Applied Data Science with Python and Jupyter

Course 1263

  • Duration: 1 day
  • Language: English
  • Level: Foundation
Get This Course 7.200 kr
  • 1-day instructor-led training course
  • One-on-one after course instructor coaching
  • jun 13 10:00 - 17:30 CEST
  • Guaranteed to Run - you can rest assured that the class will not be cancelled.
    jun 27 15:00 - 22:30 CEST
    New York or AnyWare
  • aug 15 15:00 - 22:30 CEST
    Herndon, VA or AnyWare
  • sep 12 10:00 - 17:30 CEST
  • okt 17 15:00 - 22:30 CEST
    Ottawa or AnyWare
  • dec 12 10:00 - 17:30 CET
  • dec 20 15:00 - 22:30 CET
    New York or AnyWare
  • feb 13 15:00 - 22:30 CET
    Herndon, VA or AnyWare
  • mar 20 10:00 - 17:30 CET

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Attend this Applied Data Science with Python and Jupyter training course and 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. You will also learn about creating reproducible data processing pipelines, visualisations, and prediction models, all with the goal of giving you the skills and exposure you’ll need for the real world.

Data Science is one of the fastest growing professions across all industries. Open source tools like Python have become increasingly popular, and when paired with Jupyter Notebooks, can provide a variety of data-science applications. Attend this one-day hands-on course and learn to leverage all that these powerful tools have to offer.

  • Knowledge of programming fundamentals and some experience with Python, including Python libraries, Pandas, Matplotlib, and scikit-learn.

Applied Data Science with Python and Jupyter Delivery Methods

  • After-course instructor coaching benefit

Applied Data Science with Python and Jupyter Course Benefits

  • Jupyter Fundamentals
  • Data Cleaning and Advanced Modelling
  • Web Scraping and Interactive Visualisations
  • Machine learning classification strategy
  • Exploratory data analysis and investigation

Applied Data Science with Python and Jupyter Training Outline

  • Basic Functionality and Features
  • Our First Analysis - The Boston Housing Dataset
  • Preparing to Train a Predictive Model
  • Training Classification Models
    • Scraping Web Page Data

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    Course FAQs

    Python developers write the code necessary to develop applications using Python's built-in statements, functions, and collection types. Python is also a very popular language for data analytics.

    No. This course is intended for people who already know the basics of Python Programming. This course will teach you the basics of Data Analysis.