BigData Team
Deep dive into Big Data, Machine Learning
and Software Development with experts.
Solve practical tasks and become Data Science
or Data Engineer!
and Software Development with experts.
Solve practical tasks and become Data Science
or Data Engineer!
© BigData Team
Onsite Courses & Workshops
New technologies evolves so fast, that nobody can move with the same speed. Nobody can know everything about it. For this reason we put together our big and all-round team. All together we can explain everything. What is of most importance we can explain where you can and cannot use these technologies.
Do you wonder what Machine Learning (ML), Artificial Intelligence (AI) or Big Data is, but missing a good explanation on simple English? Request a course or workshop for your company.
Our instructors are Chief Data Scientists / Team Leads / R&D Engineers at companies such as Amazon AWS, Sberbank, Yandex. We also give lecturers at the state and corporate universities. Examples are Moscow Institute of Physics and Technology (MIPT), Yandex School of Data Analysis (YSDA), Higher School of Economics (HSE), Sberbank Corporate University, Harbour.Space. University, ...
Courses are available online.
Big Data Analysis: MapReduce, Spark, BigTable/HBase, Distributed Data Analysis
During this course, the students will master and sharpen their knowledge in basic technologies of the modern Big Data landscape, namely: HDFS, MapReduce, Spark, NoSQL. The subject of particular interest during this course is efficient data warehousing using Hive, Spark SQL and Spark Dataframes.
Big Data Analysis - Alexey Dral
Online Courses (MOOC)
In comparison to existing online courses we would like to provide listeners with practical skills and knowledge. Therefore, we develop our own software for educational purposes. For instance, we can spawn Hadoop or Spark cluster in the cloud and integrate it with an educational platform.
Big Data for Data Engineers
Yandex and BigData Team have developed and launched courses on Big Data on Coursera. They are the first ever international massive online courses with the access to real computational cluster.
HSE and MIPT (State Universities) already use it in the form of flipped classroom. Sberbank recommends these courses for their employees.
HSE and MIPT (State Universities) already use it in the form of flipped classroom. Sberbank recommends these courses for their employees.
Big Data Essentials: HDFS, MapReduce and Spark RDD
In this 6-week course you will:
- learn about distributed file systems, why they exist and what function they serve;
- grasp the MapReduce framework, a workhorse for many modern Big Data applications;
- learn about Spark, the next-generation computational framework;
- develop skills to apply these tools to creating solutions in finance, social networks, telecommunications and many other fields.
- learn about distributed file systems, why they exist and what function they serve;
- grasp the MapReduce framework, a workhorse for many modern Big Data applications;
- learn about Spark, the next-generation computational framework;
- develop skills to apply these tools to creating solutions in finance, social networks, telecommunications and many other fields.
Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames
This course will teach you how to:
- Warehouse your data efficiently using Hive, Spark SQL and Spark DataFframes;
- Work with large graphs, such as social graphs or networks;
- Optimize your Spark applications for maximum performance.
- Warehouse your data efficiently using Hive, Spark SQL and Spark DataFframes;
- Work with large graphs, such as social graphs or networks;
- Optimize your Spark applications for maximum performance.
Big Data Applications: Real-Time Streaming
After you finish this course, you will master stream processing systems and NoSQL databases. You will also learn how to use such popular and powerful systems as Kafka, Cassandra and Redis.
To get the most out of this course, you need to know Hadoop and SQL. You should also have a working knowledge of bash, Python and Spark.
Do you want to learn how to build Big Data applications that can withstand modern challenges?
The course is currently closed.
To get the most out of this course, you need to know Hadoop and SQL. You should also have a working knowledge of bash, Python and Spark.
Do you want to learn how to build Big Data applications that can withstand modern challenges?
The course is currently closed.
Research & Development
Big Data and Machine Learning are inevitable components of a modern business. If you would like to expand your business or review existing initiatives, you can request consulting, research and even outsource development.
Projects (customers are not disclosed):
- AI RoadMap, financial institute (TOP-3 in Russia), consulting;
- chat-bot, pharmacy chain (TOP-3 in Russia), development;
- ML and optimization for agriculture supply chain (TOP-3 in Russia), R&D;
- Blockchain platform scalability, Blockchain-startup, research;
- architecture and software development best practices, ML-startups, consulting;
- storage and data pipeline optimization, telecom (TOP-3 in Russia), R&D.
Projects (customers are not disclosed):
- AI RoadMap, financial institute (TOP-3 in Russia), consulting;
- chat-bot, pharmacy chain (TOP-3 in Russia), development;
- ML and optimization for agriculture supply chain (TOP-3 in Russia), R&D;
- Blockchain platform scalability, Blockchain-startup, research;
- architecture and software development best practices, ML-startups, consulting;
- storage and data pipeline optimization, telecom (TOP-3 in Russia), R&D.
We work under CRISP-DM methodology
The first phase is a consulting stage:
- [Business Understanding] choose / develop business KPI and ML metrics (consider imbalanced problems, ability to setup A/B-testing with existing infrastructure / business process);
- [Data Understanding] data transfer, data sources and format understanding, tooling for data visualization, data validation.
All other phases are CRISP-DM cycles until deployment stage.
- [Business Understanding] choose / develop business KPI and ML metrics (consider imbalanced problems, ability to setup A/B-testing with existing infrastructure / business process);
- [Data Understanding] data transfer, data sources and format understanding, tooling for data visualization, data validation.
All other phases are CRISP-DM cycles until deployment stage.
Team
Alexey Dral
Founder & СEO
- 10 years of IT experience (Amazon AWS, Yandex, Rambler);
- instructor and author of a number educational courses on Machine Learning / Big Data / programs for Chief Data Officers (MSU, HSE, MIPT, YSDA, Harbour.Space University, University NTI 20.35);
- Head of international online course "Big Data for Data Engineers" in collaboration with Yandex;
- Agency of Strategic Initiatives at Russian Federation, expert;
CV: Alexey_Dral.pdf
- instructor and author of a number educational courses on Machine Learning / Big Data / programs for Chief Data Officers (MSU, HSE, MIPT, YSDA, Harbour.Space University, University NTI 20.35);
- Head of international online course "Big Data for Data Engineers" in collaboration with Yandex;
- Agency of Strategic Initiatives at Russian Federation, expert;
CV: Alexey_Dral.pdf
BigData Team: Senior Instructors
Anton Gorokhov
Big Data Instructor
• Senior SDE, Yandex
• ex. PhD, Associate Professor, MIPT
• ex. PhD, Associate Professor, MIPT
Artyom Vybornov
Big Data Instructor
• Lead Software Engineer, Rambler&Co
• Co-author "Big Data for Data Engineers" (Coursera)
• Co-author "Big Data for Data Engineers" (Coursera)
Pavel Klemenkov
Big Data Instructor
• Chief Data Scientist (Data Platform), NVIDIA.
• Founder, Moscow Spark
• Co-author "Big Data for Data Engineers" (Coursera)
• Founder, Moscow Spark
• Co-author "Big Data for Data Engineers" (Coursera)
Andrey Titov
Big Data Instructor
• Senior Spark Engineer, NVIDIA
• Active Member of Moscow Spark
• ex. Lead Data Engineer, Data Processing Platform, Otkritie FC Bank
• Active Member of Moscow Spark
• ex. Lead Data Engineer, Data Processing Platform, Otkritie FC Bank
Dmitry Ignatov
Machine Learning Instructor
• Laboratory head: Laboratory for Models and Methods of Computational Pragmatics, HSE, department of Artificial Intelligence and Data Analysis
• Author of more than 50 scientific articles (Machine Learning magazine, Expert Systems and Applications, Discrete Applied Mathematics, General Systems)
• Author of more than 50 scientific articles (Machine Learning magazine, Expert Systems and Applications, Discrete Applied Mathematics, General Systems)
Kirill Vlasov
Machine Learning Instructor
Partners
ASI
"We have been working with the BigData Team for several years now on Russian and international projects. Alexey was a instructor at our CDO track on "Island 10-21", "Island 10-22" and "Winter Island". He is a member of the expert jury of the Digital Solutions Competition and World AI&Data Challenge. The team also made a great contribution to our methodological recommendations for data based management implementation. We are confident that the cooperation with the BigData Team will only grow stronger, and together we will be able to develop the competence of authorities and data community in terms of the culture of working with data and making competent decisions based on it" - Yana Kovalenko.
Shakhmardan Yessenov Foundation
"Big Data Team excellently demonstrates expert level of professional skills, high organization, efficient decision making, and individual approach to the summer school participants.
It is important to note:
- the ability to communicate complex aspects of Machine Learning and Big Data;
- interactive teaching methods;
- general positivity of the learning process;
- focus on practical skills" - Aiganym Malisheva.
It is important to note:
- the ability to communicate complex aspects of Machine Learning and Big Data;
- interactive teaching methods;
- general positivity of the learning process;
- focus on practical skills" - Aiganym Malisheva.
MegaFon
Innopolis University
Models and Methods of Computational Pragmatics Lab
American Center in Moscow
Skyeng School
MeetSpeakers
CROC Education Solutions
Moscow Python
Collaboration on Python-related programs.
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Videos on Big Data
Fintech Deepdive: The Banking Perspective
Big Data Analysis by Alexey Dral, 2018
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