I am a Data Science and AI/ML aspirant with a strong foundation in programming, data analysis, and machine learning concepts. I am actively building practical experience by working on real-world datasets, implementing end-to-end machine learning pipelines, and experimenting with modern AI frameworks.

My primary interests include statistical modelling, predictive analytics, deep learning, and applied artificial intelligence. I focus on writing clean, scalable code and continuously improving my understanding of algorithms, data structures, and model optimization techniques.

I use this GitHub space to document my learning journey, showcase projects, and collaborate on data-driven solutions that create measurable impact. I am particularly interested in roles and opportunities that allow me to apply data science and AI to solve complex, real-world problems.

Core Skills & Tools:

Programming: Python

Data Analysis: Pandas, NumPy, Matplotlib, Seaborn

Machine Learning: Scikit-learn, model evaluation & tuning

Deep Learning (learning & practice): TensorFlow / PyTorch

Databases & Tools: SQL, Git, Jupyter Notebook

Concepts: Statistics, Linear Algebra, Feature Engineering