Data Science at Scale Specialization

Learn scalable data management, evaluate big data technologies, and design effective visualizations.

This Specialization covers intermediate topics in data science. You will gain hands-on experience with scalable SQL and NoSQL data management solutions, data mining algorithms, and practical statistical and machine learning concepts. You will also learn to visualize data and communicate results, and you’ll explore legal and ethical issues that arise in working with big data. In the final Capstone Project, developed in partnership with the digital internship platform Coursolve, you’ll apply your new skills to a real-world data science project.

Coursera

University of Washington

Communicating Data Science Results (Coursera)

Statistics & Data Analysis Data Science

Unlock the secrets of effective communication in data science! This course teaches you how to interpret your results accurately, present them clearly, and use powerful visualization techniques to inform business decisions. Whether you're a seasoned professional or just starting out, our expert-led sessions will equip you with the skills needed to make your insights impactful.

Jun 8th 2026

3 Weeks

Ethics Cloud Computing Privacy

Coursera

University of Washington

Data Manipulation at Scale: Systems and Algorithms (Coursera)

Statistics & Data Analysis Data Science

Dive into the world of big data analytics with 'Data Manipulation at Scale: Systems and Algorithms'. This course will equip you with the knowledge and skills needed to effectively manage, analyze, and manipulate large volumes of data using cutting-edge systems and algorithms. Learn how to harness powerful computing resources and programming abstractions to extract valuable insights from complex datasets.

Jun 8th 2026

4 Weeks

Algebra Algorithms Databases

Coursera

University of Washington

Practical Predictive Analytics: Models and Methods (Coursera)

Statistics & Data Analysis Data Science

Dive into the world of data science with 'Practical Predictive Analytics: Models and Methods'. This course is designed for those eager to learn how to design statistical experiments, analyze results using advanced techniques, and avoid common misinterpretations in big data. Gain a core understanding of practical machine learning methods and apply them to real-world problems.

Jun 8th 2026

4 Weeks

Machine Learning Models Methods

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