Data Science at Scale 专项课程
Tackle Real Data Challenges。Master computational, statistical, and informational data science in three courses.
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.
- Intermediate Specialization.
- Some related experience required.
第 1 门课程
课程概述Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the progra
第 2 门课程
- 4 weeks of study, 6-8 hours/week
课程概述Statistical experiment design and analytics are at the heart 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 statis
第 3 门课程
课程概述Important note: The second assignment in this course covers the topic of Graph Analysis in the Cloud, in which you will use Elastic MapReduce and the Pig language to perform graph analysis over a moderately large dataset, about 600GB. In order to complete
第 4 门课程
大规模数据科学 - 毕业项目计划开课班次：Jul 2
- 6 weeks of study, 3-4 hours/week
毕业项目介绍In the capstone, students will engage on a real world project requiring them to apply skills from the entire data science pipeline: preparing, organizing, and transforming data, constructing a model, and evaluating results. Through a collaboration
Director of Research
More questions? Visit the Learner Help Center.