Ayaan Shaheer
New Delhi
Summary
Results-driven machine learning intern with experience at Future Interns, where I developed advanced sales forecasting and stock price prediction models using Python and Scikit-learn. Proficient in data analysis and visualization, I excel in transforming complex data into actionable insights while collaborating effectively in team environments.
Overview
1
1
year of professional experience
1
1
Certification
Work History
Machine Learning Intern
Future Interns
05.2025 - Current
- Developed a sales forecasting model for a retail business using Python, Prophet, and Scikit-learn.
- Built a stock price prediction model leveraging Pandas, Scikit-learn, and Keras for time series analysis.
- Created a customer support chatbot using TensorFlow and NLTK for natural language processing, integrating it into a web interface and analyzing common customer inquiries to enhance user interaction.
Data Analyst Intern
NullClass
10.2024 - 12.2024
- Developed a real-time analytics project using Python to analyze Google Play Store app data, with insights on user sentiment, ratings, and installs.
- Utilized pandas, matplotlib, seaborn, and Power BI to perform data cleaning, visualization, and interactive dashboard creation.
- Managed code and documentation using GitHub and produced a comprehensive final project report.
Education
Bachelor's - Computer Application
Jamia Hamdard University
New Delhi05.2025
DevOps Bootcamp -
TrainWithShubham
Remote04.2025
CCNA -
PyNet Labs
Remote02.2025
Skills
- Machine learning and artificial intelligence
- Python programming
- Computer vision techniques
- Linux operating system
- DevOps practices
- AWS cloud services
- Cloud computing solutions
Certification
- Responsive web design
- Scientific computing with Python
- CCNA course completion
- DevOps Bootcamp completion
Affiliations
- Technical passion: Led AI projects like a real-time object detection system (85% accuracy) and a fraud detection model (92% precision), balancing rigorous coding with innovative problem-solving
- Continuous learning: actively studying generative AI and LLMs, dedicating evenings to mastering new frameworks like Hugging Face’s Transformers to stay ahead in tech
- Community impact: built an object detection system for visually impaired users, merging my tech skills with a passion for social good
- Physical balance: Practice boxing weekly to stay focused and maintain mental clarity amidst a busy schedule of coding and learning
Projects
Fraud detection ML model: Built a machine learning model using Python and scikit-learn to analyze 6 million financial transactions, achieving 92% precision by handling class imbalance with SMOTE, and deploying via Flask and AWS EC2 for real-time fraud detection
Real-time object detection tracker system: developed a YOLOv11-based system with audio feedback for visually impaired users, achieving 85% detection accuracy, and fully managing research, training, and deployment to assist with navigation
AI Stock Predictor Pro: Developed a web app using Streamlit, Pandas, and Scikit-learn to predict stock prices, featuring custom styling with Plotly visualizations, hosted on GitHub
Langchain chatbot: Designed a conversational AI chatbot using LangChain and Flask, enabling intelligent responses for customer support automation, with a focus on natural language processing
Data visualization pipeline with LLM: this project is a Streamlit-based web application that enables users to upload a dataset (CSV or Excel), ask questions about their data, and generate visualizations using an LLM
Timeline
Machine Learning Intern
Future Interns
05.2025 - Current
Data Analyst Intern
NullClass
10.2024 - 12.2024
Bachelor's - Computer Application
Jamia Hamdard University
DevOps Bootcamp -
TrainWithShubham
CCNA -
PyNet Labs
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