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Introduction to Data Science in Python

Dive into data science using Python and learn how to effectively analyze and visualize your data. No coding experience or skills needed.

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4 Hours13 Videos44 Exercises323,264 Learners3700 XPData Analyst TrackData Skills for Business TrackPython Programmer Track

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Course Description

Begin your journey into Data Science! Even if you've never written a line of code in your life, you'll be able to follow this course and witness the power of Python to perform Data Science. You'll use data to solve the mystery of Bayes, the kidnapped Golden Retriever, and along the way you'll become familiar with basic Python syntax and popular Data Science modules like Matplotlib (for charts and graphs) and pandas (for tabular data).

  1. 1

    Getting Started in Python


    Welcome to the wonderful world of Data Analysis in Python! In this chapter, you'll learn the basics of Python syntax, load your first Python modules, and use functions to get a suspect list for the kidnapping of Bayes, DataCamp's prize-winning Golden Retriever.

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    Dive into Python
    50 xp
    Importing Python modules
    100 xp
    Correcting a broken import
    100 xp
    Creating variables
    50 xp
    Creating a float
    100 xp
    Creating strings
    100 xp
    Correcting string errors
    100 xp
    Valid variable names
    50 xp
    Fun with functions
    50 xp
    Load a DataFrame
    100 xp
    Correcting a function error
    100 xp
    Snooping for suspects
    100 xp
  2. 2

    Loading Data in pandas

    In this chapter, you'll learn a powerful Python libary: pandas. pandas lets you read, modify, and search tabular datasets (like spreadsheets and database tables). You'll examine credit card records for the suspects and see if any of them made suspicious purchases.

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  3. 3

    Plotting Data with Matplotlib

    Get ready to visualize your data! You'll create line plots with another Python module: Matplotlib. Using line plots, you'll analyze the letter frequencies from the ransom note and several handwriting samples to determine the kidnapper.

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  4. 4

    Different Types of Plots

    In this final chapter, you'll learn how to create three new plot types: scatter plots, bar plots, and histograms. You'll use these tools to locate where the kidnapper is hiding and rescue Bayes, the Golden Retriever.

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In the following tracks

Data Analyst Data Skills for BusinessPython Programmer


mona-kayMona Khalil
Hillary Green-Lerman Headshot

Hillary Green-Lerman

Lead Data Scientist, Looker

Hillary is a Lead Data Scientist at Looker. She is an expert in creating a data-driven product and curriculum development culture, having previously built the Product Intelligence team at Knewton from the ground up. She enjoys explaining data science in a way that is understandable to people with both PhDs in Math and BAs in English.
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What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden
Harvard Business School

DataCamp is by far my favorite website to learn from.

Ronald Bowers
Decision Science Analytics, USAA