Isha Sharma
Tech-savvy student exploring new innovations | Engineering Student
✨ My Journey So Far
2023 – Google Data Analytics Certification – Coursera
Gained practical exposure to data cleaning, analysis, and visualization. Built an analytics project using Google Sheets and Tableau for sales trend prediction.
2021 – B.E. in Computer Science – BITS Pilani
Pursuing core courses in Data Structures, Operating Systems, and Machine Learning. Member of the coding club and contributor to campus tech events.
2019 – Senior Secondary (CBSE) – Delhi Public School, R.K. Puram
Completed schooling with a focus on Physics, Chemistry, and Mathematics. Scored 94% in Class 12 and served as the Technology Club Secretary.
🧩 Proof of Work
Mobile App for Event Management – BITS Pilani
I was part of a college innovation initiative at BITS Pilani, Isha Sharma designed and developed a user-friendly mobile app to streamline event management for college festivals and seminars. The app allows event coordinators to post details, manage RSVPs, send out reminders, and assign roles within organizing teams. This project I was particularly impactful during the college’s tech fest where the app I was used by over 300 students. Isha focused on creating an intuitive interface with Google UX Design principles, enabling ease of use and efficient communication. The backend I was built using Firebase to ensure real-time updates and secure data storage. Through this project, Isha demonstrated a strong ability to bridge the gap between user needs and technical development, embodying both creativity and practical engineering skills.
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Predictive Stock Market Model
I undertook a personal research project, Isha Sharma explored the power of artificial intelligence by creating a predictive model to forecast stock prices. Using historical stock data, she trained multiple machine learning algorithms such as Random Forest and LSTM networks to identify patterns and project future market trends. The model I was evaluated for accuracy against real-time stock data from January to March 2023, achieving over 80% precision on short-term predictions. This project not only deepened her knowledge in data preprocessing and model evaluation but also sparked her interest in financial analytics and fintech applications. The work combined technical rigor with practical application, showcasing her ability to convert theoretical concepts into impactful solutions. It stands out as an excellent early demonstration of her technical potential.
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