Certificate Program in
Data Engineering Course in Malaysia
- 40 Hours Classroom & elearning Sessions
- 20+ Hours Assignments
- 20+ Hours of Industry Use Cases
- 6 months Learning Management System access
- Blockchain enabled tamper-proof security certificate
Academic Partners & International Accreditations
Data Engineering Training Overview
The significant role of Data Engineers is to focus on processing data in a way that makes it easy for them to extract meaningful value from it. In this course, explore the various skills involved in laying down a successful foundation for digital transformation and facilitates the deployment of data science initiatives. Learn the tools and frameworks that data engineers need today to leverage AI, machine learning, and business intelligence skills to effectively manage data.
Data Engineering skills are constantly evolving with several skills unique to their profile. Learn advanced SQL techniques along with tools like Python, Keras, Pytorch, Spyder, etc. to handle a huge amount of data and solve real-world problems faster. Gain a thorough understanding of building data pipelines and integrating them smoothly with various data structures to keep pace with big data needs and implement data science and AI initiatives in your organizations.
What is Data Engineering?
To make data-driven decisions, data has to be collected, sorted, and analyzed giving results to quality data. This process of giving insights from data to businesses using advanced analytical tools is termed Data Engineering.
Data Engineering Training Learning Outcomes
Transforming data from a raw format to attractive analytical boards is a long journey that requires a dedicated environment known as data pipelines to obtain, process, and store data. Data Engineers are architects of these data platforms and give value to data analysis, business intelligence, and machine learning. In this course, you will learn to create and manage data infrastructures and build and deploy data pipelines to explore the various techniques to optimize large volumes of data and algorithms. You will also get to work with large and multi databases and learn how to create a Python data pipeline from scratch. Find out how tree data structures speed up the processing of data analysis. As you move on, you will also learn to work with complex data that are collected from multiple sources to build data processing systems. This course will give you an understanding of the skills involved in descriptive and inferential analysis and how data processing is optimized using various tools like NumPy. Also, learn to analyze data in Python and take a dive into object-oriented programming (OOP). Understand data warehouse and data manipulation and learn how to use Big Query ML to build different kinds of ML models. Join the Data Engineering course to get a hands-on introduction to developing and building data pipelines. Also-
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Industry Use Cases
Who Should Sign Up?
- Data professionals who work in conjunction with data science team
- Professionals aspiring to work on database designs and build data pipelines
- Professionals like ML developers, Data Engineers , Architects, Software developers
- Candidates from computer science and IT backgrounds aspiring to crack jobs in data engineering fields
- Professionals working as business intelligence analyst or database administrators
Data Engineering Course Modules
These modules are going to take you through the essential skills required to become a successful data engineer. You will learn how to gather, extract, transform, and then deploy data pipelines in the cloud. Using big data tools and real-time multiple databases you will gain expertise in skills of refining, and exchanging data. These modules are crafted keeping in mind the current industry trends and market requirements.
- Introduction Distributed Framework
- Apache Spark
- Core, SQL, MLlib
- Introduction to Apache Airflow
- Building Pipeline in Apache Airflow
- Deploy and Monitor Data Pipeline
- Production Data Pipeline
- Real Time Streaming on Cloud (Azure and GCP)
- Deploy and Monitor Data Pipelines
- Production Data Pipeline
- Connecting to Databases
- Data Lakes
- Populating a data lake
- Reading and Scanning the data lake
- Insert and Query a staging database
- Introduction to Pub/Sub Messaging System and Apache Kafka
- Building kafka Cluster
- Setup Zookeeper and Kafka Cluster
- Configuring and Testing Kafka Cluster
- Streaming Data with Apache Kafka
- Data Processing with Apache Spark and Databricks (public cloud)
Trends in Data Engineering Certification
A Data Engineer deals with delivering data analytics across various systems using data modeling, data storage, data transforming, and data maintenance. With high demand in the data engineering services market and with growth estimates from 18.3% to an unbelievable 31.5% p.a., consulting firms like Accenture and other tech companies like Cognizant are in dire need of data engineers who can capture big data, to govern, analyze, tag, and utilize. AI will take care of repetitive tasks in the field of quality assurance that will reduce the time consumed while performing these tasks.
With increasing development in software, data engineers will also be seen leveraging HTTP/3 in the layer of data collection for communicating across the web. For smooth exchange of data and distributed storage, the use of blockchain technology will also be seen in action along with the use of the AWS Lambda function by data engineers to process and execute data pipelines.
How we prepare you
Additional assignments of over 80+ hours
Live Free Webinars
Resume and LinkedIn Review Sessions
Lifetime LMS Access
Job placements in Data Engineering fields
Unlimited Mock Interview and Quiz Session
Hands-on experience in a live project
Offline Hiring Events
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