Data Science Lab (WorldQuant)
A free, self-paced, project-based lab from WorldQuant University for learners with beginner Python and basic statistics who want applied practice.
Learn the full data science workflow, from analysis and statistics to predictive machine learning models.
A free, self-paced, project-based lab from WorldQuant University for learners with beginner Python and basic statistics who want applied practice.
Study data science in R through nine HarvardX courses, covering statistics, visualization, machine learning, and a final capstone project.
An advanced, three-hour course where Netflix data scientist Jeff Li and Ken Jee link ML algorithms to business cases and code models from scratch.
A four-hour intermediate DataCamp course on time series in Python, from autocorrelation and AR/MA models to cointegration, with finance examples.
Hands-on Python course on k-means, hierarchical clustering, t-SNE, PCA and NMF with scikit-learn, ending in a music artist recommender.
Hands-on 4-hour DataCamp course teaching classification, regression, tuning, and pipelines in scikit-learn with real datasets in Python.
A 7-course Google certificate teaching Python, statistics, regression, and machine learning for advanced data analyst roles.
One of Udemy's best-known ML courses, covering regression, classification and clustering in both Python and R with template-based coding.
Five University of Michigan courses teaching Python for data analysis, visualization, machine learning, text mining and network analysis.
A three-course beginner program from DeepLearning.AI and Stanford Online covering supervised, unsupervised and neural network methods in Python.
A beginner-level Stanford course covering descriptive stats, probability, regression, and hypothesis tests, taught across 12 self-paced modules.
A three-course University of Michigan series teaching statistical visualization, inference, and regression modeling in Python, at beginner level.
A long-running Udemy course teaching R programming fundamentals for data science, covering structures, visualization and basic statistics.
Build in-demand Excel skills through four Macquarie University courses covering formulas, dashboards, automation, and data analysis.
A DataCamp track teaching pandas, NumPy and data cleaning techniques for analysts moving from spreadsheets or SQL into Python-based.
A Duke University Coursera course bridging Excel and SQL, teaching the same analytic techniques in both tools so spreadsheet users learn.
A UC Davis Coursera course teaching SQL specifically for data analysis workflows, covering querying, joining and aggregating real datasets.
A free-tier-friendly, interactive introduction to SQL covering SELECT, WHERE, JOIN and GROUP BY, taught through in-browser coding exercises.
A beginner-friendly Udemy bootcamp teaching Python, SQL, Power BI, Tableau, AWS, Snowflake, and statistics for practical data analysis work.
A 23-course Python learning path covering data manipulation, visualization, statistics, and machine learning for aspiring data scientists.
A project-based, mentor-supported Nanodegree covering the data science workflow end to end, with real-world projects reviewed by human.
A 12-course IBM program teaching Python, SQL, and machine learning skills to help you break into an entry-level data science career.
A 9-course Google path teaching data cleaning, SQL, Python, and Tableau, built to prepare complete beginners for entry-level analyst roles.
Launch your career in data analysis with expert-led training, hands-on projects, and an accredited certification.
Enhance your data analysis skills with hands-on Excel training, perfect for beginners looking to gain practical knowledge.
Discover how machine learning can transform business strategies and enhance decision-making without needing a programming background.
Data Science & Machine Learning is the technical core of working with data. This pillar brings together everything you need to move from raw datasets to models that predict and explain: exploratory data analysis, the statistics and linear algebra behind the algorithms, classical supervised and unsupervised learning, and time series forecasting. You will find beginner bootcamps that assume no prior coding experience alongside advanced specialisations for practitioners who already ship models. Compare courses by tool (Python, R, SQL), by level, and by whether they lead to a recognised certificate, then pick the path that matches the role you are aiming for.