Welcome to the "Practical Introduction to Machine Learning" course! This course is designed to give students a hands-on introduction to machine learning concepts and techniques.

Course Description This course will provide students with a solid foundation in machine learning, including both theoretical and practical knowledge. Students will learn about the different types of machine learning, such as supervised and unsupervised learning, and will gain experience working with real-world data sets. The course will also cover important concepts such as feature selection, model evaluation, and model deployment.

Course Outcomes By the end of this course, students will be able to:

• Understand the basic concepts and techniques of machine learning
• Apply machine learning algorithms to real-world data sets
• Evaluate the performance of machine learning models
• Select and implement appropriate models for a given problem
• Deploy machine learning models in a production environment

Course Materials

• Lecture Slides (not shared)
• Programming assignments
• Recommended readings
• Additional Resources
  • Quizzes
  • Guest lectures from industry

Course delivery details:

• Course will last for about 10 weeks, depends on how fast we go through the materials
  • If we need more time, you’ll know in the advanced and you will be included in the decision! 🙂