Big Data Engineer Masters Option 1
Enhance Your Proficiency in Data Abilities through a Big Data Engineer Program
This comprehensive course for Big Data Engineers includes in-depth workshops and interactive Q&A sessions led by IBM professionals. Acquire essential job-related competencies with our specialized curriculum, covering topics such as Big Data, Hadoop frameworks, and harnessing the capabilities of AWS offerings. Throughout the course, you will gain proficiency in employing database management tools and MongoDB through hands-on sessions and real-world projects.
Interacting with IBM leaders in real time. Live Masterclasses and Ask me Anything sessions.
Immersive Learning Experience
8X Higher Live Interaction in Live Data Science Online Classes by Industry Experts
Capstone and 15+ real life projectsCapstone and over 15 real life projects based on YouTube, Glassdoor and Facebook datasets.
Annual Average US salary $72K to $158K
About Big Data Engineer Course
The tuition cost for enrolling in the Big Data Engineer program is $899
In 2021, IBM has been named a Leader in Data Science and AI Magic Quadrant. Students are trained in an integrated, blended learning approach that prepares them to become expert Big Data Engineers
IBM, headquartered in Armonk, New York, is a prominent cognitive solutions and cloud platform company that offers a wide array of technology and consulting services. With an annual investment of $6 billion in research and development.
What to Anticipate from Collaborative Big Data Engineer Course with IBM Upon the successful completion of the Big Data Engineer course, you will be awarded certificates from IBM (for IBM-specific courses) and showcasing your proficiency as a Big Data Engineer post-training. Additionally, you can expect the following:
Masterclasses led by IBM experts
Interactive “Ask Me Anything” sessions with IBM leadership
Engaging Hackathons organized by IBM
Industry-recognized Master’s Certificate for Big Data Engineering
Big Data has emerged as a transformative force across global businesses, making a significant impact on various industries such as healthcare, insurance, transportation, logistics, and customer service. Embarking on a career as a Big Data Engineer sets you on a dynamic path, offering an exciting journey in a field that is projected to experience substantial growth well into 2025 and beyond.
This jointly developed Big Data Engineer course by Simplilearn and IBM is meticulously crafted to equip you with comprehensive knowledge of the versatile frameworks within the Hadoop ecosystem and essential big data tools. Beyond these, the course will also guide you in data modeling, ingestion, replication, and data sharing using the MongoDB NoSQL database management system.
Throughout the Big Data Engineer course, you will gain practical, hands-on experience in connecting Kafka with Spark and effectively utilizing Kafka Connect. This immersive curriculum aims to prepare you for a successful journey in the realm of Big Data Engineering.
Big Data Engineers are vital in establishing and managing analytics infrastructure, taking charge of tasks ranging from the creation and maintenance of architecture components like databases and large-scale processing systems to their development, deployment, and continuous monitoring.
The skills you will gain through the Big Data Engineer course are immensely valuable and position you for employment opportunities with a diverse array of companies, including prominent names such as IBM, Coca-Cola, Ford Motors, Amazon, HCL, and Uber. The versatility of Big Data Engineers extends across multiple industries such as transportation, healthcare, telecommunications, finance, manufacturing, and many more. According to data from Glassdoor, the average annual salary for a Big Data Engineer stands at $137,776, and the global job market hosts over 130,000 positions in this domain, underlining the substantial demand for skilled professionals in this area.are n
The curriculum of the Big Data Engineer course ensures a comprehensive mastery of various components within the Hadoop ecosystem. It covers essential aspects like MapReduce, Pig, Hive, Impala, HBase, and Sqoop, while also delving into real-time processing with Spark and Spark SQL. By the conclusion of this Big Data Engineer certification course, you will have achieved the following:
Acquire insights into enhancing business productivity through processing Big Data on platforms capable of managing its volume, velocity, variety, and veracity.
Attain expertise in the diverse elements of the Hadoop ecosystem, including Hadoop, Yarn, MapReduce, Pig, Hive, Impala, HBase, ZooKeeper, Oozie, Sqoop, and Flume.
Develop proficiency in MongoDB by obtaining an in-depth comprehension of NoSQL and honing skills in data modeling, ingestion, querying, sharding, and data replication.
Gain practical knowledge of Kafka’s real-world applications, encompassing its architecture and components. Engage in hands-on experiences connecting Kafka with Spark and working with Kafka Connect.
Establish a strong foundation in the fundamentals of the Scala programming language, its tooling, and the development process.
Recognize key AWS concepts, terminologies, benefits, and deployment options essential for meeting business requirements.
Gain the ability to utilize Amazon EMR for data processing through the Hadoop ecosystem tools.
Learn to leverage Amazon Kinesis for real-time big data processing and understand how to analyze and transform big data using Kinesis Streams.
Develop skills to visualize data and perform queries using Amazon QuickSight, contributing to effective data analysis and interpretation.
In essence, this curriculum is designed to equip you with the knowledge and expertise needed to excel in the field of Big Data Engineering and to harness the potential of various tools and technologies within the domain.
To enroll in this course, learners are required to possess either an undergraduate degree or a high school diploma. Additionally, having prior knowledge in the following areas will be beneficial for successfully completing the Big Data Engineer course:
SQL: Familiarity with SQL, which is a standard language for managing and manipulating relational databases, will provide a strong foundation for working with data.
Programming Basics: A grasp of programming fundamentals will aid in understanding and applying the concepts and techniques covered in the course.
Data Pipelines: Prior knowledge of data pipelines, which involve the flow and transformation of data from various sources to destinations, will be advantageous.
Algorithms: Understanding algorithms, which are step-by-step procedures for solving problems, will be helpful in dealing with data processing tasks.
Data Structures: Knowledge of data structures, such as arrays, lists, trees, and graphs, will provide insights into organizing and managing data effectively.
Having these prerequisites in place will enable learners to engage with the course material more effectively and make the most out of the Big Data Engineer program.
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Big Data Engineer
Tools Covered
Big Data Engineer Course Learning Path
Course 1
Big Data for Data Engineering
This IBM course aims to educate you about the fundamental concepts and terminology of Big Data, along with its practical applications in real-world industries. Through this course, you will gain an understanding of how to enhance business productivity by effectively processing substantial data volumes and extracting valuable insights from them.
A. Big Data for Data Engineering
a. Introduction
B. Free Course
C. Data Engineering with Hadoop
a. Lesson 1 Learning Objectives
b. Lesson 2 Introduction to Hadoop
c. Lesson 3 Hadoop Architecture and HDFS
d. Lesson 4 Hadoop administration
e. Lesson 5 Hadoop Components
D. Free Course
E. Data Engineering with Scala
a. Lesson 1 Learning Objectives
b. Lesson 2 Introduction
c. Lesson 3 Basic Object Oriented Programming
d. Lesson 4 Case Objects and Classes
e. Lesson 5 Collections
f. Lesson 6 Idiomatic Scala
Course 2
Big Data Hadoop and Spark Developer
The Big Data Hadoop course empowers you to become proficient in the Hadoop framework, comprehensive big data tools, and relevant methodologies. Earning a certification in Big Data Hadoop readies you for a rewarding career as a Big Data Developer. Through this training, you will comprehend the integration of different elements within the Hadoop ecosystem into the life cycle of Big Data processing. Enroll in this online Big Data and Hadoop training to delve into topics such as Spark applications, parallel processing, and functional programming.
A. Big Data Hadoop and Spark Developer Training
a. Course Introduction
b. Introduction to Big Data and Hadoop
c. HDFS: The Storage Layer
d. Distributed Processing MapReduce Framework
e. MapReduce Advanced Concepts
f. Apache Hive
g. Apache Pig
h. NoSQL Databases – HBase
i. Data Ingestion into Big Data Systems and ETL
j. YARN Introduction
k. Introduction to Python for Apache Spark
l. Functions
m. Big Data and the Need for Spark
n. Deep Dive into Apache Spark Framework
o. Working with Spark RDD’s
p. Spark SQL and Data Frames
B. Machine Learning using Spark ML
a. Stream Processing Frameworks and Spark Streaming
b. Spark Structured Streaming
c. Spark GraphX
C. Free Course
D. Core Java
a. Introduction to Java 11 and OOPs Concepts
b. Utility Packages and Inheritance
c. Multithreading Concepts
d. Debugging Concepts
e. JUnit
f. Java Cryptographic Extensions
g. Design Pattern
E. Free Course
F. Linux Training
a. Lesson 01 – Course Introduction
b. Lesson 02 – Introduction to Linux
c. Lesson 03 – Ubuntu
d. Lesson 04 – Ubuntu Dashboard
e. Lesson 05 – File System Organization
f. Lesson 06 – Introduction to CLI
g. Lesson 07 – Editing Text Files and Search Patterns
h. Lesson 08 – Package Management
i. Practice Project
i. Ubuntu Installation
Course 3
PySpark Training Course
Prepare to infuse Spark into your Python code through this PySpark certification training. This course offers insights into the Spark stack and guides you in harnessing the capabilities of Python within the Spark ecosystem. It equips you with the essential skills needed to excel as a PySpark developer.
A. Brief Primer on PySpark
B. Resilient Distributed Datasets
C. Resilient Distributed Datasets and Actions
D. DataFrames and Transformations
E. Data Processing with Spark DataFrames
Course 4
Apache Kafka
Embark on a Kafka certification journey that delves into processing vast volumes of data through diverse tools. This training enables you to grasp the potential of Big Data analytics with Kafka, leveraging our comprehensive blended learning approach. Immerse yourself in this Kafka course to grasp the fundamental principles of Apache Kafka. Brace yourself for an innovative curriculum meticulously crafted by industry professionals as you pursue this Apache Kafka certification, aimed at honing the practical skills required of a Kafka developer.
A. Introduction to Apache Kafka
B. Kafka Producer
C. Kafka Consumer
D. Kafka Operations and Performance Tuning
E. Kafka Cluster Architecture and Administering Kafka
F. Kafka Monitoring and Schema Registry
G. Kafka Streams and Kafka Connectors
H. Integration of Kafka with Storm
I. Kafka Integration with Spark and Flume
J. Admin Client and Securing Kafka
Course 5
MongoDB Developer and Administrator
Enroll in the MongoDB certification program to acquire the essential skills needed for a successful career as a MongoDB Developer. Our experienced instructors guide you through the ins and outs of MongoDB, enlightening you about the growing trend of businesses adopting MongoDB development services to manage their escalating data storage and processing needs. Through our MongoDB training, you will engage in hands-on industry projects, practical lab exercises, and informative demos that elucidate crucial concepts. Join our MongoDB online course to master this widely used NoSQL database technology.
MongoDB Developer and Administrator
A. Course Introduction
B. Introduction to NoSQL databases
C. MongoDB A Database for the Modern Web
D. CRUD Operations in MongoDB
E. Indexing and Aggregation
F. Replication and Sharding
G. Developing Java and Node JS Application with MongoDB
H. Administration of MongoDB Cluster Operations
Course 6
AWS Data Analytics Certification Training
Engage in the AWS Data Analytics certification training, a comprehensive program designed to equip you with the skills necessary for hosting and processing large-scale data on the AWS platform. This training encompasses all facets of distributed data processing. Aligned with the AWS Certified Data Analytics Specialty exam, our AWS data analytics course is strategically crafted to help you succeed in passing the exam on your first attempt. Developed by industry experts, this AWS certified data analytics training delves into intriguing subjects such as AWS QuickSight, AWS Lambda and Glue, S3 and DynamoDB, Redshift, Hive on EMR, and more.
A. Section 1 – Self-paced Curriculum
B. Introduction
C. Domain 01 – Collection
D. Domain 02 – Storage
E. Domain 03 – Processing
F. Domain 04 – Analysis
G. Domain 05 – Visualization
H. Domain 06 – Security
I. Everything Else
J. Preparing for the Exam
K. Appendix – Machine Learning Topics for the Amazon Web Services AWS Certified Big Data Exam
L. Wrapping Up
Course 7
Big Data Capstone
The Big Data Capstone project presents a valuable opportunity to apply the skills acquired during your Big Data Engineer training. Through this project, you will have the chance to tackle a real-world industry-related challenge, putting into practice the knowledge you’ve gained. With dedicated mentoring sessions, you’ll receive guidance on how to effectively address the problem at hand. This capstone project serves as the concluding stage in your learning journey, enabling you to demonstrate your expertise to potential employers and showcase your ability to navigate and solve complex issues within the realm of Big Data Engineering.
Lesson 01: Data Engineer Capstone
Data Engineer Capstone
Master's Program Certificate
Electives
AWS Technical Essentials
Electives
Java Certification Training
Electives
Industry Master Class – Data Engineering
Get Ahead with Master Certificate
Get Ahead with Master Certificate
Differentiate yourself with a Masters Certificate
The expertise and Data Analytics experience gained through projects, simulations, and case studies will give you an edge over your competitors.
Share your achievement
Get Ahead with Master Certificate
Differentiate yourself with a Masters Certificate
The expertise and Data Analytics experience gained through projects, simulations, and case studies will give you an edge over your competitors.
Share your achievement
Why Online Bootcamp
Develop skills for real career growth
A state-of-the-art curriculum developed in collaboration with industry and education to equip you with the skills you need to succeed in today’s world.
Don’t listen to trainers who aren’t in the game. Learn from the experts who are in the game.
Leading Practitioners who deliver current best practice and case studies in sessions that fit within your workflow.
Learn by working on real-world problems
Capstone projects combining real-world data sets with virtual laboratories for hands-on experience.
Structured guidance ensuring learning never stops
With 24×7 mentorship support and a network of peers who share the same values, you’ll never have to worry about conceptual uncertainty again.
Big Data Engineer Course FAQs
Big data engineering plays a crucial role within the field of data science, encompassing a range of activities focused on constructing, upkeeping, evaluating, and refining big data solutions. This discipline places a strong emphasis on the creation of systems that facilitate seamless data movement and retrieval. Moreover, it involves the amalgamation of data from diverse sources, followed by the meticulous tasks of data cleansing and processing, ultimately rendering it prepared for comprehensive analysis. Through these processes, big data engineering ensures that data is effectively harnessed for insights and decision-making.
A Big Data Engineer plays a pivotal role in preparing data to be utilized for either analytical or operational purposes. This role encompasses a series of key responsibilities, including:
Data Pipeline Construction: Constructing data pipelines to effectively gather information from a variety of sources. Integration and Consolidation: Integrating and consolidating data from different origins, ensuring coherence and consistency. Data Cleansing: Cleaning and refining data to eliminate inconsistencies, inaccuracies, and redundancies. Data Utilization: Utilizing the data to cater to distinct analytics applications.
The scope of a Big Data Engineer’s role advances from the fundamental tasks of data collection and storage to encompass more sophisticated functions, including:
Data Transformation: Transforming data by applying processes such as labeling and optimization. Collaboration with Data Scientists: Collaborating with data scientists who employ queries and algorithms to perform predictive analyses on the collected data. Business Unit Interaction: Collaborating with business units to deliver aggregated data insights to executives.
Big Data Engineers are proficient in managing both structured and unstructured datasets, necessitating a sound understanding of diverse data architectures, applications, and programming languages like Spark, Python, and SQL. By having a comprehensive skill set, Big Data Engineers contribute significantly to the efficient handling and utilization of data, enabling organizations to make informed decisions based on data-driven insights. In most cases, big data Engineers collaborate with data scientists, who execute queries and algorithms based on the data collected for predictive analytics. They also collaborate with business units, providing aggregated data to executives.
Big Data Engineers typically work on both structured and non-structured datasets, which require them to be proficient in various data architectures, tools and programming languages, including Spark, Python and SQL.
This collaborative Big Data Engineer course, created in partnership with IBM, is designed to provide you with comprehensive knowledge of the Hadoop ecosystem, data engineering tools, and methodologies essential for excelling as a Big Data Engineer. Upon completion, you’ll possess industry-recognized certification from both IBM and Simplilearn, validating your acquired skills and practical expertise. This course will guide you through various topics, including Big Data, Hadoop clusters, MongoDB, PySpark, Kafka architecture, SparkSQL, and more, equipping you to become a proficient Big Data Engineer with a robust skill set.
Enrolling in the Big Data Engineer course, a joint effort with IBM, offers you the following benefits:
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Lifetime E-Learning Access: Gain unlimited access to the e-learning content for all the courses within the learning path.
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Industry-Recognized Certificates: Receive certificates from both IBM (for IBM-specific courses) and after successfully completing the course, validating your accomplishments.
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IBM Cloud Platform Access: Enjoy access to IBM cloud platforms, which include valuable tools like IBM Watson and other software, available for round-the-clock practice and exploration.
You will be awarded an IBM Certificate for the first course included in your Big Data Engineer course syllabus.
Upon meeting the following minimum requirements, you will qualify to receive the Master’s certificate, attesting to your proficiency as a Big Data Engineer:
Course: Big Data for Data Engineering
- Completion Certificate Required: Yes
- Criteria: Completion of at least 85% of the online self-paced content
Course: Big Data Hadoop and Spark Developer
- Completion Certificate Required: Yes
- Criteria: Either completion of at least 85% of the online self-paced content, or attendance of one Live Virtual Classroom session, and achieving a score above 75% in the course-end assessment, along with successful evaluation in at least one project
Course: PySpark Training
- Completion Certificate Required: Yes
- Criteria: Completion of at least 85% of the online self-paced content
Course: MongoDB Developer and Administrator
- Completion Certificate Required: Yes
- Criteria: Either completion of at least 85% of the online self-paced content, or attendance of one Live Virtual Classroom session, and achieving a score above 75% in the course-end assessment, along with successful evaluation in at least one project
Course: Apache Kafka
- Completion Certificate Required: Yes
- Criteria: Completion of at least 85% of the online self-paced content
Course: Big Data on AWS
- Completion Certificate Required: No
- Criteria: Attendance of one Live Virtual Classroom session and successful evaluation in at least one project
By fulfilling these requirements for each course, you will qualify for the Master’s certificate, showcasing your proficiency as a skilled Big Data Engineer.
