, communication systems, and control theory.

Database Management Systems: Students will learn about relational database design, SQL queries, normalization, transaction management, and performance optimization. The course includes practical labs using MySQL, PostgreSQL, and MongoDB.

Software Engineering: This course focuses on software development methodologies, requirements analysis, testing, and project management. Students will work on team-based projects using agile frameworks like Scrum and Kanban.

Project-Based Learning Philosophy

The department strongly believes in project-based learning as a core component of technical education. The curriculum integrates mandatory mini-projects throughout the academic journey to ensure that students apply theoretical knowledge in real-world scenarios.

Mini-Projects: In the third and fourth semesters, students undertake mini-projects under faculty supervision. These projects are typically small-scale but require students to demonstrate their understanding of core concepts while working collaboratively with peers.

Final-Year Thesis/Capstone Project: The capstone project in the eighth semester is a significant endeavor that allows students to explore a topic of personal interest or relevance to current industry trends. Students select their projects based on faculty expertise and industry partnerships, ensuring that their work has practical value.

The evaluation criteria for these projects include innovation, technical execution, documentation quality, and presentation skills. Faculty mentors guide students throughout the process, helping them navigate challenges and refine their ideas.