“Data is the new oil. It’s valuable, but if it’s not refined it can’t really be used,” said Clive Humby, Director, H&D Advisory and Visiting Professor, Data Science, University of Sheffield.

Data scientists analyze data using mathematics, statistics, and machine learning techniques. But a typical data scientist doesn’t have deep knowledge of how to model data for interpretation. This is where data engineers come in. Data engineers design and configure analytical databases and data pipelines to transform data into a format that makes it easy for data scientists to use it.

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, growing at a CAGR of 17.6%. To make the most of this opportunity, leading institutions, universities, and online educational platforms have launched data engineering courses.

Here let us look at some data engineering courses available in India:

Post Graduate Diploma in Data Engineering and Cloud Computing, IIT Jodhpur

This is a 12-month PG degree program that helps master the key technologies involved in generating insights from data to solve today’s complex social and business challenges. The program combines live sessions with on-campus immersion to help learners hone 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 learn from Big Data using supervised and unsupervised learning techniques.

To apply, click here.

Data Engineering Graduate Program, Indian Statistical Institute

The “Data Engineering Graduate Program” is a 4-month online course that students can access through the “Edu plus now” online training platform. The course will equip students with expertise in SQL, MongoDB, Big Data, Hadoop, Cloud, Python, and Spark software tools and frameworks. The program is designed to equip students with knowledge of functional analysis, SQL, statistical analysis, data mining, regression modeling, hypothesis testing, and predictive analytics. Additionally, learners will understand machine learning techniques using R, deep learning, aspects of neural networks, and natural language processing. In the training process, candidates can work with industry-relevant field projects to gain hands-on experience.

To apply, click here.

Microsoft Azure for Data Engineering, Coursera

Microsoft Azure for Data Engineering is a specialized course designed to help students gain expertise in integrating, transforming, and consolidating data for various structured and unstructured data systems suitable for building analytics solutions. Additionally, this intermediate level course will provide candidates with an 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 earns an Azure Data Engineer Associate certification.

To apply, click here.

Cloud Data Engineering, Coursera

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. Additionally, 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.

Data engineering on Google Cloud Platform, Udemy

The course is designed to provide practical solutions to real-world cloud data engineering use cases. The course offers end-to-end batch processing, data orchestration, and real-time stream analysis on GCP. Candidates will learn how to load data into a data warehousing tool on GCP (BigQuery) and manage/write data orchestration and dependencies using Apache Airflow (Google Composer) in Python. Candidates will also gain expertise in batch data ingestion using Sqoop, CloudSql and Apache Airflow, streaming and real-time data analysis using the latest API, Spark Structured Streaming with Python and Micro batching using PySpark streaming & Hive on Dataproc.

To apply, click here.

Data Engineer Nanograde Program, Udacity

This 5-month nanodegree program will enable students to design data models, build data warehouses and lakes, automate data pipelines, and work with large data sets. The curriculum includes courses on Data Modeling, Cloud Data Warehouses, Spark and Data Lakes, Data Pipelines with Airflow, and a Capstone Project.

To apply, click here.

Data Engineering with Cloud Computing (AWS) Program, AptusLearn

This weekend-only, 6-month Professional Certificate course will help students understand the inner workings of data platforms, gain hands-on experience with modern distributed data analytics, and learn how to use the AWS cloud platform architecture framework for creating a database. lake or data warehouse. The program offers in-depth sessions on AWS Cloud Platform, Vertica/RDBMS database platform and DevOps environment and covers benchmarking 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.

PGP in Data Engineering, MITxMicroMasters and Intellipaat

This 7-month online PGP certification in data engineering will provide students with in-depth knowledge of SQL, Python, data pipelines, data transformation, Spark, and cloud services from AWS and Azure. The course will allow students to work on multiple real-world projects to gain knowledge on building production-ready ETL (extract, transform, and load) and extract data from multiple data sources, including streaming services in real time, and upload them to cloud data. warehouses.

To apply, click here.

Big Data Engineer Certification Course, IBM

The master’s program has been designed to impart in-depth knowledge of the flexible and versatile frameworks of the Hadoop ecosystem and big data engineering tools such as building data models, database interfaces, architecture advanced, Spark, Scala, RDD, SparkSQL, Spark Streaming, Spark ML, GraphX, Sqoop, Flume, Pig, Hive, Impala and Kafka Architecture. Candidates taking this course will learn how to model data, perform data ingestion, replicate data, and share data using a NoSQL MongoDB database management system. Additionally, students will gain hands-on experience connecting Kafka to Spark and using Kafka Connect. Additionally, candidates will be able to interact with IBM management through live sessions and work on one capstone project and more than 15 real-life projects.

To apply, click here.

Introduction to Data Engineering, Datacamp

Candidates get an overview of the different tools used by data engineers and how cloud technology plays a role in data engineering. Additionally, students learn about the different types of databases that data engineers use, how parallel computing is the cornerstone of the data engineer’s toolkit, and how to plan data processing tasks at the same time. using planning frameworks. The course also provides an in-depth understanding of ETL (Extract, Transform, and Load) which forms the basis of a data engineer’s workflow.

To apply, click here.