Data Engineering
About This Course
Master the skills to design, build, and maintain data pipelines that power analytics and AI. This course covers modern data engineering tools, cloud platforms, and best practices to ensure data is reliable, scalable, and ready for analysis. Learn through hands-on projects and real-world scenarios.
Learning Objectives
• Fundamentals of data engineering and ETL processes
• Data modeling and schema design
• SQL for querying and managing data
• Big Data frameworks (Hadoop, Spark)
• Cloud platforms (AWS, Azure, Google Cloud) for data engineering
• Data pipeline orchestration (Airflow, Azure Data Factory)
• Working with APIs and streaming data
• Data quality, governance, and security
• Integration with BI and analytics tools
• Performance optimization and scalability techniques
Target Audience
- • Aspiring data engineers and ETL developers
- • Software engineers transitioning into data roles
- • BI and analytics professionals
- • Data scientists looking to build data pipelines
- • Students aiming for careers in Big Data and cloud computing
Curriculum
Module 1: Introduction to Data Engineering
Module 2: Programming for Data Engineering
Module 3: Data Modeling
Module 4: Data Warehousing
Module 5: ETL/ELT Pipelines
Module 6: Big Data Technologies
Module 7: Cloud for Data Engineering
Module 8: Data Streaming and Real-Time Processing
Module 8: Data Streaming and Real-Time Processing
Module 9: Data Governance and Security
Module 10: Data Visualization
Module 11: Apache Airflow and Workflow Automation
Module 12: Monitoring and Optimization
Module 13: Data Engineering Projects
Module 14: Career Preparation
Your Instructors
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