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Duration

4 Years

Computer Science

Plaksha University, Mohali
Duration

Apply

Scholarships & exams

support@collegese.com
+91 88943 57155
Pune, Maharashtra, India
4 Years
Computer Science
UG
OFFLINE

Duration

4 Years

Computer Science

Plaksha University, Mohali
Duration
4 Years
Computer Science UG OFFLINE

Fees

₹3,50,000

Placement

94.5%

Avg Package

₹7,50,000

Highest Package

₹12,00,000

ApplyCollege
Apply

Fees

₹3,50,000

Placement

94.5%

Avg Package

₹7,50,000

Highest Package

₹12,00,000

Seats

150

Students

600

OverviewAdmissionsCurriculumFeesPlacements

Curriculum

Comprehensive Course Structure

The Computer Science curriculum at Plaksha University Mohali is meticulously structured across eight semesters to ensure a progressive and holistic learning experience. The program includes core courses, departmental electives, science electives, and laboratory components that are designed to build both theoretical understanding and practical application.

SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
1CSE101Introduction to Programming with Python3-0-0-3-
1CSE102Mathematics for Computer Science I4-0-0-4-
1CSE103Engineering Graphics and Design2-0-0-2-
1SC101Physics for Engineers3-0-0-3-
1SC102Chemistry Laboratory0-0-2-1-
2CSE201Data Structures and Algorithms3-0-0-3CSE101
2CSE202Mathematics for Computer Science II4-0-0-4CSE102
2CSE203Digital Logic and Computer Organization3-0-0-3-
2SC201Biology for Engineers3-0-0-3-
2SC202Mathematics Lab I0-0-2-1-
3CSE301Database Management Systems3-0-0-3CSE201
3CSE302Operating Systems3-0-0-3CSE203
3CSE303Computer Networks3-0-0-3CSE201
3DE301Introduction to Software Engineering3-0-0-3-
3DE302Human Computer Interaction3-0-0-3-
4CSE401Machine Learning3-0-0-3CSE201
4CSE402Computer Vision3-0-0-3CSE201
4CSE403Distributed Systems3-0-0-3CSE203
4DE401Advanced Software Engineering3-0-0-3DE301
4DE402Cybersecurity Fundamentals3-0-0-3-
5CSE501Deep Learning3-0-0-3CSE401
5CSE502Natural Language Processing3-0-0-3CSE401
5DE501Cloud Computing3-0-0-3-
5DE502Big Data Analytics3-0-0-3-
6CSE601Reinforcement Learning3-0-0-3CSE401
6CSE602Internet of Things3-0-0-3-
6DE601Blockchain Technologies3-0-0-3-
7CSE701Research Methodology2-0-0-2-
7DE701Capstone Project I3-0-0-3-
8DE801Capstone Project II4-0-0-4DE701

Advanced Departmental Electives

Departmental electives play a crucial role in allowing students to explore areas of personal interest and professional relevance. These courses are designed to provide deep insights into specialized domains such as AI, cybersecurity, cloud computing, and data science.

  • Machine Learning: This course delves into supervised and unsupervised learning algorithms, neural networks, and reinforcement learning techniques, preparing students for roles in data science and artificial intelligence.
  • Computer Vision: Students learn how to process and interpret visual information using deep learning models, with applications in robotics, medical imaging, and autonomous vehicles.
  • Distributed Systems: This course focuses on the design and implementation of systems that span multiple computers, covering topics like consensus algorithms, fault tolerance, and scalability principles.
  • Advanced Software Engineering: Emphasizes modern software development practices including agile methodologies, DevOps, and system design patterns.
  • Cybersecurity Fundamentals: Covers essential concepts in information security, including encryption, network security, and ethical hacking.
  • Cloud Computing: Introduces cloud platforms like AWS, Azure, and GCP, focusing on deployment strategies, virtualization, and scalable architecture design.
  • Big Data Analytics: Explores tools such as Hadoop, Spark, and NoSQL databases to analyze large datasets for business intelligence and predictive modeling.
  • Reinforcement Learning: Focuses on decision-making in uncertain environments using algorithms that learn optimal actions through trial and error.
  • Internet of Things (IoT): Covers sensor networks, embedded systems, and wireless communication protocols used in smart cities and industrial automation.
  • Blockchain Technologies: Provides an overview of blockchain architecture, smart contracts, and decentralized applications with real-world use cases.

Project-Based Learning Philosophy

At Plaksha University Mohali, project-based learning is the cornerstone of our academic approach. Students engage in both mini-projects and a final-year thesis that reflect their interests and career aspirations. The program emphasizes hands-on experimentation, collaboration, and innovation.

Mini-projects are introduced in the second year and require students to work in teams on real-world problems assigned by faculty or industry partners. These projects are evaluated based on technical execution, teamwork, and presentation skills.

The final-year capstone project is a significant component of the program, where students select an area of interest and work under the guidance of a faculty mentor. Projects may lead to publications, patents, or startup ventures, offering students tangible outcomes that enhance their professional profiles.

Seats

150

Students

600