Venkata Tharun Kumar Reddy Seelam

Enthusiastic software engineer with a solid foundation in object-oriented programming, full-stack development, and AI. Proficient in Python, JavaScript, and modern web technologies, with hands-on experience in building scalable web applications. Currently deepening expertise in Artificial Intelligence through a specialization in AI and Machine Learning. Looking to contribute to a dynamic team in a junior developer role, where I can apply my knowledge and continue growing my skills.

• Artificial Intelligence Specialization (in progress), Coursera – Andrew Ng’s AI & Machine Learning, 08/2024 - Present
• The Complete Node.js Developer Course, Udemy, 08/2022 - 10/2022
• Data Structures A-Z, Udemy, 03/2022 - 06/2022
• Learn Python in 5 Days, Udemy, 04/2023

Solid foundation in OOP concepts and principles, applied across Java and Python projects., Experience with developing complete web applications using MERN stack., Proficient in designing, managing, and querying databases with MySQL and MongoDB., Currently learning key concepts such as supervised/unsupervised learning, model training, and neural networks.

• English, Full Professional Proficiency
• Telugu, Native Proficiency
• Hindi, Professional Working Proficiency

• Software Development
• Full Stack Engineering
• AI & Machine Learning
• Frontend & Backend Development
• Continuous Learning and Exploring New Technologies

Portfolio Website, 08/2023 - 11/2023, Developed a fully responsive React-based portfolio showcasing my skills and projects, using modern web technologies like Tailwind CSS for styling and GitHub for version control. Student Internship Portal, 08/2022 - 12/2022, Created a full-stack application to facilitate internship opportunities for students. Implemented a secure user authentication system, integrated job listings, and handled data storage with MySQL. AI-Powered Image Classifier (In Progress), 09/2024 - Present, Working on a machine learning project that uses a convolutional neural network (CNN) to classify images. Leveraging TensorFlow and Keras, the model is trained on the CIFAR-10 dataset.