So let’s see some of the best resources you can use to learn about these. Therefore, a solid grasp of math and statistics is essential for success in data science. Without a strong understanding of these concepts, data scientists may struggle to derive meaningful insights from data, leading to incorrect or biased conclusions. Mathematics, especially linear algebra and calculus, is necessary to understand and implement algorithms such as gradient descent and singular value decomposition that underpin machine learning. For data scientists to create models, derive insights, and make predictions from data, they must have a solid understanding of statistical concepts like probability, regression, and hypothesis testing. It offers the tools required to accurately analyze and interpret data, enabling reasoned decision-making. Learn Math’s & Statistics for Data Scienceĭata science is built on math and statistics, which are fundamental to the field. What you’ll learnĪll the videos for this course are available on YouTube and all the Slides, source code, and etc. However, CS50P focuses exclusively on Python and can be taken before, during, or after CS50x. This course is part of the CS50x curriculum, which focuses on computer science and programming with various languages including C, Python, SQL, and JavaScript. No software is required except for a web browser or a personal computer. Exercises are inspired by real-world programming problems. It covers topics such as variables, conditionals, loops, functions, debugging, unit tests, and file input/output. This is a self-paced free course that will introduce you to the world of programming using the most popular language used for Data Science, Python! It is designed for both beginners and experienced programmers who want to learn Python. CS50’s Introduction to Programming with Python The course videos of an older version of the same course (2018) is available on YouTube for FREE. The course aims to teach students how to program fundamentally and how to learn new languages. Problem sets are inspired by various fields, such as the arts, humanities, social sciences, and sciences.
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The course begins with the fundamental language of C, followed by Python, SQL, HTML, CSS, and JavaScript. Topics covered include computational thinking, abstraction, algorithms, data structures, and computer science in general. The course emphasizes problem-solving, correctness, design, and style. Courses Introduction to Computer Science – Harvard’s CS50ĬS50 is an introductory course to computer science and programming from Harvard University, suitable for those with or without prior programming experience.