About
I’m currently pursuing my B.Tech in Computer Science, specializing in Artificial Intelligence and Machine Learning. I enjoy building projects where I can take what I learn in class and actually turn it into something that works. I’ve worked on projects involving machine learning, computer vision and software development. Some of them include a fake news detection system using machine learning, an AI-driven GIS platform for disaster-risk and relocation planning, and an animal detection system built using YOLOv8. Working on these projects has given me practical experience with Python, Flask, FastAPI, APIs, data processing and ML model development. Right now, I’m especially interested in growing my skills in AI/ML, Agentic AI, software development, cloud technologies and deployment. I’m also actively looking for internship opportunities where I can work on real problems, learn how professional development teams operate, and contribute what I already know. I learn best by building, experimenting and figuring things out when they don’t work the first time. I’m always open to connecting with developers, recruiters and other people working in technology.
Education
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Bachelor of Technology (B.Tech)Computer Science and Engineering · Aug 2024 – May 2028
Skills
Tools / apps / platforms
- Git <3 months
- GitHub <3 months
- Google Colab <3 months
- Jupyter Notebook <3 months
- Visual Studio Code <3 months
Languages
- English Conversational Speak
- Shona Conversational Speak
Projects
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Python, Scikit-learn, Pandas, TF-IDF, Logistic Regression, Flask, HTML, CSS
Built a web-based system that classifies news articles as real or fake using machine learning. I cleaned and prepared a dataset of over 44,000 news articles, converted the text into TF-IDF features, and trained a Logistic Regression model that achieved 98.77% test accuracy. I also built the Flask application used to send user input to the model and display the prediction.
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Python, YOLOv8, Computer Vision, OpenCV, ESP32-CAM, Flask
Developed a computer-vision system for detecting animals that may enter crop fields, including cows, wild boars, monkeys, parrots and donkeys. I worked with a custom YOLOv8 model for detection and connected the AI side of the project with an ESP32-CAM-based hardware setup. The project also includes a dashboard for viewing detections, timestamps, recent activity and detection history.
Courses & certifications
- Core Java · Cipher Schools · 2026
- Artificial Intelligence From Basics to Agentic AI · Lovely Professional University · 2019