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Best Data Engineering Course Training in Chicago

Data Engineering is the new hot job in the market. A tech job report published by a renowned agency notes that Data Engineering is the fastest-growing career option in technology.
  • 40 Hours Classroom & Online Sessions
  • 80 Hours Assignments & Real-Time Projects
  • Complementary Hadoop and Spark
  • Complementary ML on Cloud
  • Complementary Python Programming
Data Engineering certification course reviews - 360digitmg
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Data Engineering certification course reviews - 360digitmg
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Academic Partners & International Accreditations
  • Data Engineering Course with Microsoft
  • Data Engineering certification with nasscomm
  • Data Engineering certification innodatatics
  • Data Engineering certification with SUNY
  • Data Engineering certification with NEF

Data engineering is about generating quality data and making it available for businesses to make data-driven decisions. Requirement for Data Engineering professionals has always outstripped the supply since 2017. Data Engineers enable businesses to engage in insights produced by data science using advanced analytics. This course in Data Engineering will equip you to build big data superhighways by teaching you the skills to unlock the value of data. According to reports, Data Engineer is the fastest-growing job in the space of technology, and with this course in Data Engineering, you will be able to kick start your new career as a Data Engineer today!

Data Engineering

business analytics course duration in Chicago

Total Duration

3 Months

data engineering course

Prerequisites

  • Computer Skills
  • Basic Mathematical Concepts
  • Analytical Mindset

Data Engineering Training Overview in Chicago

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 in Chicago

These modules will lay out the foundation for data science and analytics. The core of Data Engineering involves an understanding of various techniques like data modelling, building data engineering pipelines, and deploying the analytics models. Students will learn how to wrangle data and perform advance analytics to get the most value out of data. As you progress, you'll 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

data engineering course in Chicago

40 hours

Classroom Sessions

data engineering course in Chicago

80 hours

Assignments

Who Should Sign Up?

  • Science, Math and Commerce graduates
  • IT professionals who want to specialise in digital tech
  • Professionals who want to move into Data Analytics
  • Professionals who want to add Data Analytics to current job skills
  • Academicians and researchers working in Data Analytics

Data Engineering Course Modules in Chicago

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.

  • 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 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
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
  • data engineering course with certification in Chicago
    Lifetime LMS Access
  • data engineering course  with USP in Chicago
    24/7 support
  • data engineering certification with USP in Chicago
    Job placements in Data Engineering fields
  • best data engineering course with USP in Chicago
    Complimentary Courses
  • best data engineering course with USP in Chicago
    Unlimited Mock Interview and Quiz Session
  • best data engineering training with placements in Chicago
    Hands-on experience in a live project
  • data engineering course with USP in Chicago
    Offline Hiring Events

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