Comprehensive Data Engineering with Hands-on Experience

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About Course

The Comprehensive Data Engineering course is designed to equip learners with the knowledge and practical skills required to excel in the field of data engineering. Through a combination of theoretical concepts, hands-on exercises, and real-world projects, participants will gain a deep understanding of data engineering principles, tools, and techniques. By the end of this course, learners will be capable of building robust data pipelines, managing large-scale data systems, and applying best practices in data engineering.


Roles you can apply to as a Data Engineer


  1. Data Engineer:
  2. ETL Developer
  3. Data Integration Specialist
  4. Big Data Engineer
  5. Data Warehouse Engineer
  6. Data Platform Engineer
  7. DataOps Engineer:
  8. Data Quality Engineer

And many more!!!

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What Will You Learn?

  • Understand the role and importance of data engineering in modern data-driven organizations.
  • Gain proficiency in data modeling and designing efficient data architectures.
  • Learn various data storage and processing technologies, including databases, data lakes, and distributed systems.
  • Develop skills in building and managing scalable data pipelines.
  • Apply data transformation and integration techniques to clean and preprocess data.
  • Learn best practices for data quality, reliability, and data governance.
  • Acquire knowledge of real-time data processing and stream processing frameworks.
  • Explore data warehousing and business intelligence concepts.
  • Understand the fundamentals of cloud computing and its relevance to data engineering.
  • Work on hands-on projects to apply the learned concepts in real-world scenarios.

Course Content

Week 1: Introduction to Data Engineering

  • Understanding the role of data engineering in the data ecosystem
  • Overview of data engineering processes and workflows
  • Introduction to data engineering tools and technologies
  • Setting up the development environment

Week 2: Data Modeling and Design

Week 3: Data Storage and Processing Technologies

Week 4: Building Data Pipelines

Week 5: Data Transformation and Integration

Week 6: Data Quality and Reliability

Week 7: Real-time Data Processing

Week 8: Data Warehousing and Business Intelligence

Week 9: Cloud Computing and Data Engineering

Week 10-15: Hands-on Projects

Week 16: Course Recap and Final Project

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