Skill Path

Analyze Data with Python

Learn to analyze and visualize data using Python and statistics.

Includes Python, NumPy, SciPy, MatPlotLib, Jupyter Notebook, and more.

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This skill path includes
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5,327 learners enrolled
This skill path includes
  • Skill level

    Intermediate
  • Time to complete

    Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary
     
    13 hours
  • Projects

    12
  • Prerequisites

    1 course
     
    We suggest you complete the following courses before you get started with Analyze Data with Python:
    • Learn Python for Data Science

About this skill path

Data is everywhere, and more companies than ever are tracking and analyzing data to inform their decisions. In this Skill Path, you will learn to analyze data statistically and create meaningful data visualizations. You will use industry standard Python libraries including MatPlotLib, NumPy and SciPy. Along the way, you will apply these skills to real-world cases and build your data portfolio. Plus, now you can build your prompt engineering skills and get hands-on experience writing, testing, and refining prompts directly in the course.

Skills you'll gain

  • Describe datasets statistically
  • Communicate insights visually
  • Test hypotheses for significance
  • Run A/B tests from start to finish

Syllabus

8 units • 15 lessons • 12 projects • 11 quizzes
  • 1

    Welcome to the Analyze Data with Python Skill Path

    Get started with the Analyze Data with Python Skill Path.

  • 2

    NumPy: A Python Library for Statistics

    Learn about NumPy, a Python library used to store arrays of numbers, organize large amounts of data, and perform statistical calculations.

  • 3

    Data Visualization with Matplotlib

    Make effective, customized data visualizations in Python with Matplotlib.

  • 4

    Statistics for Data Analysis

    Learn how to calculate and interpret several descriptive statistics using the Python library NumPy.

  • 5

    Hypothesis Testing with SciPy

    Learn SciPy, a Python module for comparative statistics, in order to perform many different statistical tests in code.

  • 6

    Learn How to use AI for Data Analysis

    Learn how to use AI for data analysis.

  • 7

    Analyze Data with Python Portfolio Project

    Create a data analysis project for your portfolio.

  • Certificate of completion available with Plus or Pro

    Earn a certificate of completion and showcase your accomplishment on your resume or LinkedIn.

The platform

Hands-on learning

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Earn a certificate of completion

Show your network you've done the work by earning a certificate of completion for each course or path you finish.
  • Show proofReceive a certificate that demonstrates you've completed a course or path.
  • Build a collectionThe more courses and paths you complete, the more certificates you collect.
  • Share with your networkEasily add certificates of completion to your LinkedIn profile to share your accomplishments.

Reviews from learners

  • The progress I have made since starting to use codecademy is immense! I can study for short periods or long periods at my own convenience - mostly late in the evenings.
    Chris
    Codecademy Learner @ USA
  • I felt like I learned months in a week. I love how Codecademy uses learning by practice and gives great challenges to help the learner to understand a new concept and subject.
    Rodrigo
    Codecademy Learner @ UK
  • Brilliant learning experience. Very interactive. Literally a game changer if you're learning on your own.
    John-Andrew
    Codecademy Learner @ USA

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    We’ve hand-picked the content in each Skill Path to fast-track your journey and help you gain a new skill in just a few months.

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What's included in skill paths

  • Practice Projects

    Guided projects that help you solidify the skills and concepts you're learning.
  • Assessments

    Auto-graded quizzes and immediate feedback help you reinforce your skills as you learn.
  • Certificate of Completion

    Earn a document to prove you've completed a course or path that you can share with your network.