Course Structure Overview
The Computer Science program at Era University Lucknow is structured over 8 semesters, with each semester comprising a mix of core courses, departmental electives, science electives, and laboratory sessions. The curriculum is designed to provide students with a strong foundation in mathematics, physics, and computing principles, followed by specialized knowledge in advanced areas.
| Year | Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|---|
| 1 | I | CS101 | Introduction to Programming | 3-0-0-3 | - |
| CS102 | Mathematics for Computer Science | 4-0-0-4 | - | ||
| 1 | II | CS103 | Data Structures and Algorithms | 3-0-0-3 | CS101 |
| CS104 | Discrete Mathematics | 4-0-0-4 | - | ||
| 2 | III | CS201 | Database Management Systems | 3-0-0-3 | CS103 |
| CS202 | Operating Systems | 3-0-0-3 | CS103 | ||
| 2 | IV | CS203 | Computer Networks | 3-0-0-3 | CS103 |
| CS204 | Software Engineering | 3-0-0-3 | CS103 | ||
| 3 | V | CS301 | Artificial Intelligence | 3-0-0-3 | CS103 |
| CS302 | Cybersecurity | 3-0-0-3 | CS204 | ||
| 3 | VI | CS303 | Machine Learning | 3-0-0-3 | CS103 |
| CS304 | Data Science | 3-0-0-3 | CS201 | ||
| 4 | VII | CS401 | Capstone Project | 0-0-6-6 | CS301, CS302, CS303 |
| CS402 | Research Methodology | 3-0-0-3 | - | ||
| 4 | VIII | CS403 | Internship | 0-0-0-6 | - |
| CS404 | Elective Courses | 3-0-0-3 | - |
Advanced Departmental Electives
The department offers a wide array of advanced elective courses that allow students to specialize in their areas of interest. These courses are designed to provide in-depth knowledge and practical experience in emerging technologies.
- Neural Networks and Deep Learning: This course explores the fundamentals of neural networks, including feedforward networks, convolutional neural networks, recurrent neural networks, and transformers. Students will gain hands-on experience with frameworks like TensorFlow and PyTorch.
- Natural Language Processing: Focused on building systems that can understand, interpret, and generate human language, this course covers text preprocessing, sentiment analysis, named entity recognition, and machine translation.
- Computer Vision: This elective introduces students to image processing techniques, object detection, segmentation, and recognition algorithms using modern deep learning models.
- Reinforcement Learning: Students learn about Markov Decision Processes, Q-learning, policy gradients, and actor-critic methods. The course includes practical implementations of reinforcement learning agents in game environments and robotics.
- Cloud Computing: This course covers cloud architecture, virtualization technologies, distributed systems, and services offered by platforms like AWS, Azure, and Google Cloud.
- Internet of Things (IoT): Students explore sensor networks, embedded systems programming, wireless communication protocols, and IoT platform development using tools like Arduino and Raspberry Pi.
- Mobile Application Development: This course teaches students how to build cross-platform mobile applications using React Native, Flutter, or native frameworks for iOS and Android.
- Game Development: Focused on game design principles, Unity engine usage, 3D modeling, physics simulation, and scripting in C# for creating interactive games.
- Human-Computer Interaction: This elective covers usability testing, user experience design, prototyping, and interaction design patterns to create intuitive interfaces.
- Cybersecurity and Ethical Hacking: Students learn about network security, cryptography, penetration testing, and vulnerability assessment using tools like Kali Linux and Metasploit.
Project-Based Learning Framework
Era University Lucknow emphasizes project-based learning as a cornerstone of the Computer Science curriculum. The program includes mandatory mini-projects in early semesters followed by a final-year thesis/capstone project that integrates all learned concepts into a real-world solution.
Mini-projects are assigned at the end of each semester and serve to reinforce theoretical knowledge through practical implementation. Each project is mentored by faculty members who guide students through problem definition, research, design, coding, testing, and documentation phases.
The final-year capstone project is an extended initiative where students collaborate with industry partners or pursue independent research topics under faculty supervision. Students select projects based on their interests and career aspirations, working closely with mentors to ensure academic rigor and innovation.
Evaluation criteria for projects include technical execution, presentation quality, documentation completeness, peer review scores, and final project defense before a panel of experts. This comprehensive framework ensures that students graduate with not only strong theoretical foundations but also substantial practical experience ready for professional environments.