Data Engineering Foundations Specialization

Data Engineering Foundations Specialization

Data Engineering Foundations Specialization Build the Foundation for a Data Engineering Career. Develop hands-on experience with Python, SQL, and Relational Databases and master the fundamentals of the Data Engineering ecosystem. Taught in English 22 languages available Some content may not be translated Instructors: Abhishek Gagneja +6 more Close Instructors Abhishek Gagneja IBM 5 Courses •

Description

Data Engineering Foundations Specialization

Data engineering is a rapidly growing field that encompasses a wide range of skills and knowledge. As organizations continue to collect and analyze vast amounts of data, the demand for skilled data engineers is on the rise. In order to meet this demand, Coursera has introduced the Data Engineering Foundations Specialization, which provides learners with the essential knowledge and skills needed to excel in the field of data engineering.

The Data Engineering Foundations Specialization consists of a series of courses that cover key concepts such as data modeling, data storage and retrieval, and data processing. These courses are designed to give learners a solid understanding of the foundational principles of data engineering, as well as hands-on experience with the tools and techniques used by data engineers in their day-to-day work.

One of the key highlights of the

Data Engineering Foundations Specialization

Build the Foundation for a Data Engineering Career. Develop hands-on experience with Python, SQL, and Relational Databases and master the fundamentals of the Data Engineering ecosystem.

Taught in English

Some content may not be translated

Abhishek Gagneja
Joseph Santarcangelo
Rav Ahuja

Instructors: Abhishek Gagneja

12,657 already enrolled

Specialization – 5 course series

Get in-depth knowledge of a subject

4.7

(1,105 reviews)

Beginner level

Recommended experience

2 months at 10 hours a week
Flexible schedule
Learn at your own pace

What you’ll learn

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

  • 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.

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