Course Overview:

This course provides a comprehensive introduction to the exciting fields of Artificial Intelligence (AI) and Machine Learning (ML). Students will delve into the foundations, theories, and applications of AI and ML, gaining the knowledge and skills necessary to design and develop intelligent systems and algorithms.

Course Objectives:

• Understand the fundamentals of Artificial Intelligence and its various subfields.
• Explore the principles and algorithms used in Machine Learning.
• Learn how to analyze, preprocess, and transform data for ML applications.
• Gain hands-on experience in implementing and training ML models.
• Discover advanced ML techniques such as deep learning and reinforcement learning.
• Explore real-world applications of AI and ML in various industries.
• Understand the ethical implications and considerations of AI and ML.
• Stay up-to-date with the latest trends and developments in AI and ML.

Course Modules:

1. Introduction to Artificial Intelligence
2. Introduction to Machine Learning
3. Data Preprocessing and Feature Engineering
4. Supervised Learning Algorithms
5. Unsupervised Learning Algorithms
6. Deep Learning and Neural Networks
7. Reinforcement Learning
8. Natural Language Processing
9. AI and ML in Industry
10. Ethical Considerations in AI and ML

Course Materials:

The course includes video lectures, readings, hands-on exercises, and assignments to reinforce learning.

Course Requirements:

• Basic programming knowledge (preferably in Python).
• Familiarity with linear algebra and statistics.
• A computer with internet access and a modern web browser.
• Optional: Prior experience in data analysis or machine learning.

Join us on this exciting journey into the world of Artificial Intelligence and Machine Learning!