Adjibar

AWS & Azure Data Engineering Bootcamp

Master the Skills to Become a Data Engineering Expert

Elevate your career with our advanced AWS & Azure Data Engineering Bootcamp. Tailored for professionals aiming to excel in data engineering, our program covers key tools and techniques such as PySpark, ETL, and more. With a 97% placement rate, our bootcamp ensures you are industry-ready. Get comprehensive support including hiring assistance, interview coaching, resume preparation, and more.

Our Program:

Course Duration

14-16 Weeks

Enroll By

July 01, 2024

Course Type

Online

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Our AWS & Azure Data Engineering Curriculum

Our comprehensive course is designed to help you master data engineering with a focus on AWS and Azure. From foundational concepts to advanced techniques, you will develop the skills needed to tackle real-world problems and create data-driven solutions.

  • Module - 1

    Introduction to Data Engineering

    Fundamentals of Data Engineering

    Learn the core concepts of data engineering, including data modeling, data warehousing, and data architecture.

    Data Pipelines

    Understand how to design and implement data pipelines for ETL processes.

  • Module - 2

    AWS Data Engineering

    AWS Fundamentals

    Learn about the foundational services of AWS, including EC2, S3, and RDS, and how they can be leveraged for data engineering workloads.

    AWS Data Tools

    Explore AWS tools such as Glue, Redshift, and EMR for data processing and analytics.

    Building Data Pipelines on AWS

    Gain hands-on experience in building scalable and efficient data pipelines using AWS services.

  • Module - 3

    Azure Data Engineering

    Azure Fundamentals

    Learn about the core services of Azure, including Azure Storage, Azure SQL Database, and Azure Synapse Analytics.

    Azure Data Tools

    Explore Azure tools such as Databricks, Data Factory, and HDInsight for data engineering tasks.

    Building Data Pipelines on Azure

    Gain hands-on experience in constructing data pipelines using Azure services.

  • Module - 4

    Data Processing with PySpark

    Introduction to PySpark

    Get an overview of PySpark and its role in big data processing.

    PySpark for Data Processing

    Learn how to use PySpark for data processing tasks, including data transformation and aggregation.

    Advanced PySpark Techniques

    Explore advanced techniques in PySpark for optimizing data processing workflows.

  • Module - 5

    ETL Processes and Data Integration

    ETL Concepts

    Understand the principles of ETL (Extract, Transform, Load) processes and their importance in data engineering.

    Building ETL Pipelines

    Learn how to design and implement ETL pipelines using AWS Glue and Azure Data Factory.

    Data Integration Techniques

    Explore various data integration techniques and tools to consolidate data from multiple sources.

  • Module - 6

    Data Warehousing and Analytics

    Data Warehousing Concepts

    Learn about data warehousing concepts and architectures.

    Building Data Warehouses

    Gain hands-on experience in building data warehouses using Amazon Redshift and Azure Synapse Analytics.

    Data Analytics

    Explore data analytics techniques and tools to derive insights from data.

  • Module - 7

    Advanced Data Engineering Techniques

    Data Security and Governance

    Learn about data security best practices and governance frameworks.

    Data Engineering Automation

    Explore automation techniques in data engineering to streamline workflows.

    Scalable Data Architectures

    Understand how to design scalable and resilient data architectures.

Why Data Engineering Course is in Demand

Market Overview

01

Data Engineering is the process of designing, building, and maintaining systems that collect, store, and process data. It is a crucial aspect of data-driven organizations and enables efficient and effective data analysis.

02

The demand for people with Data Engineering skills is on the rise, with tech-industry careers such as Data Science, Machine Learning, Business Intelligence, and Analytics relying on data-driven insights for decision-making.

03

Data Scientists, Machine Learning Engineers, Business Intelligence Analysts, and Analysts can benefit from Data Engineering knowledge and skills. If unsure about its relevance, research how it is used in your field.

04

Staying updated with the latest tools and techniques in Data Engineering is essential for career growth and competitiveness in the tech industry.

What Our Learners Are Saying

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Yonas Kebede

Data Engineer, Amazon

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This bootcamp honed my skills in data processing and distributed systems. The real-life case studies were particularly impactful for my professional development.

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Meron Tadesse

AI Specialist, Intel Corporation

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I was amazed by how much practical, hands-on AI knowledge I gained. The course bridged the gap between theory and practice, and the community was incredibly supportive.

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Tsion Girma

Data Scientist, Microsoft

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The curriculum was challenging but well-structured, making complex concepts digestible. I'm now confidently applying machine learning models in my work.

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Dawit Mengistu

Machine Learning Engineer, IBM Watson

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Adjibar Coding Bootcamp empowered me to work on cutting-edge AI projects. The instructors' dedication and the collaborative environment made all the difference.

Learn More About Data Engineering

An Introduction to Data Engineering

Our Data Engineering courses provide a comprehensive understanding of data architecture, data warehousing, ETL processes, and big data technologies. These courses are available at both beginner and advanced levels, allowing professionals to choose based on their expertise and career goals. Enrollment in these courses includes specific fees, with optional support for Python, SQL, and other relevant programming languages.

The Purpose of Data Engineering Courses

Given the growing demand for data engineering skills, obtaining a certification in this field can open new career opportunities. Our Data Engineering courses enhance your analytical thinking, problem-solving skills, and technical expertise. With a certification in data engineering, you'll possess the knowledge and capabilities needed to thrive in this rapidly evolving industry.

The Growing Global Demand for Data Engineering Courses

As data complexity continues to increase, our Data Engineering courses prepare ambitious professionals to tackle real-world challenges effectively. These courses equip you with the skills to develop data pipelines, perform ETL operations, and manage data at scale.

Moreover, these skills are applicable across various fields such as finance, healthcare, retail, and more, which increasingly rely on data-driven insights. Therefore, to stay ahead in your career, consider enrolling in our Data Engineering courses.

Our Advanced Data Engineering Curriculum Covers:

Our programs cover significant areas such as:

  • Data Modeling - Learn how to create effective data models that support business requirements.
  • ETL Processes - Master the techniques of extracting, transforming, and loading data from various sources.
  • Big Data Technologies - Gain expertise in big data tools such as Hadoop, Spark, and Kafka for processing and analyzing large datasets.
  • Cloud Data Engineering - Understand how to leverage cloud platforms like AWS and Azure for scalable and efficient data engineering solutions.
  • Data Governance - Learn best practices for managing and securing data to ensure compliance and integrity.
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