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Python and Pandas for Data Engineering

Kennedy Behrman, Alfredo Deza, and Noah Gift

In this first course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will learn how to set up a version-controlled Python working environment which can utilize third party libraries. You will learn to use Python and the powerful Pandas library for data analysis and manipulation. Additionally, you will also be introduced to Vim and Visual Studio Code, two popular tools for writing software. This course is valuable for beginning and intermediate students in order to begin transforming and manipulating data as a data engineer.

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What's inside

Syllabus

Getting Started with Python

This week, you will learn how to set up an isolated Python environment with third party libraries and apply it by setting up a virtual environment including Pandas and Jupyter.

Essential Python

This week, you will learn how to create and use Python Sequences, Dictionaries, Sets, List Comprehensions, and Generators. Additionally, you will learn how to apply these by manipulating client data in a Jupyter notebook.

Data in Python: Pandas and Alternatives

This week, you will learn how to load data into a Pandas DataFrame and write statements to select columns and rows from a DataFrame. Additionally, you will apply comparison and boolean operators as a method of selecting data.

Python Development Environments

This week, you will learn the basics of some popular development environments and apply it by writing code in Vim and Visual Studio Code. Additionally, you will learn how to check your code into a Git repository.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches the fundamentals of Python, including data types, control flow, and functions

Covers advanced Python topics such as object-oriented programming and data analysis with Pandas

Introduces popular development environments such as Vim and Visual Studio Code

Provides hands-on experience with Python coding through Jupyter notebooks

Requires basic programming knowledge and familiarity with data structures

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python and Pandas for Data Engineering with these activities:

Review basic Python programming concepts

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Refreshing your understanding of basic Python programming concepts will provide a solid foundation for the more advanced topics covered in this course.

Browse courses on Python Basics

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Review online tutorials or documentation on Python basics
Practice writing simple Python programs

Review data science and machine learning concepts

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Refreshing your knowledge of data science and machine learning concepts will provide context for the application of Python in these fields.

Browse courses on Data Science

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Review lecture notes or textbooks on data science and machine learning
Complete practice problems or exercises

Participate in study groups or hackathons

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Engaging in study groups or hackathons provides opportunities to collaborate with peers, exchange ideas, and learn from different perspectives, fostering a deeper understanding.

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Find or create a study group with other students in the course
Establish regular meeting times and set discussion topics
Actively participate in discussions and ask questions

Five other activities

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Create a cheatsheet for Python syntax

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Creating a cheatsheet will help you remember and quickly reference key Python syntax rules, improving your efficiency and understanding of the language.

Browse courses on Python Syntax

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Review and identify essential Python syntax rules
Organize and categorize the rules into meaningful sections
Create a visually appealing and easy-to-read cheatsheet

Solve coding challenges on Python code review platforms

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Actively solving coding challenges will sharpen your Python problem-solving skills, enhance your understanding of data structures and algorithms, and prepare you for real-world programming scenarios.

Browse courses on Coding Challenges

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Join a reputable Python coding challenge platform
Select challenges that align with your learning goals
Attempt to solve the challenges independently
Review solutions and learn from others' approaches

Follow tutorials on advanced Python data manipulation techniques

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Exploring advanced data manipulation techniques through guided tutorials will enhance your proficiency in handling and transforming data, a crucial skill for data engineers.

Browse courses on Data Manipulation

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Identify specific areas where you want to improve your data manipulation skills
Find comprehensive tutorials that cover these advanced techniques
Follow the tutorials step-by-step and practice the techniques

Develop a data engineering project using Python

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Embarking on a data engineering project will provide hands-on experience in applying the skills and knowledge acquired in the course, solidifying your understanding and building your portfolio.

Browse courses on Data Analysis

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Identify a real-world problem or dataset that interests you
Design and implement a data engineering pipeline using Python
Document your project and share your findings

Contribute to open-source Python projects

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Contributing to open-source Python projects allows you to engage with the wider Python community, learn from experienced developers, and enhance your practical skills.

Browse courses on Software Development

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Identify open-source Python projects that align with your interests
Familiarize yourself with the project's codebase and documentation
Propose and implement improvements or fixes

Career center

Learners who complete Python and Pandas for Data Engineering will develop knowledge and skills that may be useful to these careers:

Data Engineer

Data Engineers wield Python and Pandas as essential tools for data analysis and manipulation, two skills that are highly sought after in the field. This course offers learners a chance to gain foundational knowledge in these technologies, building blocks necessary for a successful career in data engineering. Furthermore, it introduces learners to popular development tools like Vim and Visual Studio Code, empowering them to effectively write and maintain data engineering code.

See salaries and explore the career path for Data Engineer

Data Analyst

Data Analysts utilize Python and Pandas to uncover insights from raw data. This course in Python and Pandas for Data Engineering provides a solid foundation for aspiring Data Analysts, equipping them with the skills to clean, transform, and analyze large datasets. Moreover, exposure to development environments like Vim and Visual Studio Code fosters proficiency in writing and debugging code, essential qualities for Data Analysts.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Machine Learning Engineers employ Python and Pandas for preprocessing, data analysis, and model development. This course provides a comprehensive introduction to these technologies, offering a strong foundation for aspiring Machine Learning Engineers. By gaining proficiency in data manipulation and analysis, learners can build robust machine learning models that drive data-driven decision-making.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists heavily rely on Python and Pandas for data analysis and exploration. This course offers an excellent opportunity for aspiring Data Scientists to develop these core competencies. Through hands-on exercises and real-world examples, learners will master techniques for data cleaning, transformation, and visualization, laying the groundwork for successful careers in data science.

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Software Engineer

Software Engineers may work with Python and Pandas when developing data-driven applications. This course provides a valuable introduction to these technologies, helping Software Engineers expand their skillset and gain a competitive edge. By learning to manipulate and analyze data effectively, they can build more robust and efficient software solutions.

See salaries and explore the career path for Software Engineer

Financial Analyst

Financial Analysts frequently use Python and Pandas to analyze financial data and build models. This course provides a valuable introduction to these technologies, helping aspiring Financial Analysts enhance their skillset and stay competitive. By gaining proficiency in data manipulation and analysis, they can make more informed investment decisions and provide valuable insights to clients.

See salaries and explore the career path for Financial Analyst

Business Analyst

Business Analysts often leverage Python and Pandas for data analysis and presentation. This course offers a great opportunity for aspiring Business Analysts to develop these core competencies. Through practical exercises, learners will gain proficiency in manipulating and interpreting data, enabling them to make data-driven recommendations and drive business decisions.

See salaries and explore the career path for Business Analyst

Product Manager

Product Managers often work with data to understand user behavior and market trends. This course in Python and Pandas for Data Engineering provides a solid foundation for aspiring Product Managers, equipping them with the skills to analyze data effectively. By gaining proficiency in data manipulation and visualization, they can make data-driven decisions and build products that meet user needs.

See salaries and explore the career path for Product Manager

Marketing Manager

Marketing Managers leverage data to understand customer behavior and market trends. This course in Python and Pandas for Data Engineering provides a solid foundation for aspiring Marketing Managers, equipping them with the skills to analyze data effectively. By gaining proficiency in data manipulation and visualization, they can make data-driven marketing decisions and develop effective campaigns.

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Project Manager

Project Managers may encounter data analysis tasks during project planning and execution. This course offers a valuable introduction to Python and Pandas, providing aspiring Project Managers with the skills to handle data more effectively. By gaining proficiency in data manipulation and analysis, they can make informed decisions, track progress, and manage resources efficiently.

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Operations Manager

Operations Managers often rely on data to improve efficiency and optimize processes. This course offers a valuable introduction to Python and Pandas, providing aspiring Operations Managers with the skills to analyze data more effectively. By gaining proficiency in data manipulation and analysis, they can make informed decisions, allocate resources efficiently, and streamline operations.

See salaries and explore the career path for Operations Manager

IT Manager

IT Managers often oversee data-related projects and initiatives. This course provides a valuable introduction to Python and Pandas, helping aspiring IT Managers gain a deeper understanding of data management and analysis. By gaining proficiency in these technologies, they can make more informed decisions, allocate resources effectively, and ensure the smooth operation of IT systems.

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Risk Manager

Risk Managers analyze data to identify and assess potential risks. This course in Python and Pandas for Data Engineering provides a solid foundation for aspiring Risk Managers, equipping them with the skills to handle data effectively. By gaining proficiency in data manipulation and visualization, they can make data-driven decisions and develop effective risk management strategies.

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Sales Manager

Sales Managers often leverage data to understand customer behavior and identify sales opportunities. This course in Python and Pandas for Data Engineering provides a solid foundation for aspiring Sales Managers, equipping them with the skills to analyze data effectively. By gaining proficiency in data manipulation and visualization, they can make data-driven sales decisions and develop effective sales strategies.

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UX Designer

UX Designers may use data to understand user behavior and improve user experience. This course offers a valuable introduction to Python and Pandas, providing aspiring UX Designers with the skills to analyze data more effectively. By gaining proficiency in data manipulation and visualization, they can make data-driven design decisions and create user-centric products.

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Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Python and Pandas for Data Engineering.

Python for Data Analysis

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Practical guide to using Python for data analysis. It covers all the essential topics, from data loading and cleaning to data visualization and modeling.

Python and Pandas for Data Engineering

What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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