1. Fundamental Understanding:
• Acquire a solid understanding of foundational concepts in statistics, probability, and linear algebra as they pertain to machine learning and AI.
• Grasp the essentials of data preprocessing, model evaluation, and optimization techniques.
2. Skill Development:
• Master the basics of Python programming for machine learning.
• Develop the ability to apply machine learning algorithms to real-world data.
3. Application Mastery:
• Gain competency in predictive analytics through hands-on projects.
4. Project Execution:
• Successfully build a predictive model to interpret and analyze data for making informed predictions.
5. Preparation for Advanced Learning:
• Establish a strong foundation for exploring more advanced topics in machine learning and AI in the future.
Section 1. Introduction to Machine Learning and AI with Python