ANAS MOHD
Coral comp
HYDERABAD
Dynamic Full Stack Developer Intern at Coral comp with expertise in web development and API integration. Proven ability to enhance user experience through responsive design and effective data analysis. Skilled in JavaScript frameworks and SQL, with a strong focus on delivering impactful solutions and collaborating within teams to drive project success.
1
Certification
1
year of professional experience
Work History
Full Stack Developer Intern
8 Months
Coral comp - HYDERABAD | 02.2026 - Current
- Contributed to Coral comp full stack team by implementing front-end feature updates, improving user interaction.
- Developed responsive web applications using HTML, CSS, and JavaScript frameworks to improve user experience.
- Built responsive web pages using HTML, CSS, and JavaScript
- Assisted in API integration to expand application functionality and streamline data exchange.
- Assisted backend API testing and request troubleshooting
Data Analyst
4 Months
GeeksforGeeks - Hyderabad | 07.2025 - 11.2025
- Analyzed GeeksforGeeks website traffic using SQL and Excel queries.
- Analyzed data trends to inform content development and enhance decision-making.
- Built dashboards for article performance and user engagement trends.
- Cleaned data from learning platform reports and content databases.
Education
Bachelor of Engineering - Artificial Intelligence & Machine Learning
Methodist College of Engineering & Technology - Hyderabad, India
05-2025
Intermediate
Sultan-ul-Uloom college - Hyderabad, India
01-2021
High School (10th)
St. George's Grammar School - Hyderabad, India
01-2019
Skills
Web Development
JavaScript Frameworks
Programming: Python
SQL
C++
Databases: MySQL
MongoDB
Tools: Git
Certification
- Advanced software engineering job Simulation - PepsiCo
- Cybersecurity essentials - Mastercard
- CCNA: Switching, routing, and wireless essentials
- CCNA: Enterprise networking, security, and automation
- Introduction to IoT (Cisco)
Languages
English, Fluent, Hindi, Fluent, Urdu, Fluent
Major Project
Facial Age, Gender and Emotion Recognition using Deep Learning, Designed and developed a real-time computer vision solution using Convolutional Neural Networks (CNNs) for age, gender estimation, gender classification and emotion detection., Implemented depthwise separable convolutions to improve prediction accuracy., Built and trained models using TensorFlow, Keras and Python., Integrated OpenCV for real-time video processing and facial detection., Achieved efficient real-time inference suitable for deployment on # systems.
Timeline
Full Stack Developer Intern
Coral comp
02.2026 - CurrentRead more
Data Analyst
GeeksforGeeks
07.2025 - 11.2025Read more
Methodist College of Engineering & Technology - Bachelor of Engineering, Artificial Intelligence & Machine Learning
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Sultan-ul-Uloom college - Intermediate,
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St. George's Grammar School - High School (10th),
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