Rahul Yashavanth Sanil

Driven and detail-oriented professional with a strong foundation in Information Science Engineering and a keen focus on cybersecurity. Currently pursuing a Master's in Cybersecurity, I am passionate about protecting digital infrastructures and building secure systems. Skilled in threat analysis, network security, and vulnerability assessment, I thrive in dynamic environments where innovation meets practical problem-solving.

Successfully completed an online Course on Introduction to Web Applications authorized by Akamai Technologies offered by Coursera | 10 May 2024

Successfully completed an online Course on Introduction to IT Security authorized by Akamai Technologies offered by Coursera | 09 May 2024

Successfully completed an online course on Networking Fundamentals authorized by Akamai Technologies offered by Coursera | 09 May 2024

Successfully completed a course on AWS-Solutions Architect offered by Learnmore Technologies | Dec 2023 - Mar 2024

Cruise Management System | HTML, CSS, MySQL Duration: January 2022

Implemented a Cruise Management System integrating HTML for front-end structure and CSS for styling, with MySQL serving as the backend database management system Allows users to perform tasks such as cruise booking, passenger management, and real-time availability tracking.

Platelet Donation System | Java, Android Studio Duration: November 2022

Created a Platelet Donation System mobile application using Java for implementing logic and XML for defining the app’s user interface. Committed to making the platelet donation process as simple and user-friendly as possible with the mobile app, while still offering crucial information.

Detection of Lung Cancer from Ct-Scan Images Using Deep Learning | Python, CNN Duration: June 2023

Developed a solid deep learning model for the precise identification of lung cancer from CT scan images using Python’s Convolutional Neural Networks (CNN) and libraries like TensorFlow and Keras. Advanced neural network architectures were used to evaluate and decipher complex patterns found in medical images, improving the model’s capacity to recognise potentially malignant lesions.