Artificial Intelligence

I have teaching experience in Data Science focused on beginner and intermediate learners. I have taught core concepts such as data analysis, data visualization, machine learning, and basic statistics in a structured and easy-to-understand way.

My teaching starts with Python fundamentals, including data types, loops, and functions. Then I introduce data handling using NumPy and Pandas, where students learn how to clean, explore, and analyze datasets. I also teach data visualization using Matplotlib to help students understand patterns and trends in data.

In machine learning, I cover supervised learning methods such as Linear Regression and Logistic Regression. Students learn how to split data into training and testing sets, train models, and evaluate performance using accuracy and basic metrics.

I emphasize practical learning. Students work on real-world mini projects such as house price prediction, spam email detection, and student performance analysis. This helps them understand how Data Science is applied in real situations.

My teaching approach focuses on:

• Explaining concepts in simple language

• Step-by-step coding demonstrations

• Hands-on practice

• Real dataset examples

• Project-based learning

The goal of my teaching is to help students build a strong foundation in Data Science and gain confidence in working with data and machine learning models.