Are you eager to dive into the world of machine learning but feeling a bit overwhelmed by the math and statistics? Don't worry, you're not alone! Many aspiring data scientists find these topics daunting. The good news is, there's a plethora of free online courses that can help you build a solid foundation.

Coursera:

Machine Learning by Andrew Ng: This legendary course not only introduces you to machine learning concepts but also provides a strong mathematical underpinning.
Mathematics for Machine Learning by Imperial College London: If you're seeking a deep dive into the mathematical concepts, this course is a great choice.

edX:

Introduction to Machine Learning by Microsoft: This course offers a balanced approach, combining machine learning fundamentals with the necessary mathematical knowledge.
Fundamentals of Data Science by Columbia University: A broader perspective on data science, including statistics and machine learning, is provided in this course.
MIT OpenCourseWare:

Introduction to Algorithms: While not strictly about machine learning, this course lays a strong foundation in algorithms and data structures, essential for understanding machine learning concepts.
Probability and Random Variables: A deep dive into probability theory is crucial for understanding many machine learning algorithms.

Khan Academy:

Linear Algebra: A comprehensive resource for learning linear algebra, a fundamental topic in machine learning.

Calculus: Another essential mathematical concept, calculus is covered in detail on Khan Academy.

Statistics and Probability: A solid understanding of statistics and probability is vital for data analysis and machine learning.

Remember: While these courses offer valuable resources, consistent practice and hands-on experience are key to mastering these topics. Start with the basics and gradually increase the complexity as you gain confidence. With dedication and the right resources, you'll be well on your way to becoming a skilled machine learning practitioner.

Happy learning!