Data Engineering with AWS
- 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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Academic Partners & International Accreditations
Master Data Engineering with specialization in AWS tool and gain real-time experience in designing, developing, and maintaining data pipelines.
With 360DigiTMG's Certified Course on Data Engineering with AWS, you are introduced to fundamentals as well as advanced concepts of Data Engineering with a special focus on AWS. 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 Course Overview
With our Data Engineering Training, you get to explore the various tools used by Data Engineers and understand the difference between a Data Scientist and a Data Engineer. In this training, get introduced to tools like Python, Spark, Kafka, Jupyter. Spyder, TensorFlow, Keras, PyTorch, etc. along with advanced SQL techniques. Learn to extract raw data from various data sources in multiple formats and then transform them into actionable insights, and deploy them into a single, easy-to-query database. Learn how to build pipelines while handling huge data to optimize the process of big data. Get firsthand experience with advanced data engineering projects.
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 AWS modules will lay out the foundation for Data Engineering with in-depth knowledge of AWS. The course involves an understanding of creating a new AWS account, exploring various services offered by AWS, data modeling, and building data engineering pipelines. 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
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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 Science vs Data Engineering
- Data Engineering Infrastructure and Data Pipelines
- Data Architectures
- Lambda
- Kappa
- Streaming Big Data Architectures Monitoring pipelines
- Azure Databases and other File formats (Data Lakes)
- SQL
- NoSQL
- Microsoft Azure SQL Database
- Configuring Azure SQL Database
- Azure Data Lake - Managing Data
- Securing and Monitoring Data
- Introduction to Azure Data Factory (ADF)
- Azure Data Factory and Data Pipelines
- Azure Data Factory Integration Runtime
- Processing Data with Databricks
- Introduction to Azure Synapse Analytics
- Data Transformations with Azure Synapse Dataflows
- Azure Synapse SQL Pool
- Monitoring And Maintaining Azure Data Engineering Pipelines
How we prepare you
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Additional assignments of over 80+ hours
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Live Free Webinars
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Resume and LinkedIn Review Sessions
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Lifetime LMS Access
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24/7 support
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Job placements in Data Engineering fields
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Complimentary Courses
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Unlimited Mock Interview and Quiz Session
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Hands-on experience in a live project
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Offline Hiring Events
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