The technical skills of a data analyst using Python are in massive demand in today’s growing, data-dependent world. This career path is great for beginners and professionals alike, as it starts with the fundamentals and works through advanced topics. Completing this path will set you up for success as a qualified, job-ready data analyst.

Write real code, and build coveted data analyst skills that’ll wow employers — all from the comfort of your browser and at your own pace.

  • Build your knowledge of basic and intermediate Python programming concepts
  • Study statistics, probabilities, and machine learning
  • Discover collaboration tools like Git and SQL databases

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What You’ll Learn

Learning data analysis and relevant topics on your own is difficult, confusing, and unmotivating. Dataquest is here to streamline that process. With our data analyst in Python path, we’ll guide you through each in-demand skill required to be efficient and job-ready as a data analyst. Our courses were chosen based on an analysis of real-world data analyst job postings, to ensure we're covering all the right skills. And each course teaches with real data, challenging you to complete real-world data analysis projects just like the ones you'll be confronting at work.

Here are the most sought-after data skills recruiters look for, and Dataquest teaches all of them:

  • Python programming
  • Data cleaning, analysis, and visualization
  • Web scraping, and APIs
  • Data analysis in business
  • SQL databases
  • Probability and statistics
  • Hypothesis Testing
  • Git & Version Control
  • Command-line/bash
Data Scientist in Python Salary Increase

Data analysts average between $68K to $100K per year according to

Data Scientist in Python Job Openings

Over 120,000 open data analyst roles are listed on LinkedIn

Data Scientist In Python Job Growth

Data analysts projected 20% growth between 2018 and 2028, according to Indeed

How Our Data Analyst in Python Career Path Works

By the time  you finish our program, you’ll have mastered all the skills required to become a data analyst. With our online data analysis courses, you’ll learn the Python fundamentals, dig into data analysis and data visualization using popular packages like pandas, query databases with SQL, and study statistics — among other things!

Navigating a new career path doesn’t have to be intimidating. Dataquest walks you through every step of the way . . . we don’t believe in boring, uninspiring videos. We provide hands-on and interactive teaching, so you’ll be engaged at every step. Not only will you learn in-demand skills, you’ll also have the opportunity to put them into practice.

If you have a hard time on a topic, or if you have any questions, we’re here with the support you need. Here’s a snapshot of our data analyst in Python path curriculum:

  • Our data analyst in Python career path is a series of courses that include Python fundamentals to advanced topics like web scraping and SQL for data analysis — and everything in between.
  • You’ll write real code and answer practice problems to maximize retention. Occasionally redo lessons to help review things you may have forgotten.
  • At the end of each course, you’ll complete a guided project to apply your new skills while building your portfolio to show potential employers.
  • Upon completion of each course, you’ll receive a certificate that you can share with your professional network — or use to enhance your resume.
  •  Once you complete this path, you’ll have the skills necessary to be a data analyst!

Enroll in this career path and become a data analyst in Python today!

Data Analyst Career Path Course List

Python for Data Science: Fundamentals Part I
Learn the basics of Python programming and data science.

Python for Data Science: Fundamentals Part II
Learn the basics of Python programming and data science.

Python for Data Science: Intermediate
Learn the basics of Python programming and data science.

Pandas & NumPy Fundamentals
Learn how to analyze data using the pandas and NumPy libraries..

Exploratory Data Visualization
Learn how to explore data by creating and interpreting data graphics. This course is taught using matplotlib and pandas.

Storytelling Through Data Visualization
Learn how to communicate insights and tell stories using data visualization.

Data Cleaning and Analysis
Learn how to clean and combine datasets, then practice your skills.

Data Cleaning in Python: Advanced
Learn advanced techniques for cleaning data in Python.

Data Cleaning Project Walkthrough
Learn how to clean and combine datasets, then practice your skills.

Elements of the Command Line
Learn Bash to establish a foundation of working the command line as a springboard to using the command line for data science.

Text Processing in the Command Line
Learn about text processing in the command line and how to use it in your data analysis workflow.

SQL Fundamentals
Learn the basics of working with SQL databases.

Intermediate SQL for Data Analysis
Learn to work with multi-table databases.

APIs and Web Scraping in Python
Learn how to acquire data from APIs and the web.

Data Analysis in Business
Learn about the subjective aspects of data science in a business setting.

Statistics: Fundamentals
Learn about sampling, variables and distributions.

Statistics Intermediate: Averages & Variability
Learn to summarize distributions, measure variability using variance or standard deviation, and compare values using z-scores.

Probability Fundamentals
Learn the fundamentals of probability theory using Python.

Conditional Probability
Learn about conditional probability, Bayes' theorem, and Naive Bayes.

Hypothesis Testing: Fundamentals
Learn more advanced statistical concepts including A/B tests and chi-squared tests for more powerful data analysis.

Command Line: Intermediate
Learn more about the command line and how to use it in your data analysis workflow.

Git & Version Control
Learn the basics of Python programming and data science.

Who is this Data Analyst in Python Career Path For?

The data analyst in Python career path starts with the fundamentals and then builds advanced skills. You don’t need any experience to start, and all skill levels are welcome. 

This career path is for individuals ready for a career change, data professionals looking to enhance their skills for the next promotion, and college students who want a massive head start in their data careers.