Aadip Thapaliya

I believe AI is best learned through a mix of theory and hands-on practice. In my lessons, I combine clear explanations of key concepts with coding exercises, projects, and real-world applications.

Teaching Methods:

Step-by-step explanations of AI and machine learning concepts.

Practical coding in Python with libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch.

Project-based learning (chatbots, image recognition, recommendation systems, etc.).

Interactive problem-solving, quizzes, and discussions to reinforce understanding.

Personalized feedback and guidance tailored to your goals.

Content Covered:

Basics of Python and data handling.

Machine learning algorithms (linear regression, decision trees, clustering, etc.).

Deep learning and neural networks.

Natural language processing (NLP) and computer vision.

Real-world applications of AI in business, research, and technology.

Teaching Dynamics:
My lessons are interactive, student-centered, and adapted to your pace. I encourage asking questions and experimenting with ideas. We’ll balance theory with practical coding so that you not only understand “how AI works” but also “how to build with AI.”

Teaching Experience:
I have experience teaching students at different levels from beginners just starting with coding to advanced learners working on AI projects. My goal is to make AI accessible, engaging, and career-focused, whether you’re learning for academic success, professional development, or personal interest