HRITIK C H
CHENNAI
Summary
Computer Science graduate with practical experience in software development using Python and Java. Proficient in object-oriented programming and well-versed in the Software Development Life Cycle (SDLC). Knowledgeable in machine learning concepts shown through academic projects and internships. Enthusiastic about solving real-world challenges with efficient, scalable code, and eager to collaborate within a dynamic development team.
Overview
2
2
years of professional experience
1
1
Certification
Work History
Machine Learning Intern
Vcodez Innovative Ideas
02.2025 - 04.2025
- Created customized applications to make critical predictions, automate reasoning and decisions and calculate optimization algorithms.
- Prototyped machine learning applications and quickly determined application viability.
- Studied new technologies to support machine learning applications.
AMAZON WEB SERVICES
EDIGLOBE
04.2024 - 06.2024
- Developed user interfaces for deployment on Amazon Web Services (AWS) platforms.
- Provided professional services and support in a dynamic work environment.
MACHINE LEARNING
DLK CARRIER DEVELOPMENT
07.2023 - 08.2023
- Integrated machine learning and predictive analytics into tasks.
- Implemented and evaluated artificial intelligence and machine learning algorithms and neural networks for diverse industries.
- Devised and deployed predictive models using machine learning algorithms to drive business decisions.
Education
B.E - COMPUTER SCIENCE ENGINEERING
SRM VALLIAMMAI ENGINEERING COLLEGE
POTHERI04-2025
TNDTE - COMPUTER ENGINEERING
SRM VALLIAMMAI POLYTECHNIC COLLEGE
POTHERI04-2022
SSLC -
ST JOSEPH MAT HR SEC SCHOOL
MARAIMALAI NAGAR04-2019
Skills
- Python programming
- Machine learning algorithms
- Cloud computing
- Problem-solving
- Multitasking Abilities
- Goal setting
- Continuous improvement
Projects
1. Webpage Creation for Tourist Package
Technologies: HTML, CSS, JavaScript
Developed a responsive and user-friendly website for showcasing tourist packages. Integrated dynamic elements using JavaScript to enhance user interactivity. The project aimed to provide an engaging interface for travel package selection and booking.
2. Blood Bank Management System
Technologies: Java, Application Deployment, Google Cloud Platform (GCP)
Designed and deployed an application to manage donor and blood inventory records, focusing on accessibility for rural healthcare centers. Integrated GCP for cloud storage and scalability. Improved efficiency in blood availability tracking and emergency alerts.
3. Suicidal Prediction Using Machine Learning
Technologies: Python, Machine Learning (10 algorithms)
Built a predictive model using ten different machine learning algorithms to assess suicidal tendencies based on user input. Compared performance metrics to select the most accurate model. Designed with user-specific result generation and preventive detail suggestions.
4. Detection of Phishing Using Machine Learning
Technologies: Machine Learning, Deep Learning, Real-Time Detection
Developed a system to detect phishing URLs and emails using machine learning and deep learning algorithms. Implemented real-time detection features to enhance cybersecurity. The model analyzed link structures, domain age, and behavioral patterns for high-accuracy detection.
Technologies: HTML, CSS, JavaScript
Developed a responsive and user-friendly website for showcasing tourist packages. Integrated dynamic elements using JavaScript to enhance user interactivity. The project aimed to provide an engaging interface for travel package selection and booking.
2. Blood Bank Management System
Technologies: Java, Application Deployment, Google Cloud Platform (GCP)
Designed and deployed an application to manage donor and blood inventory records, focusing on accessibility for rural healthcare centers. Integrated GCP for cloud storage and scalability. Improved efficiency in blood availability tracking and emergency alerts.
3. Suicidal Prediction Using Machine Learning
Technologies: Python, Machine Learning (10 algorithms)
Built a predictive model using ten different machine learning algorithms to assess suicidal tendencies based on user input. Compared performance metrics to select the most accurate model. Designed with user-specific result generation and preventive detail suggestions.
4. Detection of Phishing Using Machine Learning
Technologies: Machine Learning, Deep Learning, Real-Time Detection
Developed a system to detect phishing URLs and emails using machine learning and deep learning algorithms. Implemented real-time detection features to enhance cybersecurity. The model analyzed link structures, domain age, and behavioral patterns for high-accuracy detection.
Certification
- Certified MASTER DIPLOMA IN SOFTWARE ENGINEER (MDSE), ANJALI COMPUTER EDUCATION INSTITUTE - 1 YEAR
- Certified CLOUD COMPUTING, AMAZON WEB SERVICES EDUCATE
LANGUAGE
ENGLISH
TAMIL
MALAYALAM
Hobbies and Interests
MUSIC
TRAVELLING
Co-Curricular Activity
National Seminar on “Recent Advances in Big Data”.
Seminar on “FULL STACK DEVELOPMENT ON MONGO DB”
Timeline
Machine Learning Intern
Vcodez Innovative Ideas
02.2025 - 04.2025
AMAZON WEB SERVICES
EDIGLOBE
04.2024 - 06.2024
MACHINE LEARNING
DLK CARRIER DEVELOPMENT
07.2023 - 08.2023
B.E - COMPUTER SCIENCE ENGINEERING
SRM VALLIAMMAI ENGINEERING COLLEGE
TNDTE - COMPUTER ENGINEERING
SRM VALLIAMMAI POLYTECHNIC COLLEGE
SSLC -
ST JOSEPH MAT HR SEC SCHOOL
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