What is data engineering, and how is it different from data analytics?

Data engineering focuses on the systems, processes, and workflows used to prepare and make data available for use, while data analytics focuses on examining data to uncover insights. This Specialization builds technical skills that support reliable data workflows and downstream analysis.

Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Can I take the course for free?

No, you cannot take this course for free. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you cannot afford the fee, you can apply for financial aid.

Will I earn university credit for completing the Specialization?

This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

Python for Data Analytics and Engineering Specialization

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Python for Data Analytics and Engineering Specialization

Build Data Engineering Skills with Python.

Build practical Python, development, and data engineering skills for real-world data workflows.

Instructor: Barry Finder

Included with Learn more

3 course series

Get in-depth knowledge of a subject

Beginner level

Recommended experience

12 weeks to complete

at 5 hours a week

Flexible schedule

Learn at your own pace

3 course series

Get in-depth knowledge of a subject

Beginner level

Recommended experience

12 weeks to complete

at 5 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Use Python programming to solve practical problems and support data and development workflows.
Apply development tools and techniques to work with data, troubleshoot problems, and build technical solutions.
Apply data engineering concepts to prepare, manage, and support reliable data workflows for analysis and business use.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Taught in English

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Advance your subject-matter expertise

Learn in-demand skills from university and industry experts
Master a subject or tool with hands-on projects
Develop a deep understanding of key concepts
Earn a career certificate from Chegg Skills

Specialization - 3 course series

This Specialization is designed for learners who want to build practical programming and data engineering skills using Python and AI-enabled tools. Through three courses, you’ll develop Python programming skills, build a foundation in AI-enabled web development, and progress to data engineering concepts and workflows. By the end of the Specialization, you’ll be prepared to use Python and development tools to work with data, solve technical problems, and support the systems and processes that make data available for analysis and business use.

Applied Learning Project

Learners will complete hands-on activities and projects that reflect practical programming, development, and data engineering workflows. They’ll apply Python skills to solve technical problems, use AI-enabled tools to support development tasks, and practice working with data and data processes. Projects emphasize practical application, troubleshooting, evaluating outputs, and building skills that support reliable data workflows and downstream analysis.

Practical Python Programming

Course 1, 11 hours

What you'll learn

Write Python programs using foundational programming concepts and best practices.
Build reusable code with variables, functions, conditional logic, and loops.
Organize and manipulate data using Python collections, including lists, tuples, and dictionaries.
Develop the programming skills needed to pursue software development, data, AI, and automation pathways.

AI-Enabled Web Development Foundations

Course 2, 13 hours

What you'll learn

Build a strong foundation in Python programming using variables, data types, functions, collections, loops, and conditional logic.
Configure a professional development environment using Visual Studio Code, the terminal, and Google Colab.
Explain how Python supports modern web development through server-side programming, web frameworks, and AI-enabled applications.
Apply foundational programming concepts to develop simple Python programs for web development scenarios.

Skills you'll gain

Category: Web Development

Category: Python Programming

Category: Development Environment

Category: Server Side

Category: Web Applications

Category: AI Enablement

Category: AI Integrations

Category: Application Frameworks

Category: Integrated Development Environments

Category: Back-End Web Development

Category: Scripting

Category: Software Development Tools

Category: Hypertext Markup Language (HTML)

Category: Javascript

Category: Front-End Web Development

Category: Software Development

Category: Web Development Tools

Category: Cascading Style Sheets (CSS)

Category: Program Development

Category: Web Frameworks

Data Engineering with Python

Course 3, 15 hours

What you'll learn

Configure a Python development environment and use pandas to work with structured datasets.
Clean, transform, and prepare data by filtering records, handling missing values, and reshaping datasets.
Analyze and summarize data using Python and pandas to identify patterns and generate meaningful insights.
Apply Python programming techniques to support foundational data engineering workflows.

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Barry Finder

Chegg Skills

33 Courses430 learners

Offered by

Chegg Skills

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Frequently asked questions

Yes. We recommend completing the courses in the order presented, as each course builds on skills introduced in the previous one. You’ll begin with practical Python programming, progress to AI-enabled web development, and then apply those technical skills to data engineering concepts and workflows.

Course progression: Practical Python Programming → AI-Enabled Web Development Foundations → Data Engineering with Python

You’ll be prepared to use Python and development tools to solve technical problems, work with data, and apply data engineering concepts to support reliable data workflows and analysis.

No. You’ll begin by developing practical Python programming skills before progressing to development and data engineering applications.