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In this course, you will :
- RDBMS fundamentals include designing and creating databases, schemas, and tables, as well as database administration, security, and working with MySQL, PostgreSQL, and IBM Db2.
- SQL query language, SELECT, INSERT, UPDATE, and DELETE statements, database functions, stored procedures, working with multiple tables, JOINS, and transactions
- NoSQL and Big Data concepts are covered, as well as hands-on experience with MongoDB, Cassandra, IBM Cloudant, Apache Hadoop, Apache Spark, SparkSQL, SparkML, and Spark Streaming.
- ETL, Data Pipelines with Python, Shell Scripts, Apache Airflow, and Apache Kafka; Building and populating Data Warehouses; and Querying with BI Tools
Syllabus :
- Introduction to Data Engineering
- Python for Data Science, AI & Development
- Python Project for Data Engineering
- Introduction to Relational Databases (RDBMS)
- Databases and SQL for Data Science with Python
- Introduction to NoSQL Databases
- Introduction to Big Data with Spark and Hadoop
- Data Engineering and Machine Learning using Spark
- Hands-on Introduction to Linux Commands and Shell Scripting
- Relational Database Administration (DBA)
- ETL and Data Pipelines with Shell, Airflow and Kafka
- Getting Started with Data Warehousing and BI Analytics
- Getting Started with Data Warehousing and BI Analytics
- Data Engineering Capstone Project
