Data science course for beginners: the 10 best in 2026

Best for beginners who want Python for data analysis with lots of practice. It goes from knowing nothing about Python to analyzing data in Jupyter Notebook, with code-along lessons, multiple projects, practice exercises and quizzes on each section.

It has 4.5 stars from 172 reviews and about 600 students. It runs about 14 hours with 16 quizzes and was last updated in March 2025.

Best for absolute beginners who want a gentle first step with Python. It shows how to set up Jupyter Notebook, import libraries, work with tabular data, explore and manipulate pandas DataFrames and Series, clean data and visualize it.

It has 4.2 stars from more than 400 reviews and more than 41,000 students. It runs about four and a half hours, the shortest course here, and was updated in March 2026.

Best for beginners who want to learn machine learning through projects. It starts with crash courses in Python, NumPy, pandas, Matplotlib, Seaborn and Plotly, then covers regression, decision trees, random forests, SVM, KNN, boosting with XGBoost and CatBoost, clustering with k-means and DBSCAN, PCA, and introductions to deep learning and NLP.

It has 4.5 stars from 375 reviews and more than 14,000 students. It runs about 32 hours and was updated in September 2026.

Best for beginners who want a day-by-day plan. Over 100 days it covers the data science workflow, Python including web scraping, probability and distributions, data cleaning, exploratory analysis and visualization, hypothesis tests, preprocessing, machine learning maths and models from regression to XGBoost and clustering, deep learning basics, SQL and Power BI.

It has 4.3 stars from more than 700 reviews and more than 8,800 students. It runs about 49 hours with 108 quizzes and assessments, and was updated in July 2026. School-level algebra is required.

Best for beginners with some programming who want a classic hands-on path. It covers Python, NumPy, pandas, Excel files, web scraping, SQL from Python, Matplotlib, Seaborn and Plotly, then scikit-learn models from linear regression and k-nearest neighbors to random forests, SVMs, NLP and neural networks.

It has 4.5 stars from more than 161,000 reviews and more than 836,000 students, the most on this list. It runs about 25 hours. It joined the list through our second round because it was last updated in May 2020, and we lowered it slightly because it expects some programming.

Best for motivated beginners who want to go all the way to advanced AI. It covers the maths behind machine learning, classic ML algorithms, NLP, deep learning, reinforcement learning and transformer models, with TensorFlow, PyTorch and scikit-learn, hyperparameter tuning and real-world projects.

It has 4.5 stars from more than 28,000 reviews and more than 169,000 students. It runs about 101 hours, the longest course here, with 20 quizzes and 167 resources, and was updated in August 2026. We lowered it because of its length and because it expects some programming.

Best for beginners who want a short overview before committing. It lays out a structured path into data science and covers statistics for interpreting data, visualization, machine learning with Python, SQL and why the cloud matters for data scientists, with exercises and challenges.

It has 4.5 stars from more than 9,700 reviews and more than 35,000 students. It runs about five hours and was last updated in February 2025.

Best for beginners who want deep coverage of machine learning fundamentals. It teaches Python and pandas for data handling, then regression, classification and cluster analysis in detail, automatic model creation and text and emotion mining, using Anaconda cloud notebooks.

It has 4.9 stars from more than 1,700 reviews, the highest rating here, and more than 9,300 students. It runs about 60 hours with 94 resources and was updated in October 2026. It requires only basic arithmetic.

Best for beginners who want data analytics, data science and AI in one course. It covers data analysis, Python, cleaning and exploratory analysis, visualization, probability and statistics, machine learning, deep learning with TensorFlow, generative AI and NLP, SQL, Power BI and Excel, with 11 capstone projects such as bank churn analysis and a GenAI chatbot.

It has 4.8 stars from more than 5,300 reviews and more than 12,000 students. It runs about 65 hours with 154 quizzes and two practice tests, and was updated in September 2026. We lowered it slightly because its length is a lot for beginners.