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Learn Data Engineering, earn certificates with paid and free online courses from UC Irvine, UC Berkeley, Duke, Arizona State University and other top universities around the world. Read reviews to decide if a class is right for you.
Learn to architect enterprise data systems by designing staging areas, operational data stores, and data warehouses. Gain hands-on experience with Snowflake, data transformation, and OLAP reporting using real-world datasets.
Master advanced data engineering techniques for handling large-scale datasets, optimizing workflows, and implementing cutting-edge tools like Celery, Apache Airflow, and specialized databases for efficient data operations.
AWS DEA-C01 certification prep course with exercises and a full-length practice exam. Redshift, Glue, Athena, and more
Build Data Engineering Pipelines on AWS using Data Analytics Services - Glue, EMR, Athena, Kinesis, Lambda, Redshift
Explore how generative AI revolutionizes data engineering, enhancing productivity in architecture design, querying, schema design, data augmentation, pipelines, and analysis. Gain hands-on skills for real-world applications.
Learn essential data engineering concepts, AWS services, and tools for building, automating, and securing data solutions. Explore CI/CD, IaC, serverless applications, cost optimization, and authentication on AWS.
Master data engineering: build robust pipelines, implement ETL processes, and handle large datasets with Hadoop. Gain expertise in extracting, transforming, and loading data for efficient processing and analysis.
Explore data ecosystems, pipelines, ETL processes, and Apache Spark for big data handling. Gain essential skills for modern data engineering and large-scale data processing.
Discover key GenAI capabilities and practical strategies to enhance data engineering workflows, boost productivity, and future-proof skillsets in this transformative primer for data professionals.
Comprehensive program covering Python, SQL, databases, ETL, data warehousing, and big data. Gain hands-on skills for entry-level data engineering roles, including AI integration and career preparation.
In Data Engineering, learn how to interact with databases using SQL.
Master data manipulation using Python and SQL for data engineering. Extract, transform, and load data efficiently to drive insights and decision-making.
Gain the skills for building efficient and scalable data pipelines. Explore essential data engineering platforms (Hadoop, Spark, and Snowflake) and learn how to optimize them using Python, PySpark, and MLflow.
Become an expert in scaling data systems. Master Celery, Airflow, graph databases. Build real-world solutions for massive datasets and complex workflows. Optimize performance at enterprise scale.
This course provides foundational knowledge and skills to become a data engineer, covering the data ecosystem, tools, career paths, and real-world tasks.
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