Big Data Engineer Master’s Program Certification

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

• 6 months online classroom bootcamp and eLearning (self-paced)
• Industry-recognized certificates from IBM (for IBM courses) and Simplilearn
• Real-life projects providing hands-on industry training
• 30+ in-demand skills
• Lifetime access to self-paced learning and class recordings
• 35 hours of self-paced training
• 132 hours of instructor-led training
• Masterclasses, Exclusive Mentoring Sessions, and Hackathons by IBM

Program Outcomes

At the end of this BIG DATA ENGINEER MASTER’S PROGRAM, you will be able to:

• 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
• Gain expertise in creating and maintaining analytics infrastructure and own the development, deployment, maintenance, and monitoring of architecture components
• Achieve insights on how to improve business productivity by processing big data on platforms that can handle its volume, velocity, variety, and veracity
• 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
• Understand how to use Amazon EMR for processing data using Hadoop ecosystem tools

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
• Banking and finance professionals
• Database administrators
• Beginners in the data engineering domain
• Students in UG/ PG programs

Learning Path - Big Data Engineer

1. Big Data for Data Engineering (1 hours)

This introductory course from IBM will teach you the basic concepts and terminologies of big data and its real-life applications across multiple industries. You will gain insights into improving business productivity by processing large volumes of data and extracting valuable information.

Key Learning Objectives

• Understand what big data is, the sources of big data, and real-life examples
• Learn the critical difference between big data and data science
• Master the usage of big data for operational analysis and better customer service
• Gain knowledge of the ecosystem of big data and the Hadoop framework

Course Curriculum

• Lesson 1 - What is Big Data?
• Lesson 2 - Big Data: Beyond the Hype
• Lesson 3 - Big Data and Data Science
• Lesson 4 - Use Cases
• Lesson 5 - Processing Big Data

2. Big Data Hadoop and Spark Developer

AVC's Big Data Hadoop Training Course helps you master big data and Hadoop ecosystem tools such as HDFS, YARN, MapReduce, Hive, Impala, Pig, HBase, Spark, Flume, Sqoop, and Hadoop Frameworks, including additional concepts of the big data processing life cycle. Throughout this online, instructor-led Hadoop training, you will work on real-time projects in retail, tourism, finance, and other domains. This extensive data course prepares you for Cloudera’s CCA175 Big Data certification.

Key Learning Objectives

• Learn how to navigate the Hadoop Ecosystem and understand how to optimize its use
• Ingest data using Sqoop, Flume, and Kafka
• Implement partitioning, bucketing, and indexing in Hive
• Work with RDD in Apache Spark
• Process real-time streaming data
• Perform DataFrame operations in Spark using SQL queries
• Implement User-Defined Functions (UDF) and User-Defined Attribute Functions (UDAF) in Spark

Course Curriculum

• Lesson 1 - Introduction to Bigdata and Hadoop
• Lesson 2 -Hadoop Architecture Distributed Storage (HDFS) and YARN
• Lesson 3 - Data Ingestion into Big Data Systems and ETL
• Lesson 4 -Distributed Processing MapReduce Framework and Pig
• Lesson 5 -Apache Hive
• Lesson 6 - NoSQL Databases HBase
• Lesson 7 - Basics of Functional Programming and Scala
• Lesson 8 -Apache Spark Next-Generation Big Data Framework
• Lesson 9 -Spark Core Processing RDD
• Lesson 10 -Spark SQL Processing DataFrames
• Lesson 11 -Spark MLLib Modelling BigData with Spark
• Lesson 12 - Stream Processing Frameworks and Spark Streaming
• Lesson 13 -Spark GraphX

3. Pyspark Training

Pyspark Training will provide an in-depth overview of Apache Spark, the open-source query engine for processing large datasets, and how to integrate it with Python using the PySpark interface. This course will show you how to build and implement data-intensive applications as you dive into high-performance machine learning. You’ll learn how to leverage Spark RDD, Spark SQL, Spark MLlib, Spark Streaming, HDFS, Sqoop, Flume, Spark GraphX, and Kafka.

Key Learning Objectives

• Understand how to leverage the functionality of Python as you deploy it in the Spark ecosystem
• Master Apache Spark architecture and how to set up a Python environment for Spark
• Learn about various techniques for collecting data, understand RDDs and how to contrast them with DataFrames, how to read data from files and HDFS, and how to work with schemas
• Obtain a comprehensive knowledge of various tools that fall under the Spark ecosystem, such as Spark SQL, Spark MlLib, Sqoop, Kafka, Flume, and Spark Streaming
• Create and explore various APIs to work with Spark DataFrames and learn how to aggregate, transform, filter, and sort data with DataFrames

Course Curriculum

• Lesson 01 - A Brief Primer on Pyspark
• Lesson 02 - Resilient Distributed Datasets
• Lesson 03 - Resilient Distributed Datasets and Actions
• Lesson 04 - DataFrames and Transformations
• Lesson 05 - Data Processing with Spark DataFrames

4. Apache Kafka

In this Apache Kafka certification course, you will master the architecture, installation, configuration, and interfaces of Kafka open-source messaging. With this Kafka training, you will learn the basics of Apache ZooKeeper as a centralized service and develop the skills to deploy Kafka for real-time messaging. This course is part of the Big Data Hadoop Architect Master’s Program and is recommended for developers and analytics professionals who wish to advance their expertise.

Key Learning Objectives

• Describe the importance of big data
• Describe the fundamental concepts of Kafka
• Describe the architecture of Kafka
• Explain how to install and configure Kafka
• Explain how to use Kafka for real-time messaging

Course Curriculum

• Lesson 1 - Getting Started with Big Data and Apache Kafka
• Lesson 2 - Kafka Producer
• Lesson 3 - Kafka Consumer
• Lesson 4 - Kafka Operations and Performance Tuning
• Lesson 5 - Kafka Cluster Architecture and Administering Kafka
• Lesson 6 - Kafka Monitoring and Schema Registry
• Lesson 7 - Kafka Streams and Kafka Connectors
• Lesson 8 - Integration of Kafka with Storm
• Lesson 9 - Kafka Integration with Spark and Flume
• Lesson 10 - Admin Client and Securing Kafka

5. MongoDB Developer and Administrator

Become an expert MongoDB developer and administrator by gaining an in-depth knowledge of NoSQL and mastering the skills of data modeling, ingestion, query, sharding, and data replication. This course includes industry-based projects in the e-learning and telecom domains. It best suits database administrators, software developers, system administrators, and analytics professionals.

Key Learning Objectives

• Develop expertise in writing Java and NodeJS applications using MongoDB
• Master the skills of replication and sharding of data in MongoDB to optimize read/write performance
• Perform installation, configuration, and maintenance of the MongoDB environment
• Get hands-on experience creating and managing different types of indexes in MongoDB for query execution
• Proficiently store unstructured data in MongoDB
• Develop skill sets for processing vast amounts of data using MongoDB tools
• Gain proficiency in MongoDB configuration, backup methods, and monitoring and operational strategies
• Acquire an in-depth understanding of managing DB Notes, Replica set, and master-slave concepts.

Course Curriculum

• Lesson 1 - Introduction to NoSQL Databases
• Lesson 2 - MongoDB: A Database for the Modern Web
• Lesson 3 - CRUD Operations in MongoDB
• Lesson 4 - Indexing and Aggregation
• Lesson 5 - Replication and Sharding
• Lesson 6 - Developing Java and Node JS Application with MongoDB
• Lesson 7 - Administration of MongoDB Cluster Operations

6. AWS Technical Essentials

This AWS Technical Essentials course teaches you how to navigate the AWS management console; understand AWS security measures, storage, and database options; and gain expertise in web services like RDS and EBS. This course, prepared in line with the latest AWS syllabus, will help you become proficient in identifying and efficiently using AWS services.

Key Learning Objectives

• Understand the fundamental concepts of the AWS platform and cloud computing
• Identify AWS concepts, terminologies, benefits, and deployment options to meet business requirements
• Identify deployment and network options in AWS

Course Curriculum

• Lesson 01 - Introduction to Cloud Computing
• Lesson 02 - Introduction to AWS
• Lesson 03 - Storage and Content Delivery
• Lesson 04 - Compute Services and Networking
• Lesson 05 - AWS Managed Services and Databases
• Lesson 06 - Deployment and Management

7. AWS Big Data Certification Training

In this AWS Big Data certification course, you will become familiar with concepts cloud computing and its deployment models; the Amazon web services cloud platform; Kinesis Analytics; AWS big data storage, processing, analysis, visualization, and security services; EMR; AWS Lambda and Glue; machine learning algorithms; and much more.

Key Learning Objectives

• Understand how to use Amazon EMR for processing the data using Hadoop ecosystem tools
• Understand how to use Amazon Kinesis for big data processing in real-time
• Analyze and transform big data using Kinesis Streams
• Visualize data and perform queries using Amazon QuickSight

Course Curriculum

• Lesson 01 - AWS in Big Data Introduction
• Lesson 02 - Collection
• Lesson 03 -Storage
• Lesson 04 -Processing I
• Lesson 05 - Processing II
• Lesson 06 - Analysis I
• Lesson 7 - Analysis II
• Lesson 8 - Visualisation
• Lesson 9 - Security

Big Data Capstone

This Big Data Capstone project will give you an opportunity to implement the skills you learned throughout this program. You’ll learn how to solve a real-world, industry-aligned big data problem through dedicated mentoring sessions. This project is the final step in the learning path and will enable you to showcase your expertise in big data to future employers.

Elective Course

• AWS Technical Essentials

This AWS Technical Essentials course teaches you how to navigate the AWS management console; understand AWS security measures, storage, and database options; and gain expertise in web services like RDS and EBS. This course, prepared in line with the latest AWS syllabus, will help you become proficient in identifying and efficiently using AWS services.

• Java Certification Training

This advanced Java Certification Training is designed to guide you through the concepts of Java, from introductory techniques to advanced programming skills. This Java course will also teach you Core Java 8, operators, arrays, loops, methods, and constructors while giving you hands-on experience in JDBC and JUnit framework.

• Industry Master Class – Data Engineering

Attend an online interactive Masterclass and get insights into data engineering.

• SQL

This course gives you all the information you need to successfully start working with SQL databases and use the database in your applications. Learn to structure your database correctly, author efficient SQL statements and clauses, and manage your SQL database for scalable growth.

• Industry Master Class – Data Science

Attend this online interactive industry master class to gain insights about Data Science advancements and AI techniques.