Big Data Engineer Bootcamp

1.650,00 EUR

  • 100 hours
eLearning

This Big Data Engineer Bootcamp, in collaboration with IBM, provides training on the competitive skills required for a rewarding career in data engineering. You’ll learn to master the Hadoop extensive data framework, leverage the functionality of Apache Spark with Python, simplify data lines with Apache Kafka, and use the open-source database management tool MongoDB to store data in big data environments.

Key Features

Course and material in English

Beginner - Advanced level for aspiring professional

62 hours eLearning (self-paced) video content

1 year access with 100 hours study time recommendation

Industry-recognized certificates from IBM (for IBM courses)

Real-life projects providing hands-on industry training

30+ in-demand skills

Certification for each courses and Bootcamp certification upon completion

Learning Outcomes

At the end of this Big Data Engineer Bootcamp, you will be able to:

Hadoop Ecosystem

Gain an in-depth understanding of the flexible and versatile frameworks in the Hadoop ecosystem, such as Pig, Hive, Impala, HBase, Sqoop, Flume, and Yarn

Master tools and skills

such as data model creation, database interfaces, advanced architecture, Spark, Scala, RDD, SparkSQL, Spark Streaming, Spark ML, GraphX, Sqoop, Flume, Pig, Hive, Impala, and Kafka architecture

Understand how to model data

Perform ingestion, replicate data, and shard data using the NoSQL database management system MongoDB

Analytics infrastructure

Gain expertise in creating and maintaining analytics infrastructure and own the development, deployment, maintenance, and monitoring of architecture components

Improve business

Achieve insights on how to improve business productivity by processing big data on platforms that can handle its volume, velocity, variety, and veracity

Learn Kafka

Learn how Kafka is used in the real world, including its architecture and components, get hands-on experience connecting Kafka to Spark, and work with Kafka Connect

Amazon EMR

Understand how to use Amazon EMR for processing data using Hadoop ecosystem tools

Learning Path

  1. Big Data for Data Engineering

    Course 1

  2. Big Data Hadoop and Spark Developer

    Course 2

  3. Pyspark Training

    Course 3

  4. Apache Kafka

    Course 4

  5. MongoDB Developer and Administrator

    Course 5

  6. AWS Technical Essentials

    Course 6

  7. AWS Big Data Certification Training

    Course 7

  8. Big Data Capstone Project

    Course 8

  9. AWS Technical Essentials

    Elective Course

  10. Java Certification Training

    Elective Course

  11. SQL

    Elective Course

big data bootcamp
Big data engineer bootcamp

Who Should Enroll in this Program?

is ideal for individuals who want to build a career in data engineering and work with large-scale data systems. The following groups of people should consider enrolling:

Aspiring Data Engineers

Software Developers & Engineers

Database Administrators (DBAs)

Data Analysts & BI Professionals

Data Science & AI Enthusiasts

Students in UG/ PG programs

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Prerequisites

There is no formal requirement to enroll the program. However it is advisable to have some:

Programming Knowledge:

  • Proficiency in at least one programming language such as Python, Java, Scala, or R is often expected.
  • Familiarity with scripting and automation tools can be a plus.

Basic Database Knowledge:

  • Understanding of SQL, relational databases, and concepts like data modeling and data normalization.

Basic Statistics and Mathematics:

  • Understanding of basic statistics, probability, and linear algebra is essential for data analysis and machine learning.

Statements

Licensing and accreditation

Big Data Engineer Bootcamp is offered by Simplilearn according to Partner Program Agreement and complies with the License Agreement requirements.

Equity Policy

Simplilearn does not provide accommodations due to a disability or medical condition of any students. Candidates are encouraged to reach out to AVC for guidance and support throughout the accommodation process.

Frequently Asked Question

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