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“Data is the new oil. It’s valuable, but if unrefined, it cannot really be used,” said Clive Humby, Principal, H&D Advisory and Visiting Professor, Data Science, University of Sheffield.
Data scientists analyse data with the help of mathematics, statistics and machine learning techniques. But a typical data scientist does not have in-depth knowledge of how to model data for interpretation. Here’s where data engineers come into play. Data engineers design and set up analytics databases and data pipelines to transform data in a format that enables data scientists to use it readily.
The global big-data and data engineering services market is expected to grow from USD 39.50 billion in 2020 to USD 87.37 billion by 2025, at a CAGR of 17.6%.To make the most of this opportunity, premier institutions, universities and online educational platforms have launched data engineering courses.
Here, let’s take a look at a few data engineering courses available in India:
It is a 12-month PG diploma program that helps master the key technologies involved in generating insights from data to solve today’s complex social and business challenges. The curriculum combines live sessions with campus immersion to help learners hone high-in-demand skills such as big data engineering, cloud computing, and machine learning. Students will be able to understand the basics of big data and design and implement appropriate storage and processing techniques for big data, develop and implement cloud deployment strategies for big data applications and derive insights from big data using supervised and unsupervised learning techniques.
To apply, click here.
The ‘Post Graduate Program in Data Engineering’ is a 4-month online course that students can avail through the online education platform ‘Edu plus now’. The course will allow students to gain expertise in SQL, MongoDB, Big data, Hadoop, Cloud, Python, and Spark software tools and frameworks. The program is designed to equip the students with knowledge about functional analysis, SQL, statistical analysis, data mining, regression modelling, hypothesis testing, and predictive analytics. In addition, the learners will understand machine learning techniques using R, deep learning, aspects of neural networks, and natural language processing. In the training process, the candidates can work with projects from industry-relevant domains to get hands-on experience.
To apply, click here.
Microsoft Azure for Data Engineering is a specialised course to help the students gain expertise in integrating, transforming, and consolidating data for various structured and unstructured data systems suitable for building analytics solutions. In addition, this intermediate-level course will enable candidates to gain in-depth knowledge of data processing languages, such as SQL, Python, or Scala, and an understanding of parallel processing and data architecture patterns. Upon completion, the candidate gets an Azure Data Engineer Associate certification.
To apply, click here.
Duke University offers this course on Coursera. This intermediate-level online course will enable candidates to apply cloud computing to data science, machine learning and data engineering. Also, the candidates will learn how to use software development best practices to create data engineering applications. This course includes a project on building a serverless data engineering pipeline in a Cloud platform: Amazon Web Services (AWS), Azure or Google Cloud Platform (GCP).
To apply, click here.
The course is designed to provide practical solutions to real-world use cases regarding data engineering on the Cloud. The course offers end-to-end batch processing, data orchestration and real-time streaming analytics on GCP. The candidates will learn how to load data into a data-warehousing tool on GCP (BigQuery) and how to handle/write data orchestration and dependencies using Apache Airflow(Google Composer) in Python. Candidates will also get expertise in batch data ingestion using Sqoop, CloudSql and Apache Airflow, real-time data streaming and analytics using the latest API, Spark Structured Streaming with Python and Micro batching using PySpark streaming & Hive on Dataproc.
To apply, click here.
This 5-month nanodegree program will enable students to design data models, build data warehouses and lakes, automate data pipelines, and work with massive datasets. The program includes courses on data modelling, cloud data warehouses, spark, and data lakes, data pipelines with Airflow, and a Capstone project.
To apply, click here.
This 6-months weekend-only professional certificate course will help students understand the nuts and bolts of data platforms, obtain hands-on experience with modern distributed data analytics, and learn how to use the architecture framework in the AWS cloud platform to create a data lake or data warehouse. The program offers deep-dive sessions on AWS Cloud Platform, Vertica/RDBMS database platform and DevOps environment and covers comparative analyses of AWS, GCP and Azure platforms. Candidates will also acquire skills in data acquisition, Data Warehouse / Data Lake architecture, data processing and automation using open source tools such as Python, SQL and PySpark.
To apply, click here.
This 7-month online PGP Certification in Data Engineering will provide students with in-depth knowledge in SQL, Python, data pipelines, data transformation, Spark, and cloud services of AWS and Azure. The course will enable students to work on multiple real-world projects to gain knowledge on creating production-ready ETL (extract, transform and load) and pulling data from multiple data sources, including real-time streaming services, and loading them into cloud data warehouses.
To apply, click here.
The Master’s Program has been designed to impart in-depth knowledge of the flexible and versatile frameworks on the Hadoop ecosystem and big data engineering tools like Data Model Creation, Database Interfaces, Advanced Architecture, Spark, Scala, RDD, SparkSQL, Spark Streaming, Spark ML, GraphX, Sqoop, Flume, Pig, Hive, Impala, and Kafka Architecture. Candidates pursuing this course will learn how to model data, perform ingestion, replicate data, and share data using a NoSQL database management system MongoDB. Also, students will get hands-on experience connecting Kafka to Spark and working with Kafka Connect. In addition, candidates will get to interact with IBM leadership through live sessions and work on a Capstone project and 15+ real-life projects.
To apply, click here.
Candidates get an overview of the various tools data engineers use and how cloud technology plays a role in data engineering. In addition, students learn about the different types of databases data engineers use, how parallel computing is a cornerstone of the data engineer’s toolkit, and how to schedule data processing jobs using scheduling frameworks. The course also provides an in-depth understanding of ETL (extract, transform and load) that forms the base of a data engineer’s workflow.
To apply, click here.
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