• Welcome to the Department of Cybersecurity LMS
    SSM Institute of Engineering and Technology

    This Moodle-based Learning Management System (LMS) is created exclusively for the Department of Cybersecurity, SSM Institute of Engineering and Technology to support effective online and blended learning.

    Through this platform, students can access:
    📘 Course notes and learning materials
    📝 Assignments and assessments
    🧠 Online quizzes
    🧪 Lab and practical activities
    📢 Course and department announcements

    All courses are organised unit-wise for easy understanding.
    Students are advised to regularly check the LMS for updates, announcements, and deadlines.

    This LMS supports both synchronous and asynchronous learning, enabling faculty to share recorded lectures, resources, and conduct interactive academic activities.

    📌 Happy Learning!

Available courses

CCS355-Neural Networks and Deep Learning

At the end of this course, the students will be able to:

CO1: Apply Convolution Neural Network for image processing.

CO2: Understand the basics of associative memory and unsupervised learning networks.

CO3: Apply CNN and its variants for suitable applications.

CO4: Analyze the key computations underlying deep learning and use them to build and train deep neural networks for various tasks.

CO5: Apply autoencoders and generative models for suitable applications. 

CS1201- Programming in C

CO1: Demonstrate knowledge on C Programming constructs.
CO2: Design and implement applications using arrays and Pointer. 
CO3: Develop applications in C using strings and functions. 
CO4: Develop and implement modular applications in C using Structure and Union.
CO5: Design applications using sequential and random access file processing.

CS3491-Artificial Intelligence and Machine Learning

At the end of this course, the students will be able to:
CO1: Use appropriate search algorithms for problem solving
CO2: Apply reasoning under uncertainty
CO3: Build supervised learning model
CO4: Build ensemble and unsupervised models
CO5: Build deep learning neural network models

CB3491-Cryptography and Cyber Security

CO1: Understand the fundamentals of networks security, security architecture, threats and vulnerabilities

CO2: Apply the different cryptographic operations of symmetric cryptographic algorithms

CO3: Apply the different cryptographic operations of public key cryptography

CO4: Apply the various Authentication schemes to simulate different applications. 

CO5: Understand various cyber crimes and cyber security.

CS3391-Object Oriented Programming

On completion of this course, the students will be able to  

CO1:Apply the concepts of classes and objects to solve simple problems

CO2:Develop programs using inheritance, packages and interfaces  

CO3:Make use of exception handling mechanisms and multithreaded model to solve real world problems  

CO4:Build Java applications with I/O packages, string classes, Collections and generics concepts

CO5:Integrate the concepts of event handling and JavaFX components and controls for developing GUI based applications