{"id":81855,"date":"2020-05-17T01:42:37","date_gmt":"2020-05-16T23:42:37","guid":{"rendered":"https:\/\/prohoster.info\/blog\/administrirovanie\/12-onlajn-kursov-po-data-engineering"},"modified":"2020-05-17T01:42:37","modified_gmt":"2020-05-16T23:42:37","slug":"12-onlajn-kursov-po-data-engineering","status":"publish","type":"post","link":"https:\/\/prohoster.info\/en\/blog\/administrirovanie\/12-onlajn-kursov-po-data-engineering","title":{"rendered":"12 Online Courses on Data Engineering","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

\"12
\nAccording to Statista, by 2025, the big data market will grow to 175 zettabytes compared to 41 in 2019 (chart<\/a><\/noindex>). To secure a job in this field, one must understand how to work with large amounts of data stored in the cloud. Cloud4Y has prepared a list of 12 paid and free courses on data engineering that will broaden your knowledge in this area and can serve as a great starting point towards cloud certifications.<\/i><\/a><\/noindex><\/p>\n

Preface<\/strong><\/p>\n

What is a Data Engineer? This is a person responsible for creating and maintaining the data architecture in a Data Science project. Their duties may include ensuring a smooth flow of data between the server and the application, integrating new software for data management, improving fundamental data processes, and creating data pipelines.<\/p>\n

There are a vast number of technologies and tools that a data engineer must master to work with cloud computing, data warehouses, ETL (extraction, transformation, loading), etc. Moreover, the number of required skills is continually increasing, so data engineers must regularly update their knowledge. Our list includes courses for both beginners and experienced professionals. Choose what suits you best.<\/p>\n

1. Data Engineering Nanodegree Certification (Udacity<\/a><\/noindex>)<\/p>\n

You will learn to design data models, create data warehouses and data lakes, automate data pipelines, and work with large datasets. At the end of the program, you will validate your new skills by completing a Capstone project.<\/p>\n

Duration<\/strong>: 5 months, 5 hours per week
\nLanguage<\/strong>: English
\nPrice<\/strong>: $1695
\nThe<\/strong>: beginner<\/p>\n

2. Become a Data Engineer Certification (Coursera<\/a><\/noindex>)<\/p>\n

The course starts from the basics. You can gradually develop your skills using lectures and hands-on projects. By the end of your training, you will be ready to work with ML and big data. It is recommended to have at least a basic understanding of Python.<\/p>\n

Duration<\/strong>: 8 months, 10 hours per week
\nLanguage<\/strong>: English
\nPrice<\/strong>\ud83d\ude15
\nThe<\/strong>: beginner<\/p>\n

3. Become a Data Engineer: Mastering the Concepts (LinkedIn Learning<\/a><\/noindex>)<\/p>\n

You will develop data design skills and DevOps skills, learn how to build applications for Big Data, create data pipelines, and process applications in real-time using Hazelcast and Hadoop databases. : depends on you<\/a><\/noindex>.<\/p>\n

Duration<\/strong>: first month \u2014 free
\nLanguage<\/strong>: English
\nPrice<\/strong>4. Data Engineering Courses (
\nThe<\/strong>: beginner<\/p>\n

4. Data Engineering Courses (edX<\/a><\/noindex>)<\/p>\n

This series of programs introduces you to data engineering and teaches you how to develop analytical solutions. The courses are categorized based on difficulty level, allowing you to choose one that matches your experience level. Throughout the training, you will learn to use Spark, Hadoop, Azure, and manage enterprise data.<\/p>\n

Duration<\/strong>: first month \u2014 free
\nLanguage<\/strong>: English
\nPrice<\/strong>: depends on the chosen course
\nThe<\/strong>: beginner, intermediate, advanced<\/p>\n

5. Data Engineer (DataQuest<\/a><\/noindex>)<\/p>\n

This course is ideal if you have experience with Python and want to deepen your knowledge and build a career as a data processing specialist. You will learn to build data pipelines using Python and pandas, loading large datasets into a Postgres database after cleansing, transforming, and validating.<\/p>\n

Duration<\/strong>: first month \u2014 free
\nLanguage<\/strong>: English
\nPrice<\/strong>: depends on the subscription type
\nThe<\/strong>: beginner, intermediate<\/p>\n

6. Data Engineering with Google Cloud (Coursera<\/a><\/noindex>)<\/p>\n

This course will help you acquire the skills necessary to build a career in big data. For example, working with BigQuery and Spark. You will gain knowledge that will be useful for preparing for the industry-recognized Google Cloud Professional Data Engineer certification.<\/p>\n

Duration<\/strong>: 4 months
\nLanguage<\/strong>: English
\nPrice<\/strong>: currently free
\nThe<\/strong>: beginner, intermediate<\/p>\n

7. Data Engineering, Big Data on Google Cloud Platform (Coursera<\/a><\/noindex>)<\/p>\n

An engaging course that provides practical knowledge of data processing systems in GCP. During the classes, you will learn how to design systems before starting the development process. Additionally, you will analyze both structured and unstructured data, apply auto-scaling, and utilize ML techniques to extract insights.<\/p>\n

Duration<\/strong>: 3 months
\nLanguage<\/strong>: English
\nPrice<\/strong>: currently free
\nThe<\/strong>: beginner, intermediate<\/p>\n

8. UC San Diego: Big Data Specialization (Coursera<\/a><\/noindex>)<\/p>\n

The course is based on utilizing Hadoop and Spark infrastructure and applying these big data processing methods during ML. You will get acquainted with the basics of using Hadoop with MapReduce, Spark, Pig, and Hive. You will learn how to build predictive models and use graph analytics for problem modeling. Note that no programming experience is required for this course.<\/p>\n

Duration<\/strong>: 8 months at 10 hours per week
\nLanguage<\/strong>: English
\nPrice<\/strong>: currently free
\nThe<\/strong>: beginner<\/p>\n

9. Taming Big Data With Apache Spark and Python (Udemy<\/a><\/noindex>)<\/p>\n

You will learn how to use streaming structures and data frames in Spark3, gain insight into how to use Amazon's Elastic MapReduce service to work with your Hadoop cluster. You will learn to identify problems when analyzing big data and understand how GraphX libraries work with network analysis and how you can use MLlib.<\/p>\n

Duration<\/strong>: first month \u2014 free
\nLanguage<\/strong>: English
\nPrice<\/strong>: from 800 rubles to $149.99 (depends on luck)
\nThe<\/strong>: beginner, intermediate<\/p>\n

10. PG Program in Big Data Engineering (upGrad<\/a><\/noindex>)<\/p>\n

This course will give you insight into how Aadhaar works, how Facebook personalizes the news feed, and how Data Engineering can be utilized. Key topics will include data processing (including real-time processing), MapReduce, and big data analytics.<\/p>\n

Duration<\/strong>: 11 months
\nLanguage<\/strong>: English
\nPrice<\/strong>: around $3000
\nThe<\/strong>: beginner<\/p>\n

11. The Profession of Data Scientist (Skillbox<\/a><\/noindex>)<\/p>\n

You will learn to program in Python, study frameworks for training neural networks like Tensorflow and Keras. You will master databases such as MongoDB, PostgreSQL, SQLite3, and learn to work with libraries like Pandas, NumPy, and Matplotlib.<\/p>\n

Duration<\/strong>: 300 hours of training
\nLanguage<\/strong>: Russian
\nPrice<\/strong>: the first six months are free, then 3900 rubles per month
\nThe<\/strong>: beginner<\/p>\n

12. Data Engineer 7.0 (New Professions Lab<\/a><\/noindex>)<\/p>\n

You will have a deep dive into Kafka, HDFS, ClickHouse, Spark, Airflow, lambda architecture, and kappa architecture. You will learn to connect tools together, forming pipelines and getting a baseline solution. Minimal knowledge of Python 3 is required for study.<\/p>\n

Duration<\/strong>: 21 classes, 7 weeks
\nLanguage<\/strong>: Russian
\nPrice<\/strong>: from 60,000 to 120,000 rubles
\nThe<\/strong>: beginner<\/p>\n

If you want to add another good course to the list, you can leave a comment or send a direct message. We will update the post. <\/p>\n

What else is useful to read in the blog Cloud4Y<\/a><\/noindex><\/b><\/p>\n

\u2192 What is the geometry of the Universe?<\/a><\/noindex>
\n\u2192 Easter eggs on Swiss topographic maps<\/a><\/noindex>
\n\u2192 A simplified and very brief history of the development of 'clouds'<\/a><\/noindex>
\n\u2192 How the bank 'broke.'<\/a><\/noindex>
\n\u2192 90s computer brands, part 3, final<\/a><\/noindex><\/p>\n

Subscribe to our Telegram<\/a><\/noindex>-channel so you won't miss the next article. We write no more than twice a week and only when necessary. Also, we remind you that on May 21 at 15:00 (Moscow time) we will hold a webinar<\/a><\/noindex> on the topic 'Information Security of Business When Working Remotely'. If you want to understand how to protect sensitive and corporate information when employees work from home \u2014 register!
\n
Source: habr.com<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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