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Best Data Engineering Course Training in Surat

Master the fundamentals of Data Engineering and get real-time experience working with multiple Databases, Python, and SQL.
  • 60 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

Program Cost

INR 85,000 55,000+Tax

Data Engineering Training Overview

Certified Course on Data Engineering explores the various tools Data Engineers use and find out the difference in the job responsibilities of a Data Scientist and a Data Engineer. It expands learners' understanding of the various skills involved in knowing tools like Python, Spark, Kafka, and Jupyter. Spyder, TensorFlow, Keras, PyTorch, etc., with advanced SQL techniques. 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.

What is Data Engineering?

A Data Engineer collects and transforms data to empower businesses to make data-driven decisions. He/She 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 Surat

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

60 hours

Classroom Sessions

data engineering course

80 hours

Assignments

Who Should Sign Up?

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

Data Engineering Course Modules in Surat

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 Pipeline
  • Data Architecture
  • Lambda
  • Kappa
  • Streaming Big Data Architectures Monitoring pipelines
  • With Databases and various File formats (Data Lakes)
  • SQL
    • MySQL
    • PostgreSQL
  • NoSQL
    • MongoDB
    • HBase
  • Amazon Relational Database Service
  • Microsoft Azure SQL Database
  • Google Cloud SQL
  • Concepts of Extra-Load, Extract-Load-Transform, or Extract-Transform-Load paradigms
  • 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
  • Linux OS
  • Apache Hadoop
  • HDFS
  • Hadoop Cluster on GCP - Dataproc
  • Spark Components
  • Spark Executions – Spark Session
  • RDD
  • Spark DataFrames
  • Spark Core
  • Spark SQL
  • Spark MLlibs
  • Spark Streaming
  • Big Data and Apache Kafka
  • Producers and Consumers
  • Clusters Architectures
  • Kafka Streams
  • Kafka pipeline transformations
  • Building pipelines in Apache Airflow
  • Deploy and Monitor Data Pipelines
  • Production Data Pipeline
  • Data Lake Cloud offerings
  • Cloud Data Warehouse Services
  • Introduction to AWS platform, Creation of free account
  • Walk through the platform and services offered by AWS
  • IAM - Identity and Access Management
  • Intro to AWS Data Warehouses, Data Marts, Data Lakes, and ETL/ELT pipelines
  • Configuring the AWS Command Line Interface tool
  • Creating an S3 bucket
  • Working with Databases and various File formats (Data Lakes)
  • Amazon Database Migration Service (DMS) for ingesting data
  • Amazon Kinesis and Amazon MSK for streaming data
  • AWS Lambda for transforming data
  • AWS Glue for orchestrating big data pipelines
  • Consuming data - Amazon Redshift & Amazon Athena for SQL queries
  • Introduction to Microsoft Azure platform, Creation of free account
  • Walk through the platform and services offered by Azure
  • IAM - Identity and Access Management
  • Azure Data Lake - Managing Data
  • Securing and Monitoring Data
  • Introduction to Azure Data Factory (ADF)
  • Building Data Ingestion Pipelines Using Azure Data Factory
  • Azure Data Factory Integration Runtime
  • Configuring Azure SQL Database
  • Processing Data with Azure Databricks
  • Introduction to Azure Synapse Analytics
  • Data Transformations with Azure Synapse Dataflows
  • Monitoring And Maintaining Azure Data Engineering Pipelines
  • Introduction to GCP platform, Creation of free account
  • Walk through the platform and services offered by GCP
  • IAM - Identity and Access Management
  • Bigdata Solutions with GCP Components
  • Data Warehouse - BigQuery
  • Processing ETL/ELT pipelines with Data Fusion
  • Connecting BI tool for visualizing Data with Looker Studio
  • Architecting Data Pipelines
  • CI/CD On Google Cloud Platform for Data Engineers
SUNY University Syllabus
  • Storage Accounts
  • Designing Data Storage Structures
  • Data Partitioning
  • Designing the Serving Layer
  • Physical Data Storage Structures
  • Logical Data Structures
  • The Serving Layer
  • Data Policies & Standards
  • Securing Data Access
  • Securing Data
  • Data Lake Storage
  • Data Flow Transformations
  • Databricks
  • Databrick Processing
  • Stream Analytics
  • Synapse Analytics
  • Data Storage Monitoring
  • Data Process Monitoring
  • Data Solution Optimization
  • Google Cloud Platform Fundamentals
  • Google Cloud Platform Storage and Analytics
  • Deeper through GCP Analytics and Scaling
  • GCP Network Data Processing Models
  • Google Cloud Dataproc
  • Dataproc Architecture
  • Continued Dataproc Operations
  • Implementations with BigQuery for Big Data
  • Fundamentals of Big Query
  • APIs and Machine Learning
  • Dataflow Autoscaling Pipelines
  • Machine Learning with TensorFlow and Cloud ML
  • GCP Engineering and Streaming Architecture
  • Streaming Pipelines and Analytics
  • GCP Big Data and Security
  • Certificate Course in Data Engineering by SUNY
How we prepare you
  • data engineering course with placements
    Additional assignments of over 80+ hours
  • data engineering course with placements training
    Live Free Webinars
  • data engineering training institute with placements
    Resume and LinkedIn Review Sessions
  • data engineering course with certification
    Lifetime LMS Access
  • data engineering course  with USP
    24/7 support
  • data engineering certification with USP
    Job placements in Data Engineering fields
  • best data engineering course with USP
    Complimentary Courses
  • best data engineering course with USP
    Unlimited Mock Interview and Quiz Session
  • best data engineering training with placements
    Hands-on experience in a live project
  • data engineering course with USP
    Offline Hiring Events

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