Data Engineering and Machine Learning using Spark (Coursera)
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Jan 29th 2024
IBM Data Engineering Professional Certificate
This Professional Certificate is for anyone who wants to develop job-ready skills, tools, and a portfolio for an entry-level data engineer position. Throughout the self-paced online courses, you will immerse yourself in the role of a data engineer and acquire the essential skills you need to work with a range of tools and databases to design, deploy, and manage structured and unstructured data.
By the end of this Professional Certificate, you will be able to explain and perform the key tasks required in a data engineering role. You will use the Python programming language and Linux/UNIX shell scripts to extract, transform and load (ETL) data. You will work with Relational Databases (RDBMS) and query data using SQL statements. You will use NoSQL databases and unstructured data. You will be introduced to Big Data and work with Big Data engines like Hadoop and Spark. You will gain experience with creating Data Warehouses and utilize Business Intelligence tools to analyze and extract insights.
Each course includes numerous hands-on labs & projects to apply the concepts and skills you learn. The program will culminate in a Capstone Project where you will bring together all of these skills to develop and implement an entire data platform with various data repositories and pipelines to address a real-world inspired data analytics problem.
WHAT YOU WILL LEARN
- RDBMS fundamentals including Design & Creation of Databases, Schemas, Tables; DB Administration, Security & working with MySQL, PostgreSQL & IBM Db2.
- SQL query language, SELECT, INSERT, UPDATE, DELETE statements, database functions, stored procs, working with multiple tables, JOINs, & transactions.
- NoSQL & Big Data concepts including practice with MongoDB, Cassandra, IBM Cloudant, Apache Hadoop, Apache Spark, SparkSQL, SparkML, Spark Streaming.
- ETL, Data Pipelines using Python, Shell Scripts, Apache Airflow and Apache Kafka; Building & Populating Data Warehouses, and Querying with BI tools.