Data Scientist in Python: Online Courses
Learn how to make inferences and predictions from data.
Python
SQL
Machine Learning
This is a Dataquest career path — a sequence of interactive data science courses that’s designed to take you from total beginner to qualified data scientist. You’ll learn to write and run real code, all from the comfort of your browser window.
Made for: Beginners
Prerequisites: None
Join 50,000+ other students enrolled in the last three months!
Your New Skills
You’ll learn all this and much more in our interactive data science courses:
- Python programming
- SQL queries
- Data analysis and visualization
- Data mining, web scraping, and APIs
- Probability and statistics
- Machine learning
- Deep learning
- Jupyter Notebooks
- Git
- Command line/bash
Your New Portfolio
Predicting the Stock Market
Use machine learning to predict future stock prices
Predicting Home Sale Prices
Use linear regression to predict real estate prices
Performing Market Analysis
Use statistical analysis to identify market opportunities
Analyzing SAT Fairness
Use demographic data and SAT scores to assess testing bias
Building a Handwritten Digits Classifier
Use deep learning to build a system for reading handwritten numbers
Building a Custom Spam Filter
Filtering spam email messages using Naive Bayes
+ many more projects
Start working toward your new career in Data Science.
Start working toward your new career in Data Science.
Start working toward your new career in Data Science.
Learn Interactively
In this career path, our courses will help you learn Python fundamentals, dig into data analysis and data viz, query databases with SQL, study statistics, and build machine learning models in a thoughtful sequence, with each lesson building on the previous one.
Our courses are designed so that there are no prerequisites and no prior experience required. Everything you need to learn, you'll learn on this path!
As you learn, you'll apply each concept immediately by writing code right in your browser that's automatically checked by our system to give you near-instant feedback on your progress.
Learn more about the Dataquest teaching method, and how we differ from other online learning sites.
Become a Data Scientist
This course path covers all of the technical skills you’re likely to need to work as a data scientist, and we’re adding new courses all the time!
Dataquest learners like Francisco, Caitlin, Isaac, Adam, Sunishchal, and many more have used this path to go from working in totally unrelated fields to working as full-time data scientists. And it’s not just about getting a job — Francisco, who got his first data science job four years ago after using Dataquest, says he’s still using his Dataquest skills every day.
Don’t take our word for it! Read what real Dataquest learners have to say about how Dataquest has impacted their lives.
Choosing the Right Data Science Courses
There are lots of options out there for learning data science. Online learning platforms and MOOCs like Coursera, edX, Udemy, etc. tend to be based on "traditional" education, using video lectures to replace in-person ones. Even interactive platforms like Datacamp still haven't fully escaped from the "video lecture" model.
While video lectures work well for some people, Dataquest's no-video approach is based on science that says learners who go hands-on are more likely to succeed than those who learn via lectures.
Another reason we don't teach with videos is that in real-world data science work, you'll frequently be challenged to learn about a new package, function, API, etc. by reading documentation. The vast majority of technical documentation is available in text only, which means that the most effective data scientists need to be well-practiced at reading about these kinds of technical topics. Our platform is designed to help you hone those technical reading skills gradually, rather than teaching you with videos and then tossing you into the documentation deep end when you start your first data science job!
Dive into Data Science and Get Certified!
Sign up for a free account to try any course in this path. To complete courses and earn certificates, you’ll need a Premium subscription, which unlocks all of our course content, practice problems, guided projects, and even access to our Premium-only career forum to help you navigate your path towards becoming a data scientist.
Full List of Data Science Courses:
Python for Data Science: Fundamentals
Learn the basics of Python programming and data science.
FREE
Python for Data Science: Intermediate
Learn the basics of Python programming and data science.
FREE
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.
BASIC
Storytelling Through Data Visualization
Learn how to communicate insights and tell stories using data visualization.
BASIC
Data Cleaning and Analysis
Learn how to clean and combine datasets, then practice your skills.
BASIC
Data Cleaning in Python: Advanced
Learn advanced techniques for cleaning data in Python.
BASIC
Data Cleaning Project Walkthrough
Learn how to clean and combine datasets, then practice your skills.
BASIC
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
BASIC
Text Processing in the Command Line
Learn more about the command line and how to use it in your data science workflow.
BASIC
SQL Fundamentals
Learn the basics of working with SQL databases.
FREE
Intermediate SQL for Data Analysis
Learn to work with multi-table databases.
BASIC
APIs and Web Scraping in Python
Learn how to acquire data from APIs and the web.
BASIC
Statistics: Fundamentals
Learn about sampling, variables and distributions.
BASIC
Statistics Intermediate: Averages & Variability
Learn to summarize distributions, measure variability using variance or standard deviation, and compare values using z-scores.
BASIC
Probability Fundamentals
Learn the fundamentals of probability theory using Python
BASIC
Conditional Probability
Learn about conditional probability, Bayes' theorem, and Naive Bayes.
BASIC
Hypothesis Testing: Fundamentals
Learn more advanced statistical concepts including A/B tests and chi-squared tests for more powerful data analysis.
BASIC
Machine Learning Fundamentals
Learn the fundamentals of machine learning using k-nearest neighbors.
PREMIUM
Calculus for Machine Learning
Learn the calculus necessary for intermediate machine learning techniques like linear regression.
PREMIUM
Linear Algebra for Machine Learning
Learn the linear algebra necessary for intermediate machine learning techniques like linear regression.
PREMIUM
Linear Regression for Machine Learning
Learn how to use the linear regression machine learning model.
PREMIUM
Machine Learning in Python: Intermediate
Dive more into Machine learning.
PREMIUM
Decision Trees
Learn how to construct and interpret decision trees.
PREMIUM
Deep Learning: Fundamentals
Learn the basics of deep neural networks. Includes graph representation, activation functions, multiple hidden layers, and image classification.
PREMIUM
Machine Learning Project
Learn what a complete data science project looks like, from data cleaning to machine learning.
PREMIUM
Kaggle Fundamentals
Learn how to get started with and participate in Kaggle competitions with Kaggle's 'Titanic' competition.
PREMIUM
Functions: Advanced
Learn how to write high-quality functions.
PREMIUM
Command Line: Intermediate
Learn more about the command line and how to use it in your data analysis workflow.
BASIC
Git & Version Control
Learn the basics of Python programming and data science.
BASIC
Spark & Map-Reduce
Learn how to use Apache Spark and the map-reduce technique to clean and analyze large datasets.
PREMIUM
Our Data Science Course Curriculum
As you can see above, our data science curriculum includes all of the required skills for data analysis and data science, starting from scratch. You'll learn Python programming, including mastering key libraries like pandas, numpy, matplotlib, and scikit-learn, as well as key concepts like both object-oriented and functional programming. You'll learn to master writing SQL queries including a variety of joins, union, and much more, including complex queries. You'll master web scraping with Python and BeautifulSoup, and learn to access new data sets using APIs.
You'll also learn the math and statistics required to perform accurate data analysis and run meaningful tests, as well as the calculus needed to understand what's happening under the hood with machine learning algorithms. By the end of the path, you'll be able to do things like explain Bayes' theorem, or use a chi-squared test. And of course, you'll learn how to use all of the most popular machine learning algorithms in scikit-learn to perform ML tasks including linear regression, deep learning, image recognition, predictive analytics, and much more.
But you'll learn much more than just those mandatory technical skills. You'll learn how to use the UNIX command line to streamline your workflow, and how to use Git and Github to enable collaboration between and across teams — skills that'll help set you a part as an effective and efficient data scientist.
You Don't Need a Degree to Succeed!
Earning an undergraduate or Masters degree in data science is a laudable accomplishment. But it is not required to get a job in data science!
And thank goodness it isn't, because degree programs are tremendously expensive. For example:
- A Purdue University Masters in Data Science will cost you more than $47,000 (out of state)
- A University of Rochester MS in Data Science costs more than $51,000
- Carnegie Mellon's Data Science Masters degree costs $25,000 per semester
- Columbia University's MS in Data Science costs over $60,000
And of course, these programs also cost time — typically at least a full year of full-time study.
Some degree programs provide an excellent education. But even if you can afford to take on substantial debt and go a full year without any sort of income, is this the best way to invest your money and time?
If your goal is to work as a data scientist, probably not.
With such high demand for data scientists, hiring managers tend not to care much where or how you learned your skills. All they care about is that you actually have the skills required to do the job.
Thankfully, you'll finish the Dataquest data science course path with a portfolio projects that prove you do have those skills, and more!
So why spend $25,000 to $50,000 per year on a university degree when you could learn the same skills faster and more effectively on your own time with Dataquest, and still end up with the job in data science you're looking for?
Here, there's no application process. There's nothing you need to wait for. You don't even need a credit card to get started. Sign up now and start learning data science for free!