AWS Data Engineer Course Content

Data engineering is a vast concept and we have handpicked a few of the widely used tools to design this AWS data engineering course. This AWS data engineer online training is fully customizable and covers job-ready skills with projects. Below listed are standard AWS data engineer online Course modules:

Topics:

  • Data Engineering Overview
  • Expectations of Data Engineer
  • Current Data Ecosystem
  • Data Engineer vs. Data Analyst vs. Data Science

Topics:

  • Basic Database concepts
  • Normalization,
  • Keys
  • Constraints
  • Database storage etc

Topics:

  • Tables
  • Views
  • Keys
  • Indexes
  • Joins
  • Filters
  • CTEs
  • Subquery

Topics:

  • Windows function
  • Aggregations
  • Complex SQL writing

Topics:

  • Basic syntaxes
  • Working with files
  • Connecting to databases
  • Building basic APIs
  • Working with structured (database and tables)
  • Working with unstructured(XML, JSON, etc.) data.

Topics:

  • Data Engineering Overview
  • Expectations of Data Engineer
  • Current Data Ecosystem
  • Data Engineer vs. Data Analyst vs. Data Science

Topics:

  • Basic Database concepts
  • Normalization,
  • Keys
  • Constraints
  • Database storage etc

Topics:

  • Tables
  • Views
  • Keys
  • Indexes
  • Joins
  • Filters
  • CTEs
  • Subquery

Topics:

  • Windows function
  • Aggregations
  • Complex SQL writing

Topics:

  • Basic syntaxes
  • Working with files
  • Connecting to databases
  • Building basic APIs
  • Working with structured (database and tables)
  • Working with unstructured(XML, JSON, etc.) data.

Topics:

  • Learn about the basics of Cloud computing
  • SAAS, PAAS, IAAS offerings
  • distributed computing
  • Capex vs Op-ex
  • Elastic scalability
  • Storage and Compute in the cloud
  • Data Stacks in the Cloud
  • AWS, Azure, GCP clouds 

Topics:

  • History of Hadoop
  • Hadoop 1,2,3
  • HDFS
  • MapReduce
  • YARN
  • Sqoop
  • Hive
  • PIG
  • HBase
  • Oozie
  • Zookeeper
  • SPARK basics

Topics:

  • AWS Simple Storage Service
  • Uploading files into S3
  • Adding AWS S3 Buckets
  • Version Control
  • S3 Storage Classes
  • AWS CLI

Topics:

  • AWS Elastic Cloud Compute
  • SSH Access
  • Launching EC2 Instance Virtual Machine
  • Security Groups Basics
  • IP Address Basics

Topics:

  • AWS Lambda Overview
  • AWS Lambda console
  • Project Deployment to AWS Lambda
  • Libraries in AWS Lambda
  • Validating Connections & Files
  • AWS Event Bridge

Topics:

  • Glue Basics
  • Glue Components
  • Data Catalog
  • Working of Glue Jobs
  • Scheduling Jobs & Crawlers
  • Troubleshooting on Glue

Topics:

  • EMR Cluster
  • EMR Cluster with Spark
  • EMR Cluster Scaling Policy
  • EMR Cluster Configurations
  • Deploying Applications to EMR
  • EMR Cluster Management
  • Troubleshooting

Topics:

  • DynamoDB Basics
  • Overview of GitHub APIs
  • Repository Creation
  • DynamoDB Tables
  • CRUD Operations
  • Batch Operations

Topics:

  • Amazon Athena
  • Amazon Athena Architecture
  • Athena Query Editor
  • Creating Database & Tables using Athena
  • Athena - Partitioned Table

Topics:

  • Dimensions and Types
  • Facts and Types
  • SCD1, SCD2, SCD3
  • Data Life Cycle
  • ETL Vs ELT
  • Surrogate Keys and other constraints
  • Functional Views

Topics:

  • Amazon Redshift - Introduction
  • Redshift Cluster Creation
  • Redshift Query Editor
  • Querying information schema
  • Insert Data into Redshift Tables
  • Update Data in Redshift Tables
  • Delete data from Redshift tables
  • Redshift Saved Queries using Query Editor
  • Deleting Redshift Cluster

Looking for a detailed curriculum? Enquire now!

Get the full course details to your inbox!

LIVE SESSIONS


  • Real-time Trainers
  • Live interactive Sessions
  • Cloud Labs

CORPORATE TRAINING


  • Customized Training Solutions
  • Blended Delivery Model
  • Project Implementation Support

SELF-PACED LEARNING


  • High-Quality Videos
  • Access to Materials
  • Permanent Access

AWS Data Engineer Training Objectives

Through this AWS Data Engineer Course, you will gain practical exposure in the areas:

  • Understand Data engineering lifecycle
  • Explore database concepts
  • Gain vital knowledge of Structured Query Language
  • Learn to write programs in Python for data-related queries
  • Detailed overview of Amazon Web Services
  • Skill to work with AWS S3 storage
  • Hands-on knowledge in the creation of EC2 instance
  • Use Glue Catalog to manage tables
  • Execute Batch Data Pipelines using Glue
  • Run Queries using Athena
  • Learn to build  Data Pipelines using Elastic Map Reduce (EMR)
  • Create reports and dashboards using EMR
  • Master skills to ingest data using AWS Lambda Functions
  • Insights into AWS Kinesis
  • Learn to process data using  AWS Athena
  • Perform data copy tasks from S3 to a data warehouse
  • Creating schemas, clusters, tables, etc.

The participants should have basic knowledge of the following areas to enroll in this Data Engineering training program:

  • SQL Experience
  • Python knowledge
  • Data Engineers who wish to learn data engineering with AWS
  • Analytics Engineers
  • Test Data Engineer
  • Freshers planning to build careers in the data engineering space.

Data engineering is a broad concept that uses various tools & frameworks to achieve desired results. It is a methodology to collect, store, and transform business data. Data engineers are the professionals who design & build databases and models to collect, store, transform & use business data.

Data Engineering with AWS is similar to everyday data engineering operations, but in this case, we use different Amazon cloud services to perform data engineering operations & to maintain infrastructure.

Whether you are a freshman or have experience in data handling technologies, this AWS Data engineering training course is for you. We have built this course from the ground to cover advanced data engineering concepts. Our AWS data engineering course Online offers end-to-end practical data engineering skills that today's employers are looking for.

This AWS Data Engineer Certification offers deep insights & practical skills into building blocks of data engineering, basic to advanced SQL concepts, Python, AWS essentials services, AWS Athena, Glue, EMR, Kinesis, DynamoDB, EC2, Data Warehousing, and more. Practical labs, assignments, projects, and interview-specific training would simplify your path for your data engineering job.

This AWS data engineer certification course starts with an overview of data engineering and takes you through the following tools and technologies 

  • SQL Foundation (MySQL)
  • Python Programming concepts related to data engineering
  • ETL (Extract, Transform & Load)
  • Amazon Web Service Fundamentals
  • AWS Simple Storage Service (S3)
  • AWS IAM & EC2
  • Lambda functions for data Ingestion
  • Pyspark Concepts from basic to advanced
  • Glue Components
  • AWS EMR clusters
  • Kinesis for building pipelines
  • DynamoDB
  • Amazon Athena & Redshift

SQL (structured Query Language) is a mandatory skill for data engineers! Apart from SQL, Python programming skills have become a must-have for data engineers. These days, Python is used in a wide range of data engineering operations, and popular ones are for ETL jobs, data integration, writing data pipelines, etc. Some data engineering projects may require professionals to have Java & Scala skills.

A Data engineer professional is a highly technical and demanding position in any organization. Being a  data engineer, he or she has to possess diversified skills to handle data engineering projects; the following are some of the everyday tasks carried out by a data engineer:

  • Raw data analysis
  • Build Data warehouse/ databases
  • Build Pipelines
  • Gather business requirements & work on it
  • Work on complex data analysis
  • Data trends interpretation
  • Data preparation for predictive modeling
  • Building algorithms
  • Combining raw data coming from different sources
  • Enhancing data quality & exploring ways to do it
  • Work with analytical tools
  • Collaborate with Data Scientists for project operations

AWS Data Engineer Certification

Yes, once you finish your AWS Data Engineer Certification course you will receive an electronic course completion certificate from Techsolidiy. You can share this certificate on social media platforms to share your skills with employers.

techsolidity-certification

AWS Data Engineer Course Projects

AWS data engineering is a broad area, and understanding theory alone will not help job seekers. This course is associated with two live capstone projects to address this issue. Working on these projects would help you put your learning into implementation & build databases, models, and workflows using AWS services. AWS Data Engineering Project 1 - Build an Analytical Platform for eCommerce using AWS Services AWS Data Engineering Project 2 - Build an ETL Data Pipeline on AWS EMR Cluster

AWS Data Engineer Course Reviews

AWS Data Engineer Course FAQ's

Yes, Techsolidty offers you two types of Discounts: one is group discount and the other is referral discount.
Yes, In order to provide you the financial flexibility, we provide you the chance to pay the course fee in two installments.
Due to any reasons, you would like to cancel your registration after paying the fee, you should intimate the same to us within the first two classes. The refund amount will be processed within 30 days from the requested date.
To meet the customer expectations we provide multiple types of training which include, Live instructor-led training, Self-paced training, blended training, classroom training, corporate training, etc.
Yes, at Techsolidity all the training courses consist of a minimum of two projects to offer the candidates real-time work understanding!