1. Who is this class for?

- This class is designed for a wide range of individuals, including beginners and intermediate learners interested in machine learning.
- It's suitable for those who want to harness the power of data to make data-driven decisions, predictions, and gain valuable insights.
- Whether you're a student, a professional from various fields, or an aspiring data scientist, this class caters to your needs.
2. What will the students learn in this class?

- Students will gain a strong foundation in essential machine learning concepts.
- They will learn data preprocessing techniques, including data cleaning, feature selection, and data visualization.
-The class will cover various machine learning algorithms and their practical applications.
- Students will understand how to select the most appropriate machine learning models for different types of data and tasks.
Practical experience is a key focus, allowing students to work with real datasets, apply machine learning techniques, evaluate model performance, and draw meaningful insights.
3. Is there anything the students need to bring to the class?

- Yes, students are required to bring their own laptops to the class.
Laptops should have Python installed, along with popular machine learning libraries such as scikit-learn, TensorFlow, or PyTorch.
- This hands-on approach enables students to actively participate in practical exercises and apply what they've learned in real-world scenarios.