I have successfully completed a 6-week Internship on Front-End Web Development, conducted by Edunet Foundation in collaboration with All India Council for Technical Education (AICTE) and IBM SkillsBuild.
During this internship, I gained hands-on experience in:
💻 Building responsive and interactive web pages
⚙️ Working with HTML, CSS, and JavaScript
🚀 Developing and deploying front-end projects
This internship gave me an excellent opportunity to strengthen my technical and problem-solving skills in web development.
Completed a virtual internship program focused on industry-oriented training, project execution, and skill development. Gained practical experience through guided tasks, assignments.
Completed the SQL Subqueries course, learning to write optimized queries, work with complex datasets, and handle real-world database operations using advanced SQL concepts.
Presented a research paper at an international conference, gaining exposure to academic discussions and contributing insights on emerging technologies through professional research work.
I was chosen to participate in the NxtWave Hackathon, where I worked on real-life problem statements and collaborated with developers to design innovative tech solutions. This experience enhanced my creativity, teamwork, and practical development skills.
Successfully completed an NLP course covering text preprocessing, tokenization, classification, and application of Natural Language Processing techniques in real-world projects.
Successfully completed a Web Development course covering HTML, CSS, JavaScript, and responsive design principles to build dynamic and user-friendly websites.
Learned the principles of Object-Oriented Programming using Python, including classes, objects, inheritance, polymorphism, and real-world applications of OOP concepts.
Completed an HTML fundamentals course, learning the structure of webpages, semantic tags, and essential concepts required to build clean and professional web interfaces.
Gained foundational knowledge in Machine Learning, including data preprocessing, supervised algorithms, model evaluation, and practical insights into building ML-based solutions.