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Working in a hands-on learning environment, led by our Data Science with Python and Jupyter expert instructor, students will learn about and explore: Get up and running with the Jupyter ecosystem and some example datasets. Learn about key machine learning concepts like SVM, KNN classifiers and Random Forests. Discover how you can use web scraping to gather and parse your own bespoke datasets.

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Last Updated

January 6, 2021

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Certification

Course Description

Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world. We'll finish up by showing you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context.

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Course Curriculum

    • Jupyter Fundamentals 00:00:00
    • Lesson Objectives 00:00:00
    • Basic Functionality and Features 00:00:00
    • Our First Analysis – The Boston Housing Dataset 00:00:00
    • Data Cleaning and Advanced Machine Learning 00:00:00
    • Preparing to Train a Predictive Model 00:00:00
    • Training Classification Models 00:00:00
    • Web Scraping and Interactive Visualizations 00:00:00
    • Lesson Objectives 00:00:00
    • Scraping Web Page Data 00:00:00
    • Interactive Visualizations 00:00:00

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