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Certificate Program in

Data Engineering Course in Malaysia

With Data Engineering, learn to optimize, label, explore, transform and move data to produce meaningful and useful insights to empower your business.
  • 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
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Academic Partners & International Accreditations
  • Data Engineering Course with Microsoft
  • Data Engineering certification with nasscomm
  • Data Engineering certification innodatatics
  • Data Engineering certification with SUNY
  • Data Engineering certification with NEF

Calendar-for-Virtual Interactive Classes

Start Date

Data Engineering

business analytics course duration in Jodhpur

Total Duration

3 Months

data engineering course


  • Need basic programming skills
  • Python knowledge is highly recommended
  • SQl/Nosql experience is highly desired
  • Basic knowledge on Linux platform

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-

Understand the meaning of Data Engineering and its ecosystem
Learn to extract data from multiple files and databases
Learn to construct and deploy a data pipeline in production
Work with various file formats in both NoSQL and Relational databases
Master the skills and techniques to refine, transform, and add value to your data
Explore the various data structures including Linked Lists, Stacks, Dictionaries, Queues, etc.

Block Your Time

data engineering course

40 hours

Classroom &
elearning sessions

data engineering course

20+ hours


Data engineering course

20+ hours

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)
Data Pipeline Modules - Self-Paced Learning Modules
How we prepare you
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    Lifetime LMS Access
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    Job placements in Data Engineering fields
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    Hands-on experience in a live project
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