This course is perfect for those looking to become familiar with Jupyter Notebook and its features to perform data science tasks in Python. Led by Dražen Lucanin, a developer, data analyst, and founder of Punk Rock Dev, learners will start from basic data analysis tasks and work their way up to learn common scientific Python tools. Through the course, learners will work with real datasets, such as crime and traffic accidents in New York City, to explore data scraping and cleaning. By the end, learners will be able to create insightful visualizations and interactive reports to extract useful information from datasets. Don't miss out on this opportunity to learn the fundamentals of data science with Jupyter Notebook!
Jupyter Notebook for Beginners
4.6
Udemy1,258 learners
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This course is perfect for absolute beginners who want to learn about Jupyter Notebook, a powerful tool used by machine learning engineers, data scientists, mathematicians, and Python and R developers. Learners will gain an understanding of the advantages of using Jupyter Notebook, such as its ability to support more than 40 programming languages, its similarity to a physical notebook, and its ability to share and distribute notebooks. Additionally, learners will gain the skills necessary to use Jupyter Notebook in their own projects. With this course, you will be able to take advantage of the powerful features of Jupyter Notebook and use it to create amazing projects.
Wrangling Major League Baseball Pitchf&x Data with Python
4.3
Udemy3,097 learners
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This course is perfect for coders, SaberMetricians, and baseball fans who want to gain insight into the MoneyBall phenomenon and the next wave of player development. Through the use of Python, learners will be able to wrangle MLB PitchF/x data from Clayton Kershaw's 2014 no-hitter and graph the pitches with MatPlotLib and PyPlot. Along the way, learners will also learn best practices for Jupyter Notebook, Python coding, XML parsing, and more. This course provides new learners with an introduction to SaberMetrics, the empirical study of baseball statistics. Don't miss out on this opportunity to explore the world of SaberMetrics and MoneyBall!
Learning Path: Jupyter: Interactive Computing with Jupyter
3.3
Udemy290 learners
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This Learning Path is designed to help new learners understand the Jupyter Notebook, an open-source web application that supports more than 40 programming languages. Dan Toomey, a 20+ year veteran of application development, will guide learners through the process of integrating the Jupyter system with different programming languages, such as R, Python, JavaScript, and Julia. Learners will also learn how to use interactive widgets, namespaces, and work with Jupyter in the multiuser mode. By the end of the course, learners will be able to write code, compute mathematical formulae, create graphics, and view the output, all in a single document and web browser. Click this course to learn how to use Jupyter Notebook and access Big Data with ease!
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