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Data Analysis in Python: Using Numpy for Analysis
  • Level Intermediate
  • Duration 3 hours
  • Offered by

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This Guided Project Data Analysis in Python: Using Numpy for Analysis is for Intermediate Python learners. In this 1-hour long project-based course, you will learn how to: Transform 1 and 2-dimensional data in Python Lists and Dictionaries into Numpy Arrays, leveraging the real world data of the Lakers starting players to calculate their BMIs and their player efficiency rates. To achieve this, we will work through importing all the necessary python libraries and data, transforming 1D and 2D python data structures to Numpy arrays, performing basic arithmetic operations on Numpy arrays, and performing Numpy aggregation. This project is unique because, there are practice tests to use the Golden State Warriors data and in the end, there's a capstone project that leverages real-world data of the top 10 highest-paid NBA players to calculate their BMIs and player efficiencies using the skills learned. In order to be successful in this project, you will need a basic understanding of python syntax for importing python modules, python JSON module, setting variables, and calling methods of python modules.

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Enhance your Python skills with Coursera's "Data Analysis in Python: Using Numpy for Analysis." Designed for intermediate learners, this 180-minute guided project delves into data analysis using Numpy. Ideal for those in IT and Computer Science, it offers free subscription access and expert instruction.