About our program that focuses big data engineer training in Sydney, created with IBM
IBM is one of the world’s leading technology brands and one of the most well-known in the industry. IBM has earned worldwide recognition in the industry, including five Nobel Prizes, six Turing Awards, 10 inductions in the U.S. Inventors Hall of Fame, nine U.S. National Medals of Technology, and five U.S. National Medals of Science.
They invest $6 billion into research and development annually, focusing on developing and growing technology. They are also the second-largest predictive analytics and machine learning provider worldwide.
Simplilearn and IBM have joined together to closely develop our latest big data engineer training in Sydney. This course is suitable for anyone looking to take the next step in their career, and for those who have an interest in data engineering, big data, or other technical fields.
What can I expect from this big data engineer training in Sydney that was created with IBM?
Upon completion of our big data engineer training in Sydney, students will graduate with two certificates, one from IBM and another from Simplilearn. These credentials help our students stand out in a large pool of job applications. You will also receive the following:
There are more than a dozen projects assigned to students in our big data engineer training in Sydney. These projects present scenarios to students that closely resemble the everyday tasks that big data engineers handle. They teach clusters, scalability, and other principles. Examples include:
Project 1: Use big data clusters the way other companies do
Project Title: Scalability-Deploying Multiple Clusters
Description: You are assigned with creating a new cluster on a new system, but because it can take a long time to set up new clusters, you will have to create a new cluster in the meantime on the existing system. You have also been tasked with testing the new cluster applications to ensure their effectiveness for this project in the big data engineer training in Sydney.
Project 2: Leverage big data clusters the same way large corporations do
Project Title: Working with Clusters
Description: Show your understanding of the following:
Project 3: Show how financial institutions, such as banks, stand out amongst their competition with big data analysis and insights
Domain: Banking
Description: A Portuguese bank has been working on a marketing campaign that advertises the benefits of investing in a bank term deposit. The campaign included calling potential customers on the phone, with some individuals being contacted numerous times. You are tasked with interpreting the information collected from these phone calls.
Project 4: Understand how telecom giants, such as AT&T, use big data to make decisions
Domain: Telecommunication
Description: After a mobile provider launched an Open Network Campaign, they wanted customers to submit complaints if they were experiencing any issues with their service, including signal issues with service interruptions. Customers who did experience difficulties with local towers submitted the requested complaints, and this information was collected accordingly.
The fourth and the fifth field of this data include the latitude and longitude of users, which is essential data for the cell phone provider to have. You must determine the latitude and longitude information on the basis of the available information and establish three clusters of users with a k-means algorithm.
Project 5: Understand how some of the most popular streaming services, like Netflix, leverage big data
Domain: The movie industry
Description: A college in the United States has acquired information from numerous movie reviews for a research project. You will execute various tasks with that data through Spark to collect important insights.
Project 6: Learn how online learning programs, such as Simplilearn, use NoSQL and big data
Domain: E-learning industry
Description: In this project, students are tasked with creating a web application with MongoDB for a top online school. It should support read and write scalability and give students the opportunity to practice hands-on with Servlet, HTML, Java, and other technical skills. Users should also be able to access, delete, remove, and add course information with MongoDB as the backend database.
After receiving your big data engineer training in Sydney, which was designed in collaboration with IBM, you may qualify for any of the following opportunities:
Students enrolled in our big data engineer training in Sydney learn all about big data frameworks and other technologies. With most organizations depending on big data each day to analyze past and future decisions, it is a career path with extreme growth potential. In fact, it is predicted that the industry is expected to grow tremendously by the year 2025.
In this program, students learn about different techniques and software required to work as big data engineers. Our course also teaches ingestion performance, database management system use, data replication and modeling, among other essentials. Students learn all about Spark ML, Impala, Scala, MongoDB, Pig, Flume, Advanced Architecture, Data Model Creation, Hive, and others.
After starting our big data engineer training in Sydney, you’ll learn the fundamentals of the Hadoop ecosystem, a key concept of big data engineering. You’ll also learn MapReduce, Pig, Sqoop, Impala, HBase, and others. When students complete our big data engineer training in Sydney, they can:
Big data engineers work on the development and maintenance of analytics infrastructures. This includes the inception and monitoring of architecture components and databases. With the dependence on big data anticipated to grow substantially by the year 2025, pursuing a career in big data engineering can be a good choice if you’re looking for an industry that promises stability and opportunities. Big data engineers work all around the world in different industries, and from small businesses to large corporations.
If you are trying to decide on a career path that typically pays a higher salary than the national average, working as a big data engineer can be a great choice. Glassdoor reports that on average, big data engineers earn $137,776 yearly.
If you’re ready to fast-track your new career in big data engineering, get started by applying for our big data engineer training in Sydney.
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.
Simplilearn’s Big Data Hadoop course lets you master the concepts of the Hadoop framework, Big data tools, and methodologies. Achieving a Big Data Hadoop certification prepares you for success as a Big Data Developer. This Big Data and Hadoop training help you understand how the various components of the Hadoop ecosystem fit into the Big Data processing lifecycle. Take this Big Data and Hadoop online training to explore Spark applications, parallel processing, and functional programming.
Get ready to add some Spark to your Python code with this PySpark certification training. This course gives you an overview of the Spark stack and lets you know how to leverage the functionality of Python as you deploy it in the Spark ecosystem. It helps you gain the skills required to become a PySpark developer.
Simplilearn’s Kafka certification lets you explore how to process huge amounts of data using various tools. You will understand how to better leverage Big data analytics with this Kafka training. Take advantage of our blended learning approach for this Kafka course and learn the basic concepts of Apache Kafka. Get ready to go through the cutting-edge curriculum of this Apache Kafka certification designed by industry experts and develop the job-ready skills of a Kafka developer.
Simplilearn’s MongoDB certification equips you with the relevant skills required to become a MongoDB Developer. The highly-qualified instructors for this MongoDB course help you understand why more businesses are using MongoDB development services to handle their increasing data storage and handling demands. Our MongoDB training is equipped with industry projects, lab exercises and various demos to explain key concepts. Enroll in our MongoDB online course and learn this popular NoSQL database
Simplilearn’s AWS Data Analytics certification training prepares you for all aspects of hosting big data and performing distributed processing on the AWS platform. Our AWS data analytics course is aligned with the AWS Certified Data Analytics Specialty exam and helps you pass it in a single try. Developed by industry leaders, this AWS certified data analytics training explores some interesting topics like AWS QuickSight, AWS lambda and Glue, S3 and DynamoDB, Redshift, Hive on EMR, among others
Simplilearn’s Big Data Capstone project will give you an opportunity to implement the skills you learned in the Big Data Engineer certification training. With dedicated mentoring sessions, you’ll know how to solve a real industry-aligned problem. The project is the final step in the learning path and will help you to showcase your expertise to employers.
Our Big Data Engineer Masters program is exhaustive and this certificate is proof that you have taken a big leap in mastering the domain.
The knowledge and Data Engineering skills you've gained working on projects, simulations, case studies will set you ahead of competition.
Talk about Big Data Engineer certification on LinkedIn, Twitter, Facebook, boost your resume, or frame it - tell your friends and colleagues about it.
Big data engineering is an important aspect of data science that involves building, maintaining, testing, and assessing big data solutions. It emphasizes the development of systems that allow for better flow and access to the data. It also incorporates the collection of data of disparate sources, cleaning, and processing data to make it ready for analysis.
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.
These Big Data Engineering courses developed in collaboration with IBM will give you insights into the Hadoop ecosystem, 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 Big Data Engineering course will train you on Big Data and Hadoop, Hadoop clusters, MongoDB, PySpark, Kafka architecture, SparkSQL, and much more to become an expert in Big Data Engineering.
As a part of this Big Data Engineer course, developed in collaboration with IBM you will receive the following:
You will get an IBM certificate for the first course present in the Big Data Engineer Course learning path.
Upon completion of the following minimum requirements, you will be eligible to receive the Master’s certificate for Big Data Engineering Certification that will testify to your skills as a Big Data Engineer.
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 |
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 Kafka | Required | 85% of online self-paced completion |
Big Data on AWS | Required | Attendance of one Live Virtual Classroom AND successful evaluation in at least one project |