Embarking on a career in Artificial Intelligence (AI) or Machine Learning (ML) starts with a solid foundation. The Machine Learning Specialization offers exactly that – a comprehensive online program designed for beginners to grasp the fundamentals and apply them to real-world AI challenges. This specialization serves as an ideal Machine Learning Class to launch your journey into this exciting field.
Taught by the renowned AI visionary Andrew Ng of DeepLearning.AI and Stanford Online, this program provides an updated and expanded version of his highly-rated pioneering Machine Learning course. You’ll learn to build machine learning models using Python, leveraging popular libraries like NumPy and scikit-learn. The curriculum covers supervised learning techniques, including linear and logistic regression, essential for prediction and binary classification tasks.
This 3-course Specialization delves into modern machine learning, encompassing supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and crucial best practices honed in Silicon Valley. You’ll gain insights into evaluating and tuning models and adopting a data-centric approach to enhance performance.
By completing this Machine Learning Specialization, you will not only master key machine learning concepts but also acquire the practical skills to effectively tackle complex, real-world problems. If you’re seeking a robust and accessible machine learning class to enter the AI domain or advance your machine learning career, this Specialization is the perfect starting point.
