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Data Engineering Foundations Specialization

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Course Features

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Duration

5 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

Data engineering is one the fastest growing tech jobs. The demand for data engineers is far greater than the supply. Data engineering's goal is to provide quality data for fact-finding, data-driven decision-making and other purposes. The IBM Specialization in Data Engineering will assist anyone who is interested in pursuing a career as a data engineer by teaching the fundamental skills necessary to get started. This Specialization does not require any prior experience in data engineering. This Specialization is composed of five self-paced online courses that cover the skills needed for data engineering. These include Python, SQL and Relational databases. These prerequisites will be taught through engaging videos and practical practice with real tools and real databases. This course will help you to understand data engineering and gain the skills necessary for a career in data engineering. These courses will give you the skills and knowledge to work on advanced projects and delve deeper into data engineering.

Course Overview

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Python programming basics including data structures, logic, working with files, invoking APIs, using libraries such as Pandas and Numpy, doing ETL

Relational Database fundamentals including Database Design, Creating Schemas, Tables, Constraints, and working with MySQL, PostgreSQL & IBM Db2

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

Working knowledge of Data Engineering Ecosystem and Lifecycle Viewpoints and tips from Data professionals on starting a career in this domain

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