Big Data Engineer Master’s Program Certification
1.650,00 EUR
- 100 hours
This Big Data Engineer Master’s Program, 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 Master's certification upon completion
Learning Outcomes
At the end of this Big Data Engineer Master´s Program, 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
Big Data for Data Engineering
Course 1
Big Data Hadoop and Spark Developer
Course 2
Pyspark Training
Course 3
Apache Kafka
Course 4
MongoDB Developer and Administrator
Course 5
AWS Technical Essentials
Course 6
AWS Big Data Certification Training
Course 7
Big Data Capstone Project
Course 8
Elective Courses
Elective Course
Who Should Enroll in this Program?
A prominent data engineer builds and maintains data structures and architectures for data ingestion, processing, and deployment for large-scale, data-intensive applications. It’s a promising career for both new and experienced professionals with a passion for data, including:
IT Professionals
Beginners in the Data Engineering Domain
Banking and Finance Professionals
Students in UG/ PG programs
Database Administrators
Statements
Licensing and accreditation
Big Data Engineer Master's Program 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.
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.
Frequently Asked Question
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