What will be the focus of this course?

The Data Engineering course aims to provide aspirants with an in-depth understanding of all the essential tools and skills used by Data Engineers. The course provides hands-on learning of leading as Python, SQL, Spark, Kafka, and many more.

What will be the mode of training?

The training will be conducted in hybrid mode i.e., through the classroom as well as live instructor-led virtual sessions. The timings for both the sessions will be the same.

When do I get to work on live projects?

After the successful completion of 80% of your assignments, you are assigned to a live project where you will work with a group of students to bring the project to closure. After that, you will make a project presentation.

When do I get my certificate?

After the successful completion of the program, you will be awarded the Data Engineering certificate, powered by IBM.

Who all can pursue a Data Engineering course?

This course is designed for students as well as working professionals. The basic requirement to undertake this course includes a degree in engineering, computer applications, or mathematics.

Do I need to pay extra to receive a certificate?

No, there are no extra charges for the certification. The cost is included in the package.

What if I miss out on a session?

Not to worry, if you miss out on a session you can access the recorded session from the online Learning Management System (LMS).

Do I get a job guarantee?

We do not guarantee placements nevertheless, our placement cell supports you with resume building sessions, mock interviews, mentorship, and interview preparation. Our team also helps you launch your career by providing interview opportunities.

Data Engineering with Azure

Name: Best Data Engineering Certification Course Online | 360DigiTMG
Brand: 360DigiTMG
Rating: 5 (3117 reviews)

Master the fundamentals of Data Engineering and get real-time experience working with multiple Databases, Python, and SQL.

Accredited by NASSCOM, Approved by Government of India
80 Hours Assignments & Real-Time Projects
Complementary Hadoop and Spark
Complementary ML on Cloud
Complementary Python Programming
Enroll and avail Government of India (GOI) Incentives after successfully clearing the mandatory Future Skills Prime Assessment

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3117 Learners

data engineering certification course training

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Academic Partners & International Accreditations

With 360DigiTMG's Certified Course on Data Engineering with Azure, you are introduced to fundamentals as well as advanced concepts of Data Engineering with a special focus on Azure. Students get a chance to extract raw data from various data sources in multiple formats and transform them into actionable insights, and deploy them into a single, easy-to-query database. They learn to handle huge data sets and build data pipelines to optimize processes for big data. Students get a chance to dive deeper into advanced data engineering projects that will help in gaining practical experience. This course is at par with Future Skills Prime, accredited by NASSCOM, and approved by the Government of India.

Data Engineering

Program Cost

INR 42,140 25,000/-

(Excluding Taxes)

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Data Engineering Course Overview

The certification course in Data Engineering with Azure lets you explore Azure in depth, where you can learn how to create a new Azure account, and various sources offered by it. Master in creating containers and uploading files to Azure Blob Storage. The course will introduce you to Azure Data Factory, How to build Data Ingestion Pipelines Using Azure Data Factory, and Azure Data Factory Integration Runtime. Azure Synapse Analytics is given special focus in this course. Learn to handle huge data sets and build data pipelines to optimize processes for Big Data. Dive deeper into advanced data engineering projects which will help you gain practical experience and skills.

What is Data Engineering?

A Data Engineer collects and transforms data to empower businesses to make data-driven decisions. He has to pay attention to security and compliance; reliability and fidelity; scalability and efficiency; and flexibility and portability while designing, operationalizing, and monitoring data processing systems.

Data Engineering Training Learning Outcomes

Data Engineering with Azure modules will lay out the foundation for Data Engineering with in-depth knowledge of Azure. The course involves an understanding of creating a new Azure account and exploring various services offered by Azure with a special module dedicated to Azure Synapse Analytics. Students will get a keen understanding of how to handle data, as the course progress, they get to learn how to design as well as build data pipelines and work with big data of diverse complexity and production databases. You will also learn to extract and gather data from multiple sources, build data processing systems, optimize processes for big data, build data pipelines, and much more. With this course develop skills to use multiple data sources in a scalable way and also master the skills involved in descriptive and inferential statistics, interactive data analysis, regression analysis, forecasting, and hypothesis testing. Also, learn to

Comprehend the meaning of Data Engineering

Understand the Data Engineering Ecosystem and Lifecycle

Learn to draw data from various files and databases

Acquire skills and techniques to clean, transform, and enrich your data

Learn to handle different file formats in both NoSQL and Relational databases

Learn to deploy a data pipeline and prepare dashboards to view results

Learn to scale data pipelines in the production environment

Block Your Time

40 hours

Classroom Sessions

80 hours

Assignments

Enroll Now

Who Should Sign Up?

Science, Maths, and Computer Graduates
IT professionals who want to Specialize in Digital Tech
SQL and related developers or software developers
Students/IT professionals have an interest in Data and Databases
Professionals working in the space of Data Analytics
Academicians and Researchers working with data
Cloud and BigData enthusiasts

Data Engineering Course Modules

These modules on Data Engineering are designed to ensure that they are at par with the current industry requirements for Data Engineers. All the modules will wrap up with hands-on practice using real tools and real-time multiple databases. With these modules you will learn to manage, load, extract, and transform data to facilitate delivering of results that your organization can leverage. You will also learn to master the core skills of cleansing, and migrating data.

Data Engineering

Intro to Data Engineering
Data Science vs Data Engineering
Building Data Engineering Infrastructure
Working with Databases and various File formats (Data Lakes)
- SQL
  - MySQL
  - PostgreSQL
- NoSQL
  - MongoDB
  - HBase
  - Apache Cassandra
- Cloud Sources
  - Microsoft Azure SQL Database
  - Amazon Relational Database Service
  - Google Cloud SQL
  - IBM Db2 on Cloud
Extra-Load, Extract-Load-Transform, or Extract-Transform-Load paradigms
Preprocessing, Cleaning, and Transforming Data
Cloud Data Warehouse Service
- AWS: Amazon Redshift
- GCP: Google Big Query
- IBM: Db2 Warehouse
- Microsoft: Azure SQL Data Warehouse
Distributed vs. Single Machine Environments
Distributed Framework - Hadoop
- Various Tools in Distributed Framework to handle BigData
  - HBase
  - Kafka
  - Spark
  - Apache NiFi
- Distributed Computing on Cloud
  - ML and AI platforms on Cloud
Databases and Pipelines
- Data Pipeline
  - Features of Pipelines
  - Building a pipeline using NiFi
Installing and Configuring the NiFi Registry
- Using the Registry in NiFi
- Versioning pipelines
- Monitoring pipelines
- Monitoring NiFi using GUI
- Using Pything with the NiFi REST API
Building pipelines in Apache Airflow
- Airflow boilerplate
- Run the DAG
- Run the data pipelines
Deploy and Monitor Data Pipelines
- Production Data Pipeline
- Creating Databases
Data Lakes
- Populating a data lake
- Reading and Scanning the data lake
- Insert and Query a staging database

Building a Real-Time Data Pipeline

Building a Kafka Cluster
Setup Zookeeper and Kafka Cluster
Configuring and Testing Kafka Cluster
Streaming Data with Apache Kafka
Data Processing with Apache Spark
Real-Time Edge Data with MiNiFi, Kafka, and Spark

Intro to Data Engineering

Data Science vs Data Engineering
Data Engineering Infrastructure and Data Pipelines

Data Sources

Working with Databases and various File formats (Data Lakes)
- SQL
  - MySQL
  - PostgreSQL
- NoSQL
  - MongoDB
  - HBase
- Cloud Sources
  - Microsoft Azure SQL Database
  - Amazon Relational Database Service
  - Google Cloud SQL

Concepts of Extra-Load, Extract-Load-Transform, or Extract-Transform-Load paradigms

Python Programming
- Getting started with Python programming for Data Processing
- Data Types
- Python Packages
- Loops and Conditional Statements
- Functions
- Collections
- String Handling
- File handling
- Exceptional Handling
- MySQL Integration
- INSERT, READ, DELETE, UPDATE, COMMIT, ROLLBACK operations
- MongoDB Integration
Pre-processing, Cleaning, and Transforming Data