Data Scientist in Python

Fast track your career and stand out from the crowd by adding Python for data science to your skill repertoire. Whether you’re a complete beginner looking to start a new career or a seasoned expert looking to hone your skills, this career path is designed to rapidly transform you into a qualified, job-ready data scientist.

Write and run real code, and build a portfolio employers will love — all from the comfort of your browser.

  • Build a foundation in Python, command line, and SQL fundamentals
  • Study statistics, probabilities, and machine learning
  • Discover deep learning, Apache Spark, and Kaggle fundamentals
  • Explore data cleaning, visualization, and storytelling
  • Construct a portfolio to help you land the job

Unsure if the data scientist career path is the right one for you? Take our career path quiz here

50,000+ people have enrolled in this path in the last three months! Join them today!

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What You’ll Learn

Navigating the path to learn data science can be time-consuming, difficult, and downright frustrating — but not with Dataquest. With our data science career path, we teach every skill required to become an exceptional data scientist, including Python programming, data analysis, probabilities, statistics, and more!

Everything you’ll ever need to know to become a data scientist is right here.

  • Python programming
  • Data analysis and visualization
  • Data mining, web scraping, and APIs
  • Jupyter Notebooks
  • Command-line/bash
  • SQL queries
  • Probability and statistics
  • Machine learning
  • Deep learning
  • Git
  • Statistics

How Our Data Scientist in Python Career Path Works

Master mandatory data scientist technical skills like Python and object-oriented and functional programming. Along the way, you’ll also learn key libraries such as scikit-learn, Matplotlib, NumPy, and pandas. Moreover, discover everything you need to know about web scraping and SQL queries in our Python data science courses. 

These courses will teach you the calculus needed to understand, explain, and complete tasks like machine learning algorithms, image recognition, deep learning, and predictive analytics, among others.

Most data science programs stop there, since those are all the skills needed to become a data scientist, but we took it a step further. To differentiate yourself even more from other candidates, we included concepts such as the UNIX command line, Git, and Github to develop collaboration and efficiency.

At Dataquest, we know that navigating a brand new career path is a lot to process, so we teach differently. All of our courses are hands-on and interactive. Say goodbye to dull, lengthy videos. With Dataquest, you’ll be writing and running real code and validating your new skills daily. If you get stuck, we’ll provide the support you need. Here’s how the data scientist curriculum is set up:

  • Our Python data science career path consists of a series of courses that include intro to Python for beginners all the way to advanced Python for data science.
  • You’ll be writing real code and answering practice problems that’ll help you master specific skills required for data science.
  • 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 be issued a certificate that you can share with your professional network or use to enhance your resume.
  • After completing the entire path, you’ll be armed with all the skills necessary to become a data scientist!

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

Data Scientist 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 important Python data science skills.

Pandas & NumPy Fundamentals

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

FREE + BASIC

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 the basics of the 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 more about the command line and how to use it in your data science 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.

Machine Learning Fundamentals

Learn the fundamentals of machine learning using k-nearest neighbors.

Calculus for Machine Learning

Learn the calculus necessary for intermediate machine learning techniques like linear regression.

Linear Algebra for Machine Learning

Learn the linear algebra necessary for intermediate machine learning techniques like linear regression.

Linear Regression for Machine Learning

Learn how to use the linear regression machine learning model.

Machine Learning in Python: Intermediate

Dive more into Machine learning.

Decision Trees

Learn how to construct and interpret decision trees.

Deep Learning: Fundamentals

Learn the basics of deep neural networks. Includes graph representation, activation functions, multiple hidden layers, and image classification.

Machine Learning Project

Learn what a complete data science project looks like, from data cleaning to machine learning.

Kaggle Fundamentals

Learn how to get started with and participate in Kaggle competitions with Kaggle's 'Titanic' competition.

Functions: Advanced

Learn how to write high-quality functions.

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.

Spark & Map-Reduce

Learn how to use Apache Spark and the map-reduce technique to clean and analyze large datasets.

Who is this Data Scientist in Python Career Path For?

The data scientist career path starts you out at the beginning, which means that it can be for anyone. There is no experience required to start. 

This career path is for individuals who are ready for an exciting career switch, data professionals who are looking to advance in their field, college students pursuing data science who want to get job-ready, and more! 

Start learning with our Data Scientist in Python Career Path!

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