This course is the seventh course in the Google Data Analytics Certificate. The Python programming language is a powerful tool for data analysis. In this course, you’ll learn the basic concepts of Python programming and how data professionals use Python on the job. You'll explore concepts such as object-oriented programming, variables, data types, functions, conditional statements, loops, and data structures.

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What you'll learn
Explain how Python is used by data professionals
Explore basic Python building blocks, including syntax and semantics
Understand loops, control statements, and string manipulation
Use data structures to store and organize data
Skills you'll gain
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January 2026
16 assignments
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There are 4 modules in this course
You’ll discover the main features and benefits of the Python programming language, and how Python can help power your data analysis. Python is an object-oriented programming language based on objects that contain data and useful code. You’ll become familiar with the core concepts of object-oriented programming: object, class, method, and attribute. You’ll learn about Jupyter Notebooks, an interactive environment for coding and data work. You’ll investigate how to use variables and data types to store and organize your data; and, you'll begin practicing important coding skills.
What's included
12 videos10 readings4 assignments3 ungraded labs
Next, you’ll discover how to call functions to perform useful actions on your data. You’ll also learn how to write conditional statements to tell the computer how to make decisions based on your instructions. And you’ll practice writing clean code that can be easily understood and reused by other data professionals.
What's included
8 videos4 readings3 assignments5 ungraded labs
You’ll start off by exploring loops, which repeat a portion of code until a process is complete. You’ll learn how to work with different kinds of iterative or repeating code, such as for loops and while loops. Then, you'll explore strings, which are sequences of characters like letters or punctuation marks. You’ll learn how to manipulate strings by indexing, slicing, and formatting them.
What's included
9 videos5 readings4 assignments7 ungraded labs
Now, you’ll explore data structures in Python, which are methods of storing and organizing data in a computer. You’ll focus on data structures that are among the most useful for data professionals: lists, tuples, dictionaries, sets, and arrays. You’ll also discover how to categorize data using data loading, cleaning, and binning. Lastly, you’ll learn about two of the most widely used and important Python tools for advanced data analysis: NumPy and pandas.
What's included
18 videos15 readings5 assignments9 ungraded labs
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Frequently asked questions
Data is a group of facts that can take many different forms, such as numbers, pictures, words, videos, observations, and more. Data analytics is the collection, transformation, and organization of these facts in order to draw conclusions, make predictions, and drive informed decision making. Companies need data analysts to sort through this data to help make decisions about their products, services or business strategies.
The amount of data created each day is tremendous. Any time you use your phone, look up something online, stream music, shop with a credit card, post on social media, or use GPS to map a route, you’re creating data. Companies must continually adjust their products, services, tools, and business strategies to meet consumer demand and react to emerging trends. Because of this, data analyst roles are in demand and competitively paid.
Data analysts make sense of data and numbers to help organizations make better business decisions. They prepare, process, analyze, and visualize data, discovering patterns and trends and answering key questions along the way. Their work empowers their wider team to make better business decisions.
You will learn the skill set required for becoming a junior or associate data analyst in the Google Data Analytics Certificate. Data analysts know how to ask the right question; prepare, process, and analyze data for key insights; effectively share their findings with stakeholders; and provide data-driven recommendations for thoughtful action.
You’ll learn these job-ready skills in our certificate program through interactive content (discussion prompts, quizzes, and activities) in under six months, with under 10 hours of flexible study a week. Along the way, you'll work through a curriculum designed with input from top employers and industry leaders, like Tableau, Accenture, and Deloitte. You’ll even have the opportunity to complete a case study that you can share with potential employers to showcase your new skill set.
After you’ve graduated from the program, you’ll have access to career resources and be connected directly with employers hiring for open entry-level roles in data analytics.
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