Data Science Prerequisites – Numpy, Matplotlib, and Pandas in Python
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In this 4 hr course, you will learn the fundamental tools of the NumPy stack, including NumPy, Matplotlib, Pandas, and SciPy, to aid in your journey into data science and machine learning. The course integrates tutorials and practical exercises to teach numerical computation, data manipulation, and visualization skills.
What I will be able to do after this course
Understand and use NumPy for numerical operations, including matrices and systems of equations.
Become proficient in data visualization using Matplotlib, covering graphs, plots, and image representation.
Learn to handle and manipulate datasets effectively with Pandas, focusing on DataFrame operations.
Gain familiarity with statistical and probability methods using SciPy to analyze distributions and hypotheses.
Develop foundational knowledge of machine learning basics, understanding models for classification and regression.
Course Instructor(s)
Lazy Programmer is an experienced educator in data science and machine learning topics. With a strong background in AI, he has designed courses that blend theory with practical application, ensuring learners gain hands-on experience. His teaching approach emphasizes clarity and connecting concepts to industry-relevant use cases.
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