What background is required?

No prior experience with spreadsheets or data analytics required. All you need is high school level math and curiosity about how things work.

What tools or platforms are included in the curriculum?

You'll learn to use analysis tools and platforms such as spreadsheets (Google Sheets or Microsoft Excel), SQL, presentation tools (Powerpoint or Google Slides), Tableau, Python, and Kaggle.

Which "spreadsheet" platform is being taught?

Learners can self-select which platform they want to use throughout the program, Google Sheets or Microsoft Excel. It’s entirely up to the learner’s preference, and all activities throughout the syllabus can be performed on either platform.

Do you need to take each course in course order?

We highly recommend completing the courses in the order presented because the content in each course builds on information from earlier lessons.

What will I get if I subscribe to this Certificate?

When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Introduction to Data Analysis Using Python

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Introduction to Data Analysis Using Python

本课程是 Google Data Analytics 专业证书的一部分

位教师：Google Career Certificates

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深入了解一个主题并学习基础知识。

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4个模块

深入了解一个主题并学习基础知识。

113 条评论

初级等级

无需具备相关经验

灵活的计划

3 周在 10 小时一周

自行安排学习进度

97%

大多数学生喜欢此课程

您将学到什么

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

您将获得的技能

类别：Code Reusability
类别：Scripting
类别：Data Analysis
类别：Analytical Skills
类别：Data Manipulation
类别：Data Cleansing
类别：Analytics
类别：Data Structures
类别：Object Oriented Programming (OOP)
类别：Programming Principles

您将学习的工具

类别：Pandas (Python Package)
类别：NumPy
类别：Python Programming

要了解的详细信息

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通过 Google 获得可共享的职业证书

该课程共有4个模块

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.

Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career. Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary. By the end of this course, you will: -Define what a programming language is and why Python is used by data scientists -Create Python scripts to display data and perform operations -Control the flow of programs using conditions and functions -Utilize different types of loops when performing repeated operations -Identify data types such as integers, floats, strings, and booleans -Manipulate data structures such as , lists, tuples, dictionaries, and sets -Import and use Python libraries such as NumPy and pandas

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.

涵盖的内容

12个视频10篇阅读材料4个作业3个非评分实验室

12个视频总计46分钟

Introduction to Course 7 4分钟
Adrian: My path to a data career2分钟
Welcome to module 12分钟
Introduction to Python5分钟
Discover more about Python7分钟
Jupyter Notebooks3分钟
Object-oriented programming5分钟
Hamza: How Python helped my data science career3分钟
Variables and data types6分钟
Create precise variable names5分钟
Data types and conversions4分钟
Wrap-up1分钟

10篇阅读材料总计84分钟

Course 7 overview8分钟
Helpful resources and tips8分钟
From spreadsheets to SQL to Python10分钟
Python versus other programming languages8分钟
Introduction to R10分钟
Ways to learn about programming12分钟
How to use Jupyter Notebooks8分钟
More about object-oriented programming8分钟
Explore Python syntax8分钟
Glossary terms from module 14分钟

4个作业总计70分钟

Test your knowledge: Get started with the course6分钟
Test your knowledge: The power of Python6分钟
Test your knowledge: Using Python syntax8分钟
Module 1 challenge50分钟

3个非评分实验室总计100分钟

Annotated follow-along guide: Hello, Python!20分钟
Activity: Use Python syntax60分钟
Exemplar: Use Python Syntax20分钟

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.

涵盖的内容

8个视频4篇阅读材料3个作业5个非评分实验室

8个视频总计40分钟

Welcome to module 23分钟
Lateefat: Tips to address challenges when learning to code3分钟
Define functions and return values 6分钟
Write clean code4分钟
Use comments to scaffold your code7分钟
Make comparisons using operators4分钟
Use if, elif, else statements to make decisions11分钟
Wrap-up1分钟

4篇阅读材料总计32分钟

Reference guide: Functions8分钟
Reference guide: Python operators8分钟
Reference guide: Conditional statements8分钟
Glossary terms from module 28分钟

3个作业总计64分钟

Test your knowledge: Functions6分钟
Test your knowledge: Conditional statements 8分钟
Module 2 challenge50分钟

5个非评分实验室总计180分钟

Annotated follow-along guide: Functions and conditional statements20分钟
Activity: Functions60分钟
Exemplar: Functions20分钟
Activity: Conditional statements60分钟
Exemplar: Conditional statements20分钟

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.

涵盖的内容

9个视频5篇阅读材料4个作业7个非评分实验室

9个视频总计40分钟

Welcome to module 33分钟
Michelle: Approach problems with an analytical mindset3分钟
Introduction to while loops9分钟
Introduction to for loops4分钟
Loops with multiple range() parameters4分钟
Work with strings4分钟
String slicing7分钟
Format strings5分钟
Wrap-up2分钟

5篇阅读材料总计40分钟

Loops, break, and continue statements8分钟
For loops8分钟
String indexing and slicing8分钟
String formatting and regular expressions8分钟
Glossary terms from module 38分钟

4个作业总计68分钟

Test your knowledge: While loops 6分钟
Test your knowledge: For loops 6分钟
Test your knowledge: Strings6分钟
Module 3 challenge50分钟

7个非评分实验室总计260分钟

Annotated follow-along guide: Loops and strings20分钟
Activity: While loops60分钟
Exemplar: While loops20分钟
Activity: For loops60分钟
Exemplar: For loops20分钟
Activity: Strings60分钟
Exemplar: Strings20分钟

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.

涵盖的内容

18个视频15篇阅读材料5个作业9个非评分实验室

18个视频总计89分钟

Welcome to module 42分钟
Introduction to lists5分钟
Modify the contents of a list4分钟
Introduction to tuples4分钟
More with loops, lists, and tuples6分钟
Introduction to dictionaries5分钟
Dictionary methods5分钟
Introduction to sets6分钟
The power of packages4分钟
Introduction to NumPy4分钟
Basic array operations6分钟
Introduction to pandas5分钟
pandas basics10分钟
Boolean masking6分钟
Grouping and aggregation6分钟
Merging and joining data9分钟
Wrap-up 2分钟
Course wrap-up 2分钟

15篇阅读材料总计88分钟

Reference guide: Lists8分钟
Compare lists, strings, and tuples8分钟
zip(), enumerate(), and list comprehension4分钟
Reference guide: Dictionaries4分钟
Reference guide: Sets8分钟
Understand Python libraries, packages, and modules8分钟
Python’s new versions and features4分钟
Reference guide: Arrays8分钟
The fundamentals of pandas4分钟
Boolean masking in pandas 4分钟
More on grouping and aggregation8分钟
Glossary terms from module 48分钟
Reflect and connect with peers4分钟
Course 7 glossary4分钟
Coming up next...4分钟

5个作业总计83分钟

Test your knowledge: Lists and tuples8分钟
Test your knowledge: Dictionaries and sets6分钟
Test your knowledge: Arrays and vectors with NumPy6分钟
Test your knowledge: Dataframes with pandas8分钟
Module 4 challenge55分钟

9个非评分实验室总计340分钟

Annotated follow-along guide: Data structures in Python20分钟
Activity: Lists & tuples 60分钟
Exemplar: Lists & tuples 20分钟
Activity: Dictionaries & sets60分钟
Exemplar: Dictionaries & sets20分钟
Activity: Arrays and vectors with NumPy60分钟
Exemplar: Arrays and vectors with NumPy20分钟
Activity: Dataframes with pandas60分钟
Exemplar: Dataframes with pandas20分钟

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学生评论

5 stars
82.45%
4 stars
10.52%
3 stars
0.87%
2 stars
1.75%
1 star
4.38%

显示 3/113 个

已于 Mar 7, 2026审阅

This course help me to grow my career and improve my profile as a data analyst

已于 Mar 27, 2026审阅

This course made me from Zero to Hero - Very Good Insights and very useful information

已于 May 17, 2026审阅

really good course, I just wish this entire program focused way more on hands on activities and guided projects than explanatory videos or videos about google employees experiences

常见问题

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.

You don't need to be a math all-star to succeed in the certificate. You need to be curious, and open to learning with numbers (the language of data analysts). Being a strong data analyst is more than just math, it's like about asking the right questions, finding the best sources to answer your question effectively and illustrating your findings clearly in visualizations.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

Introduction to Data Analysis Using Python

Introduction to Data Analysis Using Python

您将学到什么

您将获得的技能

您将学习的工具

要了解的详细信息

积累 Data Analysis 领域的专业知识

该课程共有4个模块

Hello, Python!

涵盖的内容

Functions and conditional statements

涵盖的内容

Loops and strings

涵盖的内容

Data structures in Python

涵盖的内容

获得职业证书

位教师

提供方

人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

学生评论

常见问题

What is data analytics?

Why start a career in data analytics?

Why enroll in the Google Data Analytics Certificate?