IBM
Data Engineering Foundations Specialization
IBM

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

12,815 already enrolled

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Specialization - 5 course series

Get in-depth knowledge of a subject

4.7

(1,118 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.

Details to know

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Specialization - 5 course series

Get in-depth knowledge of a subject

4.7

(1,118 reviews)

Beginner level

Recommended experience

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

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Specialization - 5 course series

Introduction to Data Engineering

Course 112 hours4.7 (2,372 ratings)

What you'll learn

  • List basic skills required for an entry-level data engineering role.

  • Discuss various stages and concepts in the data engineering lifecycle.

  • Describe data engineering technologies such as Relational Databases, NoSQL Data Stores, and Big Data Engines.

  • Summarize concepts in data security, governance, and compliance.

Skills you'll gain

Category: Data Science
Category: Data Analysis
Category: Python Programming
Category: Numpy
Category: Pandas

Python for Data Science, AI & Development

Course 225 hours4.6 (35,369 ratings)

What you'll learn

  • Learn Python - the most popular programming language and for Data Science and Software Development.

  • Apply Python programming logic Variables, Data Structures, Branching, Loops, Functions, Objects & Classes.

  • Demonstrate proficiency in using Python libraries such as Pandas & Numpy, and developing code using Jupyter Notebooks.

  • Access and web scrape data using APIs and Python libraries like Beautiful Soup.

Skills you'll gain

Category: Python Programming
Category: Information Engineering
Category: Extract Transform and Load (ETL)
Category: Data Engineer
Category: Web Scraping

Python Project for Data Engineering

Course 39 hours4.6 (577 ratings)

What you'll learn

  • Demonstrate your skills in Python for working with and manipulating data

  • Implement webscraping and use APIs to extract data with Python

  • Play the role of a Data Engineer working on a real project to extract, transform, and load data

  • Use Jupyter notebooks and IDEs to complete your project

Skills you'll gain

Category: Python Programming
Category: Cloud Databases
Category: Relational Database Management System (RDBMS)
Category: SQL
Category: Jupyter notebooks

Introduction to Relational Databases (RDBMS)

Course 415 hours4.6 (518 ratings)

What you'll learn

  • Describe data, databases, relational databases, and cloud databases.

  • Describe information and data models, relational databases, and relational model concepts (including schemas and tables). 

  • Explain an Entity Relationship Diagram and design a relational database for a specific use case.

  • Develop a working knowledge of popular DBMSes including MySQL, PostgreSQL, and IBM DB2

Skills you'll gain

Category: Data Science
Category: Database (DBMS)
Category: Information Engineering
Category: SQL
Category: NoSQL

Databases and SQL for Data Science with Python

Course 520 hours4.6 (19,323 ratings)

What you'll learn

  • Analyze data within a database using SQL and Python.

  • Create a relational database and work with multiple tables using DDL commands.

  • Construct basic to intermediate level SQL queries using DML commands.

  • Compose more powerful queries with advanced SQL techniques like views, transactions, stored procedures, and joins.

Skills you'll gain

Category: Database (DB) Design
Category: Postgresql
Category: Relational Database Management System (RDBMS)
Category: Database Architecture
Category: MySQL

Instructors

Abhishek Gagneja
IBM
5 Courses102,433 learners
Joseph Santarcangelo
IBM
25 Courses1,346,540 learners

Offered by

IBM

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