Online Course – Certified Professional Internship in Python, Bash, and Basic SQL for Data Engineering from Duke University

Advance your career in data engineering. Master the fundamental strategies and tools required to become proficient in developing data engineering and machine learning solutions.

Suggested by: Coursera (What is Coursera?)

Professional Certificate

Beginners

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Data Science
  • Big Data
  • Python programming
  • Bash (Unix command line)
  • Database Management System (DBMS)
  • Information Engineering
  • SQL
  • Web application

What you will learn in the course

Courses for which the course is suitable

  • Data Engineer
  • Data Analyst
  • Data Solutions Developer
  • SQL expert
  • Python developer
  • Bash key
  • Data Manager
  • Information Systems Analyst

Internship – 4-part course series

If you’re interested in developing the skills needed to become a data engineer, specializing in Python, Bash, and SQL is a great place to start. We live in a world driven by big data—from our web searches to the route we take to our favorite restaurant, and much more in between. Businesses and organizations use this data to make decisions that affect how we operate in our lives.

Key questions

  • How do engineers collect this data?
  • How can the data be organized so that it can be analyzed correctly?

A data engineer specializes in this initial stage of accessing, cleaning, and managing big data.

Basic requirements for data engineers

Data engineers today need a solid foundation in several essential areas:

  • Python
  • Bash
  • SQL

Python, Bash, and SQL course for data engineering

In the Python, Bash, and SQL for Data Engineering course, we provide a comprehensive and clear overview of these skills required to enter the world of data engineering. Led by three professional data engineers, this specialization will give you quick and accessible ways to learn data engineering strategies, offer you the opportunity to practice what you learn in practical exercises, and then you can immediately apply these techniques in your professional or academic life.

Hands-on Learning Project

Each course includes hands-on exercises using Visual Studio Code or Jupyter notebooks, giving you the opportunity to practice your Python, Bash, and SQL skills with real-world examples discussed in each course.

For each data engineering solution you delve into, you will also be encouraged to create a demo video and a code repository on GitHub that you can showcase in your digital portfolio to employers. By the end of this internship, you will have the foundational skills needed to start tackling more complex data engineering solutions.

Details of the courses that make up the specialization

Python and Pends for Data Engineering

Course 1

  • 51 hours
  • 4.6 (212 ratings)

Course Details

What you’ll learn
  • Setting up a fully-equipped Python project environment
  • Using Pandas libraries to read and write data to data structures and files
  • Writing Python code using Vim and Visual Studio Code
Skills you will acquire
  • Category: Data Structures
  • Category: Vim
  • Category: Python Programming
  • Category: Visual Studio Code
  • Category: Pandas

Linux and Bash for Data Engineering

Course 2

  • 65 hours
  • 4.6 (115 ratings)

Course Details

What you’ll learn
  • Using Linux tools to build data engineering solutions
  • Developing Bash syntax to configure and control Linux
Skills you will acquire
  • Category: Bash (Unix Shell)
  • Category: Databases (DBMS)
  • Category: Data Management
  • Category: Linux

Scripts with Python and SQL for data engineering

Course 3

  • 23 hours
  • 4.4 (91 ratings)

Course Details

What you’ll learn
  • Extracting data from various sources and mapping it to data structures in Python
  • Design scripts to connect and query SQL databases from Python
  • Using Scraping techniques to read and extract data from a website
Skills you will acquire
  • Category: Python Programming
  • Category: Databases (DBMS)
  • Category: SQL
  • Category: Web Scraping
  • Category: MySQL

Web applications and command-line tools for data engineering

Course 4

  • 43 hours
  • 4.3 (35 ratings)

Course Details

What you’ll learn
  • Building microservices in Python with FastAPI
  • Developing a command-line tool in Python using Click
  • Comparing several ways to set up and use a Jupyter notebook
Skills you will acquire
  • Category: Python Programming
  • Category: Cloud Calculators
  • Category: Command Line Interface
  • Category: Web Application
  • Category: Jupyter Calculators