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Python Courses
These Python courses teach essential syntax, data structures, and libraries like pandas and NumPy through interactive coding exercises. You’ll write scripts to automate tasks, clean data, and build robust applications from scratch.
1M+ learners
Hands-on projects
No credit card required
4.8
Recommended Path for Beginners
Start your python journey with these expert-curated learning paths.
Data Scientist (Python)
Analyze complex datasets and build predictive models by applying statistics and machine learning to deliver end-to-end data science solutions.
38 courses
26 projects 435k
Data Engineer (Python)
Design, build, and automate reliable data pipelines with Python, SQL, and cloud-ready tooling for production workloads.
29 courses
12 projects 121.2k
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Explore All Python Courses
Introduction to Algorithms
Evaluate algorithm time and space complexity in Python, trade memory for speed, and design efficient solutions for data engineering workflows.
8 hours
5.9k
PostgresSQL for Data Engineering
Build hands-on PostgreSQL skills for data engineering by designing tables, loading CSV data, and managing databases beyond SQLite.
8 hours
19k
Optimizing PostgreSQL Databases
Optimize PostgreSQL performance by diagnosing slow queries, using EXPLAIN, indexing tables, and applying core database internals in practice.
5 hours
3.9k
NumPy for Data Engineering
Apply NumPy array operations to process large datasets efficiently, perform fast numerical computations, and optimize Python workflows for data engineering.
4 hours
3k
Processing Large Datasets In Pandas
Optimize pandas workflows to handle larger datasets by reducing memory usage, processing data in chunks, and combining pandas with SQLite.
5 hours
5.6k
Introduction to Unsupervised Machine Learning in Python
Apply unsupervised machine learning techniques by building, evaluating, and interpreting k-means models to segment and explore unlabeled data.
6 hours
3.6k
Linear Regression Modeling in Python
Model and interpret relationships between variables by constructing, evaluating, and applying linear regression for inference and prediction.
4 hours
3.5k
Gradient Descent Modeling in Python
Optimize machine learning models by implementing and applying gradient descent techniques to efficiently train and improve predictive performance.
3 hours
2.8k
Logistic Regression Modeling in Python
Classify and interpret categorical outcomes by constructing, evaluating, and applying logistic regression models for inference and prediction.
4 hours
2.8k
Decision Tree Modeling in Python
Apply decision trees and random forest models to solve classification and regression problems while producing interpretable, high-performing predictions.
6 hours
3.2k
Optimizing Machine Learning Models in Python
Improve machine learning model performance by applying optimization techniques such as cross-validation, regularization, and feature engineering in Python.
4 hours
2.8k
Introduction to Conditional Probability in Python
Extend probability fundamentals to conditional reasoning, independence, and prior knowledge, culminating in a Naive Bayes spam filter.
6 hours
9.1k
Hypothesis Testing in Python
Practice hypothesis testing in Python by running chi-square and permutation tests to evaluate real-world outcomes and statistical significance.
4 hours
10.8k
Introduction to Supervised Machine Learning in Python
Develop a supervised machine learning workflow for classification by training, evaluating, and tuning models with scikit-learn on real-world datasets.
8 hours
14.2k
Data Cleaning and Analysis in Python
Practice cleaning and preparing messy datasets in Python by aggregating, reshaping, and combining data for efficient, real-world analysis.
11 hours
28.5k
Advanced Data Cleaning in Python
Go beyond basic data cleaning by working with messy real-world datasets using advanced Python techniques like regex, lambdas, and list comprehensions.
8 hours
18.7k
Data Cleaning Project Walkthrough
Real datasets are messy. This project-based course walks through cleaning, combining, and preparing data in Python for analysis.
7 hours
19.2k
Data Analysis for Business in Python
Translate ambiguous business questions into measurable metrics and analyses, addressing churn, pricing, and customer behavior with Python.
6 hours
12.8k
Learn Python Courses by Building Projects
Apply your skills to real-world scenarios with these guided projects
Project
Exploring Hacker News Posts
For this project, we’ll step into the role of data analysts to explore Hacker News submissions, analyzing trends using skills in string manipulation, object-oriented programming, and date handling in Python.
8 Steps
Project
Profitable App Profiles for the App Store and Google Play Markets
For this project, we’ll assume the role of data analysts for a company that builds free Android and iOS apps. Our revenue depends on in-app ads, so our goal is to analyze data to determine which kinds of apps attract more users.
14 Steps
Project
Exploring Financial Data using Nasdaq Data Link API
For this project, you’ll become a financial analyst exploring real-world economic data. You’ll use Python to interact with the NASDAQ Data Link API, retrieve financial datasets, then apply Pandas for data wrangling.
10 Steps
Project
Free
Kaggle Data Science Survey
For this project, we’ll act as a data analyst for Kaggle. Kaggle surveyed data scientists about their career status and skills.
8 Steps
Frequently Asked Questions
How do I choose the right Python course for my goals?
The right Python course depends on your goals. If you want to focus on web development, automation, or data visualization, pick a course that emphasizes practical applications rather than just syntax.
Dataquest’s Python courses are designed for data roles and provide hands-on practice with tools like pandas and NumPy.
What is Python?
Python is a high-level python programming language designed to be easy to read and write. It is widely used for data analysis, automation, web development, and machine learning. Python is maintained by the Python Software Foundation, which supports its open-source development and ongoing improvement.
Is Python hard to learn?
Learning Python is not hard. Its clear and readable syntax makes it beginner-friendly, and core concepts like object-oriented programming are introduced gradually to build confidence. Dataquest reinforces learning with hands-on coding exercises so you practice as you go.
What are the best Python courses online?
The best Python courses online focus on active learning rather than passive video watching. Look for courses that let you write and test code throughout each lesson. Dataquest uses an interactive platform that provides instant feedback, helping learners improve quickly and build practical skills.
Are Python skills still in demand?
Yes, Python skills are still in high demand across technology and data-related fields. A strong python skill is essential for careers in data science, analytics, and artificial intelligence. Employers value professionals who understand how to apply Python to real business problems.
What jobs can you get with Python skills?
Python skills can lead to several in-demand roles, including:
- Data Scientist
- Data Analyst
- Python Developer
- Machine Learning Engineer
- Backend Developer
Dataquest focuses on teaching Python programming for data-focused careers that continue to grow.
Which programming language should I learn first?
What is the difference between learning Python for development vs. data science?
Python for development is used to build applications and websites, often with frameworks like Django or Flask. Python for data science is used to analyze data, create models, and automate workflows using libraries like pandas, NumPy, and scikit-learn.
Dataquest focuses on teaching the Python skills most relevant for data-focused careers.
Do I need a technical background before starting Python courses?
No technical background is required to start learning Python. Many beginners start without any experience writing Python code. Dataquest assumes no prior knowledge and teaches concepts step by step.
What tools are commonly used with Python?
Common Python tools for data roles include Jupyter Notebooks, pandas, NumPy, Matplotlib, and scikit-learn. Some learners also use a Python cheat sheet for reference while practicing. Dataquest integrates these tools directly into the learning environment.
What is the best way to learn Python fast?
The best way to learn Python quickly is to practice writing code every day. Consistent practice reinforces concepts and improves retention. Dataquest supports this approach with short lessons and a coding challenge structure that encourages active learning.
How long will it take to become job-ready in Python?
Most learners become job-ready for data analysis roles in three to six months. Data science and engineering roles may require six to twelve months of study. Dataquest’s learning paths help learners stay focused while building practical Python scripts.
How much do Python courses cost?
The cost of Python courses varies by provider and format. Dataquest offers a subscription that includes access to its full curriculum, including Python, SQL, and R. Learners can try introductory content before committing.
Will I get a certificate, and does it help me stand out?
Yes, learners earn a certificate for each completed course, which can serve as a basic Python certification. More importantly, learners build a portfolio of projects that demonstrates real-world skills to employers.