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Data Science at Scale

Bill Howe

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.

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What's inside

Four courses

Data Manipulation at Scale: Systems and Algorithms

(0 hours)

Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making. Extracting knowledge from large, heterogeneous, and noisy datasets requires powerful computing resources and programming abstractions to use them effectively. This course covers the landscape of relevant systems, the principles on which they rely, their tradeoffs, and how to evaluate their utility against your requirements.

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Practical Predictive Analytics: Models and Methods

(0 hours)

Statistical experiment design and analytics are the foundation of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts.

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Communicating Data Science Results

Making predictions is not enough! Effective data scientists know how to explain and interpret their results, and communicate findings accurately to stakeholders to inform business decisions. Visualization is the field of research in computer science that studies effective communication of quantitative results by linking perception, cognition, and algorithms to exploit the enormous bandwidth of the human visual cortex.

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Data Science at Scale - Capstone Project

(0 hours)

In the capstone, students will work on a real-world project that requires them to apply skills from the entire data science pipeline, including preparing, organizing, and transforming data, constructing a model, and evaluating results. These projects will not be straightforward and the outcome is not prescribed, but students will need to tolerate ambiguity and negative results.

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Time

66 hours

Level

Intermediate

Via

Coursera

Institution

University of Washington

Instructor

Bill Howe

Level

Intermediate

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