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- Learning materials, assignments, and helpful resources for professional certification. Expected Completion June 2023
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Throughout this Professional Certificate, you will complete hands-on labs and projects to help you gain practical experience with Python, SQL, relational databases, NoSQL databases, Apache Spark, building data pipelines, managing databases, and working with data warehouses.
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Tools: python, github, Watson Studio MySQL, IBM Db2, PostgreSQL, MongoDB, Cassandra, Hadoop, Apache Spark, SparkSQL, SparkML, SQL, Bash, Apache Airflow, Apache Kafka, IBM Cloudant,
IBM Data Engineering Professional Certificate
| Courses | |
|---|---|
| 1. | [Introduction to Data Engineering](create linked page) |
| 2. | [Python for Data Science, AI & Development](create linked page) |
| 3. | [Python Project for Data Engineering](create linked page) |
| 4. | [Introduction to Relational Databases (RDBMS)](create linked page) |
| 5. | [Databases and SQL for Data Science with Python](create linked page) |
| 6. | [Hands-on Introduction to Linux Commands and Shell Scripting](create linked page) |
| 7. | [Relational Database Administration (DBA)](create linked page) |
| 8. | [ETL and Data Pipelines with Shell, Airflow and Kafka](create linked page) |
| 9. | [Getting Started with Data Warehousing and BI Analytics](create linked page) |
| 10. | [Introduction to NoSQL Databases](create linked page) |
| 11. | [Introduction to Big Data with Spark and Hadoop](create linked page) |
| 12. | [Data Engineering and Machine Learning using Spark](create linked page) |
| 13. | [Data Engineering Capstone Project](create linked page) |
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