Machine Learning Using Python

This course introduces students to the fundamental concepts of Machine Learning (ML) using Python. The course covers the key ML algorithms, techniques, and libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, and TensorFlow. By the end of this course, students will be able to build, evaluate, and deploy machine learning models to solve real-world problems.

Course Objectives:

• Learn the basics of Python programming for data analysis and machine learning.
• Understand the fundamental concepts of machine learning, including supervised and unsupervised learning.
• Gain practical knowledge of popular machine learning algorithms such as regression, classification, clustering, and deep learning.
• Develop the ability to analyze datasets, preprocess data, and implement machine learning models using Python libraries.
• Get hands-on experience with model evaluation and optimization techniques.
• Learn to deploy machine learning models in real-world applications.