课程信息
3.9
48 个评分
12 个审阅
专项课程

第 3 门课程(共 5 门)

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
高级

高级

完成时间(小时)

完成时间大约为24 小时

建议:5 weeks of study, 6-8 hours/week...
可选语言

英语(English)

字幕:英语(English)
专项课程

第 3 门课程(共 5 门)

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
高级

高级

完成时间(小时)

完成时间大约为24 小时

建议:5 weeks of study, 6-8 hours/week...
可选语言

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 7 分钟

Welcome

...
Reading
5 个视频 (总计 7 分钟)
Video5 个视频
Course Structure1分钟
Meet Alexey2分钟
Meet Pavel分钟
Meet Ilya1分钟
完成时间(小时)
完成时间为 1 小时

(Optional) Machine Learning: Introduction

...
Reading
6 个视频 (总计 43 分钟), 1 个阅读材料
Video6 个视频
(Optional) Basic concepts11分钟
(Optional) Types of problems and tasks5分钟
(Optional) Supervised learning7分钟
(Optional) Unsupervised learning6分钟
(Optional) Business applications of the machine learning4分钟
Reading1 个阅读材料
Slack Channel is the quickest way to get answer to your question10分钟
完成时间(小时)
完成时间为 5 小时

Spark MLLib and Linear Models

...
Reading
11 个视频 (总计 94 分钟), 3 个阅读材料, 5 个测验
Video11 个视频
First example. Linear regression10分钟
How MLlib library is arranged10分钟
How to train algorithms. Gradient descent method9分钟
How to train algorithms. Second order methods8分钟
Large scale classification. Logistic regression12分钟
Regularization8分钟
PCA decomposition9分钟
K-means clustering7分钟
How to submit your first assignment3分钟
How to Install Docker on Windows 7, 8, 104分钟
Reading3 个阅读材料
Grading System: Instructions and Common Problems10分钟
Docker Installation Guide10分钟
Assignments. General requirements10分钟
Quiz4 个练习
Large scale machine learning. The beginning14分钟
Large scale regression and classification. Detailed analysis10分钟
Regularization and Unsupervised Techniques10分钟
Spark MLLib and Linear Models18分钟
2
完成时间(小时)
完成时间为 2 小时

Machine Learning with Texts & Feature Engineering

...
Reading
12 个视频 (总计 70 分钟), 5 个测验
Video12 个视频
Welcome1分钟
Feature Engineering for Texts, part 17分钟
Feature Engineering for Texts, part 25分钟
N-grams4分钟
Hashing trick6分钟
Categorical Features6分钟
Feature Interactions2分钟
Spark ML. Feature Engineering for Texts, part 17分钟
Spark ML. Feature Engineering for Texts, part 25分钟
Spark ML. Categorical Features3分钟
Topic Modeling. LDA.7分钟
Word2Vec11分钟
Quiz5 个练习
Feature Enginering for Texts16分钟
Categorical Features & Feature Interactions6分钟
Spark ML Tutorial: Text Processing6分钟
Advanced Machine Learning with Texts8分钟
Machine Learning with Texts & Feature Engineering20分钟
3
完成时间(小时)
完成时间为 6 小时

Decision Trees & Ensemble Learning

...
Reading
13 个视频 (总计 64 分钟), 6 个测验
Video13 个视频
Welcome1分钟
Decision Trees Basics4分钟
Decision Trees for Regression6分钟
Decision Trees for Classification3分钟
Decision Trees: Summary1分钟
Bootstrap & Bagging8分钟
Random Forest6分钟
Gradient Boosted Decision Trees: Intro & Regression7分钟
Gradient Boosted Decision Trees: Classification6分钟
Stochastic Boosting1分钟
Gradient Boosted Decision Trees: Usage Tips & Summary3分钟
Spark ML. Decision Trees & Ensembles6分钟
Spark ML. Cross-validation3分钟
Quiz5 个练习
Decision Trees16分钟
Bootstrap, Bagging and Random Forest6分钟
Gradient Boosted Decision Trees10分钟
Spark ML Programming Tutorial: Decision Trees & CV6分钟
Decision Trees & Ensemble Learning16分钟
4
完成时间(小时)
完成时间为 3 小时

Recommender Systems

...
Reading
15 个视频 (总计 118 分钟), 1 个阅读材料, 4 个测验
Video15 个视频
Recommender Systems, Introduction. Part II4分钟
Non-Personalized Recommender Systems9分钟
Content-Based Recommender Systems8分钟
Recommender System Evaluation10分钟
Collaborative Filtering RecSys: User-User and Item-Item10分钟
RecSys: SVD I7分钟
RecSys: SVD II8分钟
RecSys: SVD III5分钟
RecSys: MF I7分钟
RecSys: MF II6分钟
RecSys: iALS I6分钟
RecSys: iALS II11分钟
RecSys: Hybrid I7分钟
RecSys: Hybrid II7分钟
Reading1 个阅读材料
Recommender Systems. Spark Assignment10分钟
Quiz4 个练习
Basic RecSys for Data Engineers14分钟
Moderate RecSys for Data Engineers10分钟
Advanced RecSys for Data Engineers4分钟
Recommender Systems16分钟

讲师

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Pavel Mezentsev

Senior Data Scientist
PulsePoint inc
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Alexey A. Dral

Founder and Chief Executive Officer
BigData Team
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Ilya Trofimov

Principal Data Scientist
Yandex
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Evgeny Frolov

Data Scientist, PhD Student @Skoltech
Computational and Data Intensive Science and Engineering

关于 Yandex

Yandex is a technology company that builds intelligent products and services powered by machine learning. Our goal is to help consumers and businesses better navigate the online and offline world....

关于 Big Data for Data Engineers 专项课程

This specialization is made for people working with data (either small or big). If you are a Data Analyst, Data Scientist, Data Engineer or Data Architect (or you want to become one) — don’t miss the opportunity to expand your knowledge and skills in the field of data engineering and data analysis on the large scale. In four concise courses you will learn the basics of Hadoop, MapReduce, Spark, methods of offline data processing for warehousing, real-time data processing and large-scale machine learning. And Capstone project for you to build and deploy your own Big Data Service (make your portfolio even more competitive). Over the course of the specialization, you will complete progressively harder programming assignments (mostly in Python). Make sure, you have some experience in it. This course will master your skills in designing solutions for common Big Data tasks: - creating batch and real-time data processing pipelines, - doing machine learning at scale, - deploying machine learning models into a production environment — and much more! Join some of best hands-on big data professionals, who know, their job inside-out, to learn the basics, as well as some tricks of the trade, from them. Special thanks to Prof. Mikhail Roytberg (APT dept., MIPT), Oleg Sukhoroslov (PhD, Senior Researcher, IITP RAS), Oleg Ivchenko (APT dept., MIPT), Pavel Akhtyamov (APT dept., MIPT), Vladimir Kuznetsov, Asya Roitberg, Eugene Baulin, Marina Sudarikova....
Big Data for Data Engineers

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