Coursera – Data Engineering Foundations – Specialization
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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.
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.
Skills you’ll gain
• Extraction, Transformation And Loading (ETL)
• Python Programming
• Relational Database Management System (RDBMS)
• Information Engineering
• SQL
Specialization – 5 course series
Data engineering is one of the fastest-growing tech occupations, where the demand for skilled data engineers far outweighs the supply. The goal of data engineering is to make quality data available for fact-finding and data-driven decision making. This Specialization from IBM will help anyone interested in pursuing a career in data engineering by teaching fundamental skills to get started in this field. No prior data engineering experience is required to succeed in this Specialization.
The Specialization consists of 5 self-paced online courses covering skills required for data engineering, including the data engineering ecosystem and lifecycle, Python, SQL, and Relational Databases. You will learn these data engineering prerequisites through engaging videos and hands-on practice using real tools and real-world databases. You’ll develop your understanding of data engineering, gain skills that can be applied directly to a data career, and build the foundation of your data engineering career.
Upon successfully completing these courses, you will have the practical knowledge and experience to delve deeper into data engineering and work on more advanced data engineering projects.
1. Introduction to Data Engineering
2. Python for Data Science, AI & Development
3. Python Project for Data Engineering
4. Introduction to Relational Databases (RDBMS)
5. Databases and SQL for Data Science with Python
5 Courses, Total, 479 Files, 91 Folders
Applied Learning Project
All courses in the Specialization contain multiple hands-on labs and assignments to help you gain practical experience and skills.
The projects range from working with data in multiple formats to transforming and loading that data into a single source to analyzing socio-economic data with SQL and working with advanced SQL techniques.
You will work hands-on with multiple real-world databases and tools including MySQL, PostgresSQL, IBM Db2, PhpMyAdmin, pgAdmin, IBM Cloud, Python, Jupyter notebooks, Watson Studio, etc.
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