IBM is the second-largest predictive analytics and Machine Learning solutions provider globally (The Forrester Wave report, September 2018). A joint partnership with Simplilearn and IBM introduces students to integrated blended learning, making them experts in Big Data and Data Engineering. The program in collaboration with IBM will make students industry ready to start their careers in Big Data and Data Engineer job roles. IBM is a leading cognitive solution and cloud platform company, headquartered in Armonk, New York, offering a plethora of technology and consulting services. Each year, IBM invests $6 billion in research and development and has achieved five Nobel prizes, nine US National Medals of Technology, five US National Medals of Science, six Turing Awards, and 10 Inductions in US Inventors Hall of Fame.
What can I expect from this Simplilearn program developed in collaboration with IBM?
Upon completion of this Master's Program, you will receive the certificates from IBM and Simplilearn in the Big Data Engineer courses in the learning path*. These certificates will testify to your skills as an expert in Data Engineering. You will also receive the following:
Big Data has a major impact on businesses worldwide, with applications in a wide range of industries such as healthcare, insurance, transport and logistics, and customer service. A role in this domain places you on the path to an exciting, evolving career that is predicted to grow sharply into 2025 and beyond. This co-developed Simplilearn and IBM Big Data Engineering Master's Program is designed to give you in-depth knowledge of the flexible and versatile frameworks on the Hadoop ecosystem and data engineering tools like Data Model Creation, Database Interfaces, Advanced Architecture, Spark, Scala, RDD, SparkSQL, Spark Streaming, Spark ML, GraphX, Sqoop, Flume, Pig, Hive, Impala, and Kafka Architecture. This integrated program will also teach you to model data, perform ingestion, replicate data, and shard data using a NoSQL database management system MongoDB. The course curriculum will give you hands-on experience connecting Kafka to Spark and working with Kafka Connect.
Big Data engineers create and maintain analytics infrastructure and are responsible for the development, deployment, maintenance, and monitoring of architecture components, such as databases and large-scale processing systems. The global Big Data and data engineering services market is expected to grow at a CAGR of 31.3 percent by 2025, so this is the perfect time to pursue a career in this field. The valuable skills you’ll acquire as a big data engineer will help you secure employment with companies as diverse as IBM, Coca-Cola, Ford Motors, Amazon, HCL, and Uber. Big Data engineers are employable across a variety of industries such as transportation, healthcare, telecommunications, finance, manufacturing, and many more. According to Glassdoor, the average annual salary for a data engineer is $137,776, with more than 130K jobs in this field worldwide.
The learning path ensures that you master the various components of the Hadoop ecosystem, such as MapReduce, Pig, Hive, Impala, HBase, and Sqoop, and learn real-time processing in Spark, Spark SQL, Spark streaming, Spark MLliB, GraphX programming, and shell scripting in Spark. By the end of this Big Data Engineer Master’s Program, you will:
This Big Data Engineer Master's program includes more than 12 real-life, industry-based projects on different domains to help you master concepts of Data Engineering, such as Clusters, Scalability, and Configuration. A few of the projects that you will be working on are mentioned below:
Project 1: See how large MNCs like Microsoft, Nestle, and PepsiCo set up their Big data clusters by gaining hands-on experience.
Project Title: Scalability-Deploying Multiple Clusters
Description: Your company wants to set up a new cluster and has procured new machines. However, setting up clusters on new machines will take time. Meanwhile, your company wants you to set up a new cluster on the same set of machines and start testing the new cluster’s working and applications.
Project 2: Understand how companies like Facebook, Amazon, and Flipkart leverage Big Data Clusters.
Project Title: Working with Clusters
Description: Demonstrate your understanding of the following tasks:
Project 3: See how banks like Citigroup, Bank of America, ICICI, and HDFC make use of Big Data to stay ahead of the competition.
Domain: Banking
Description: A Portuguese banking institution ran a marketing campaign to convince potential customers to invest in a bank term deposit. Their marketing campaigns were conducted through phone calls, and sometimes the same customer was contacted more than once. Your job is to analyze the data collected from the marketing campaign.
Project 4: Learn how Telecom giants like AT&T, Vodafone, and Airtel make use of Big Data by working on a real-life project based on telecommunication.
Domain: Telecommunication
Description: A mobile phone service provider has launched a new Open Network campaign. The company has invited users to raise complaints about the towers in their locality if they face issues with their mobile network. The company has collected the dataset of users who raised a complaint. The fourth and the fifth field of the dataset have a latitude and longitude of users, which is important information for the company. You must find this latitude and longitude information on the basis of the available dataset and create three clusters of users with a k-means algorithm.
Project 5: Understand how entertainment companies like Netflix, Amazon Prime leverage Big Data.
Domain: Movie Industry
Description: US-based university has collected datasets which represent reviews of movies from multiple reviewers as a part of the Research Project. To gain in-depth insights from research data collected you have to perform a series of tasks in Spark on the dataset provided.
Project 6: Learn how E-Learning companies like Simplilearn, Lynda, and Pluralsight make use of NoSQL and Big Data technology.
Domain: E-Learning Industry
Description: Design a web application for a leading E-learning organization using MongoDB to support read and write scalability. You can use web technologies such as HTML, JavaScript (JSP), Servlet, and Java. Using this web application, a user should able to add, retrieve, edit, and delete the course information using MongoDB as the backend database.
The course is ideal for anyone who wishes to pursue a career in data engineering. There are no prerequisites to take this course, but prior knowledge of the listed skills and technologies are beneficial, including:
If you are not familiar with these skill sets, don’t worry. You can enroll in the following courses from Simplilearn to get you started with Big Data Engineer Master’s Program:
This introductory course from IBM will teach you the basic concepts and terminologies of Big Data and its real-life applications across industries. You will gain insights on how to improve business productivity by processing large volumes of data and extract valuable information from them.
Switch career on Big Data Hadoop and Spark with Simplilearn's online training course on Big Data Hadoop. Master Big Data and Hadoop Ecosystem tools, such as HDFS, YARN, MapReduce, Hive, HBase, Spark, Flume, Sqoop, Hadoop Frameworks, Spark SQL and more concepts of Big Data processing life cycle. Work on real-time projects in Human Resource, Stock Exchange, BFSI, Retail & Payments and master concepts of Big Data Hadoop. This course also prepares you for Cloudera’s CCA175 Big Data certification.
Get ready to add some Spark to your Python code with this PySpark training! You’ll get 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. The course will show you how to build and implement data-intensive applications as you dive into the world of high-performance machine learning, leveraging Spark RDD, Spark SQL, Spark MLlib, Spark Streaming, HDFS, Sqoop, Flume, Spark GraphX, and Kafka.
This Big Data and Hadoop Administrator training course with furnish you with the aptitudes and methodologies necessary to excel in the fast-developing Big Data Analytics industry. With this Hadoop Admin training, you’ll learn to work with the adaptable, versatile frameworks based on the Apache Hadoop ecosystem, including Hadoop installation and configuration, cluster management with Sqoop, Flume, Pig, Hive, Impala, Cloudera, and Big Data implementations that have exceptional security, speed, and scale.
More businesses are using MongoDB development services—the most popular NoSQL database—to handle their increasing data storage and handling demands. The MongoDB Developer and Administrator certification equip you with the skills required to become a MongoDB experienced professional.
This Apache Cassandra Certification Training will develop your expertise in working with the high-volume Cassandra database management system as part of the Big Data Hadoop framework. With this Cassandra training, you will learn Cassandra concepts, features, architecture, and data model, and how to install, configure, and monitor open-source databases. The Cassandra course is ideal for software developers and analytics professionals who wish to further their careers in the Big Data field.
Advance your mastery of the Big Data Hadoop Ecosystem with Simplilearn’s Apache Spark and Scala certification training course. This course will help you will attain crucial, in-demand Apache Spark skills and develop a competitive advantage for an exciting career as a Hadoop developer.
Our Masters program is exhaustive and this certificate is proof that you have taken a big leap in mastering the domain.
The knowledge and skills you've gained working on projects, simulations, case studies will set you ahead of competition.
Talk about it on Linkedin, Twitter, Facebook, boost your resume or frame it - tell your friends and colleagues about it.
A Big Data Engineer prepares data for analytical or operational uses. Their primary roles include building data pipelines to collect information from various sources, integrating, combining, cleaning, and using data for individual analytics applications. Their role evolves from collecting and storing data to transforming, labeling, and optimizing data. Big Data engineers often work with data scientists who run queries and algorithms against the collected information for predictive analysis. They also work with business units to deliver data aggregations to executives. Big Data engineers commonly work with both structured and unstructured data sets, for which they must be well-versed in different data architectures, applications, and programming languages such as Spark, Python, and SQL.
This program co-developed with IBM will give you insights into the Hadoop ecosystem, Big Data & data engineering tools, and methodologies to prepare you for success in your role as a big data engineer. The industry-recognized certification from IBM and Simplilearn will attest to your new skills and on-the-job expertise. The program will train you on Big Data and Hadoop, Hadoop clusters, MongoDB, Pyspark, Kafka architecture, SparkSQL, and much more to become an expert in data engineering.
As a part of this online training, co-developed with IBM you will receive the following:
Upon completion of the following minimum requirements, you will be eligible to receive the Big Data Engineer Master’s Program certificate that will testify to your skills as a Big Data Engineer expert.
Course | Course Completion Certificate | Criteria |
Big Data for Data Engineering | Required | 85% of online self-paced completion |
Big Data Hadoop and Spark Developer | Required | 85% of online self-paced completion OR attendance of one Live Virtual Classroom, AND score above 75% in course-end assessment AND successful evaluation in at least one project |
Pyspark Training | Required | 85% of online self-paced completion |
Big Data and Hadoop Administrator | Required | 85% of online self-paced completion OR attendance of one Live Virtual Classroom, AND score above 75% in course-end assessment AND successful evaluation in at least one project |
MongoDB Developer and Administrator | Required | 85% of online self-paced completion OR attendance of one Live Virtual Classroom, AND score above 75% in course-end assessment AND successful evaluation in at least one project |
Apache Cassandra | Required | 85% of online self-paced completion |
Apache Spark and Scala | Required | 85% of online self-paced completion OR attendance of one Live Virtual Classroom, AND score above 75% in course-end assessment AND successful evaluation in at least one project |
Following are the list of courses for which you will get IBM certificates:
You can enroll in this training on our website and make an online payment using any of the following options:
Once payment is received you will automatically receive a payment receipt and access information via email.