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IBM Data Engineering Professional Certificate

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Course Features

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Duration

15 months

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Beginner

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Effort

3 hours per week

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Teaching Type

Self Paced

Course Description

The Professional Certificate is for people who are looking to gain job-ready skills. The Professional Certificate will teach you how to use a variety databases and tools to manage both structured and unstructured data.

This Professional Certificate will equip you with the skills to perform important tasks in data engineering. You will use the Python programming language and Linux/UNIX shell commands to extract, transform, load (ETL) data. SQL statements will be used to query data and interact with Relational Databases. NoSQL databases can be used. You can also use unstructured data. Learn about Big Data and how to use Big Data engines like Spark and Hadoop. You will learn how to create Data Warehouses and how to use Business Intelligence tools to extract insights and analyze them.

Each course includes many practical projects and labs that will allow you to apply the concepts and skills you have learned. In the final capstone project, you will have all of these skills combined. This will enable you to design and implement a data platform that contains various data repositories and pipelines.

Course Overview

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Virtual Labs

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International Faculty

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Case Based Learning

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Post Course Interactions

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Case Studies,Hands-On Training,Instructor-Moderated Discussions

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Case Studies, Captstone Projects

Skills You Will Gain

Prerequisites/Requirements

Comfort working in either Linux, Windows, or MacOS

No prior programming or data skills needed

Your new career in Data Engineering is now possible. Master SQL, RDBMS and ETL with job-ready skills.

What You Will Learn

ETL, Data Pipelines using Python, Shell Scripts, Apache Airflow and Apache Kafka; Building & Populating Data Warehouses, and Querying with BI tools

NoSQL & Big Data concepts including practice with MongoDB, Cassandra, IBM Cloudant, Apache Hadoop, Apache Spark, SparkSQL, SparkML, Spark Streaming

SQL query language, SELECT, INSERT, UPDATE, DELETE statements, database functions, stored procs, working with multiple tables, JOINs, & transactions

RDBMS fundamentals including Design & Creation of Databases, Schemas, Tables; DB Administration, Security & working with MySQL, PostgreSQL & IBM Db2

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