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Home » Technology » Big Data & Data Science » Beginning Data Science with Python and Jupyter

Course Skill Level:

Foundational

Course Duration:

2 day/s

  • Course Delivery Format:

    Live, instructor-led.

  • Course Category:

    Big Data & Data Science

  • Course Code:

    BDSWPJL21E09

Who should attend & recommended skills:

Python beginners

Who should attend & recommended skills

  • This course is designed for beginners who know a little Python and are looking for a quick, fast-paced introduction. Getting started with data science doesn’t have to be an uphill battle.
  • Skill-level: Foundation-level Data Science with Python and Jupyter skills for Intermediate skilled team members. This is not a basic class.
  • Python: Basic (1-2 years’ experience)

About this course

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.

Skills acquired & topics covered

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

Course breakdown / modules

  • Lesson Objectives
  • Basic Functionality and Features
  • Our First Analysis – The Boston Housing Dataset

  • Preparing to Train a Predictive Model
  • Training Classification Models

  • Web Scraping and Interactive Visualizations
  • Lesson Objectives
  • Scraping Web Page Data
  • Interactive Visualizations

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