Big Data Applications: Machine Learning at Scale

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 portf

Created by: Alexey A. Dral

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Overall Score : 70 / 100

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Course Description

Machine learning is transforming the world around us. To become successful, you'd better know what kinds of problems can be solved with machine learning, and how they can be solved. Don't know where to start? The answer is one button away.During this course you will:- Identify practical problems which can be solved with machine learning- Build, tune and apply linear models with Spark MLLib- Understand methods of text processing- Fit decision trees and boost them with ensemble learning- Construct your own recommender system.As a practical assignment, you will - build and apply linear models for classification and regression tasks; - learn how to work with texts; - automatically construct decision trees and improve their performance with ensemble learning; - finally, you will build your own recommender system!With these skills, you will be able to tackle many practical machine learning tasks.We provide the tools, you choose the place of application to make this world of machines more intelligent.Special thanks to:- Prof. Mikhail Roytberg, APT dept., MIPT, who was the initial reviewer of the project, the supervisor and mentor of half of the BigData team. He was the one, who helped to get this show on the road.- Oleg Sukhoroslov (PhD, Senior Researcher at IITP RAS), who has been teaching MapReduce, Hadoop and friends since 2008. Now he is leading the infrastructure team.- Oleg Ivchenko (PhD student APT dept., MIPT), Pavel Akhtyamov (MSc. student at APT dept., MIPT) and Vladimir Kuznetsov (Assistant at P.G. Demidov Yaroslavl State University), superbrains who have developed and now maintain the infrastructure used for practical assignments in this course.- Asya Roitberg, Eugene Baulin, Marina Sudarikova. These people never sleep to babysit this course day and night, to make your learning experience productive, smooth and exciting.

Instructor Details

Alexey A. Dral

Alexey Dral is the Founder and CEO of BigData Team ( He also the Head of Big Data and Machine Learning and the Senior Lecturer at Moscow Institute of Physics and Technologies. His 10 year working experience for the top Russian and international companies, including Amazon AWS, Yandex, Rambler and qualification on large-scale problems, leading R&D teams, defining strategy for the whole departments build up a great mentor with an aspiration to offer insights to his students. He teaches around the globe, launches new onsite and online courses to reduce the gap between industry and academia, supervise Data Science and Data Engineering initiatives. For instance, he is personally responsible for AI RoadMap at one of the biggest Russian financial institutes. Information about BigData Team. BigData Team provides 3 types of services: online course development, in-campus course development and BigData & Machine Learning research, development and consultations. BigData Team partners are the market leaders. For instance: - Yandex - the biggest Russian search engine company. We collaborate on online course development. See "Big Data for Data Engineers" Coursera specialization. - BigData Team provide courses and give lectures on Big Data and Machine Learning for top Russian universities (MSU, HSE, MIPT, ...) as well as for corporate clients (Sberbank, Megafon, -). BigData Team courses available on English (Harbour.Space University). BigData Team company is the edu



68 total reviews

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By Pramod W on 24-May-18

many things was impressive

By sekhar on 27-Mar-18

Excellent course

By on 8-Jul-18

Course contained lots of new information for me, but exercises were too simple in comparison with other courses of specialization.

By Egor M on 3-Nov-17

Oh, that lovely accent

By Alberto B on 17-Sep-18

Needs more examples and to reduce the speed in many subjects.

By Evgeniy C on 2-Sep-18

need more simple examples and literature links

By Rami on 1-Aug-18

It was good. People made lot of work on it...

By Kiselyov A on 23-May-19

Nice course, but the impression about practical tasks is really awful. The tasks are ok, but grading system is too buggy

By Mykola K on 23-Aug-19

I wish there were more practice

By Paulo H C on 13-Jul-19

Lack of clarity on how to answer questions both in quiz and programming

By Marco G on 5-Dec-18

The videos are good, it's just the assignments that are frustrating.I spent at least 10 times as long trying to get them to pass the autograder as I did solving them.You need to improve this aspect of the course if you're expecting 4 or 5-star reviews :)

By Martin T on 26-Sep-18

The assignments are not clear and the teacher support is poor (despit the slack channel being a welcome improvement!).