Key Responsibilities:

● Deliver live interactive sessions on:

○ Python (beginner → advanced)

○ Machine Learning fundamentals

● Cover essential ML libraries:

○ NumPy, Pandas

○ Matplotlib / Seaborn

○ Scikit-learn

● Teach Machine Learning concepts, including:

○ Supervised vs Unsupervised Learning

○ Regression (Linear, Logistic)

○ Classification algorithms

○ Clustering techniques

● Explain concepts with:

○ Real-world examples

○ Practical datasets

○ Hands-on coding sessions

● Guide students in building end-to-end ML projects, including:

○ Data cleaning & preprocessing

○ Model building

○ Evaluation & improvement

● Focus on intuition behind algorithms, not just library usage

● Handle student doubts and ensure high engagement