Path overview
In this path, you will gain experience in manipulating, comparing, and presenting compelling and actionable data and you’ll discover the best methods for visualizing data using line graphs, histograms, bar charts, scatter plots, and more.
Best of all, you’ll learn by doing — you’ll write code and get feedback directly in the browser. You’ll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview.
Key skills
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Programming with Python to manipulate data
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Using the Python libraries Pandas and NumPy for data analysis
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Using the most common data visualization techniques to explore data
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Using data visualization to convey insights and tell a story
The Dataquest guarantee
Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you'll master data skills and grow your career.
We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren't satisfied with your outcome, we'll give you a refund.
Master skills faster
with Dataquest
Go from zero to job-ready
Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.
Build your project portfolio
Build confidence with our in-depth projects, and show off your data skills.
Challenge yourself with exercises
Work with real data from day one with interactive lessons and hands-on exercises.
Showcase your path certification
Impress employers by completing a capstone project and certifying it with an expert review.
Path outline
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Projects in this path
Learning resources
8 Skills You Need to Become a Data Analyst
Learn the key skills required to get a job as a Data Analyst.
Read Article5 Essential Data Skills for the 21st Century
Here are five core skills for working with data that can benefit everyone
Read ArticleAn Objective Comparison Between R vs Python for Data Analysis
Determine whether R or Python will work better for you.
Read Article11 Design Tips for Data Visualization
Here are some easy techniques to make your data look better.
Read ArticleLearner testimonials
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for learners who complete a path
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