What it covers: Machine learning concepts, classification algorithms, regression aglorithms, clustering algorithms, decision trees (a type of machine learning algorithm). Why this course: The Applied Data Science with Python taught you how to visualize and manipulate data, now it's time to find out how to find patterns in it using machine learning algorithms. Course 4: Machine Learning Specialization by College of London What it covers: Pandas Python library (for manipulating data), NumPy library (for numerical computing), Matplotlib library (for visualizing data), data cleaning, Scikit-Learn library (for machine learning algorithms). If you’ve learned some fundamental Python, it’s time to start writing data science specific Python with the Applied Data Science with Python Specialization. Why this course: Python is a general programming language meaning it’s capable of writing many different kinds of programs. Course 3: Applied Data Science with Python What it covers: Installing Python, writing your first Python program, writing various Python data structures. Before you start writing machine learning and data science code, it’s best to learn the fundamentals of Python. Why this course: A large amount of machine learning and data science is done in the Python programming language. Course 2: Python for Everybody Specialization What it covers: Techniques on how to approach learning a new subject, such as, focused and diffused thinking. Why this course: If you’re going to be learning online, you better learn how to learn.
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