Tuesday 2 January 2024

Data Engineering Foundations Specialization


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.

Join Free:Data Engineering Foundations Specialization

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. 

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.


Post a Comment

Popular Posts


AI (27) Android (24) AngularJS (1) Assembly Language (2) aws (17) Azure (7) BI (10) book (4) Books (120) C (77) C# (12) C++ (82) Course (64) Coursera (182) Cybersecurity (24) data management (11) Data Science (98) Data Strucures (6) Deep Learning (10) Django (6) Downloads (3) edx (2) Engineering (14) Excel (13) Factorial (1) Finance (6) flutter (1) FPL (17) Google (19) Hadoop (3) HTML&CSS (46) IBM (25) IoT (1) IS (25) Java (92) Leet Code (4) Machine Learning (46) Meta (18) MICHIGAN (5) microsoft (4) Pandas (3) PHP (20) Projects (29) Python (772) Python Coding Challenge (256) Questions (2) R (70) React (6) Scripting (1) security (3) Selenium Webdriver (2) Software (17) SQL (40) UX Research (1) web application (8)


Person climbing a staircase. Learn Data Science from Scratch: online program with 21 courses