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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4个模块

深入了解一个主题并学习基础知识。

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3 周在 10 小时一周

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4个模块

深入了解一个主题并学习基础知识。

20 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

98%

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

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作业

16 项作业

授课语言：英语（English）

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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 career 2分钟
Welcome to module 1 2分钟
Introduction to Python 5分钟
Discover more about Python 7分钟
Jupyter Notebooks 3分钟
Object-oriented programming 5分钟
Hamza: How Python helped my data science career 3分钟
Variables and data types 6分钟
Create precise variable names 5分钟
Data types and conversions 4分钟
Wrap-up 1分钟

10篇阅读材料总计84分钟

Course 7 overview 8分钟
Helpful resources and tips 8分钟
From spreadsheets to SQL to Python 10分钟
Python versus other programming languages 8分钟
Introduction to R 10分钟
Ways to learn about programming 12分钟
How to use Jupyter Notebooks 8分钟
More about object-oriented programming 8分钟
Explore Python syntax 8分钟
Glossary terms from module 1 4分钟

4个作业总计70分钟

Module 1 challenge 50分钟
Test your knowledge: Get started with the course 6分钟
Test your knowledge: The power of Python 6分钟
Test your knowledge: Using Python syntax 8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 syntax 60分钟
Exemplar: Use Python Syntax 20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 2 3分钟
Lateefat: Tips to address challenges when learning to code 3分钟
Define functions and return values 6分钟
Write clean code 4分钟
Use comments to scaffold your code 7分钟
Make comparisons using operators 4分钟
Use if, elif, else statements to make decisions 11分钟
Wrap-up 1分钟

4篇阅读材料总计32分钟

Reference guide: Functions 8分钟
Reference guide: Python operators 8分钟
Reference guide: Conditional statements 8分钟
Glossary terms from module 2 8分钟

3个作业总计64分钟

Module 2 challenge 50分钟
Test your knowledge: Functions 6分钟
Test your knowledge: Conditional statements 8分钟

5个非评分实验室总计180分钟

Annotated follow-along guide: Functions and conditional statements 20分钟
Activity: Functions 60分钟
Exemplar: Functions 20分钟
Activity: Conditional statements 60分钟
Exemplar: Conditional statements 20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 3 3分钟
Michelle: Approach problems with an analytical mindset 3分钟
Introduction to while loops 9分钟
Introduction to for loops 4分钟
Loops with multiple range() parameters 4分钟
Work with strings 4分钟
String slicing 7分钟
Format strings 5分钟
Wrap-up 2分钟

5篇阅读材料总计40分钟

Loops, break, and continue statements 8分钟
For loops 8分钟
String indexing and slicing 8分钟
String formatting and regular expressions 8分钟
Glossary terms from module 3 8分钟

4个作业总计68分钟

Module 3 challenge 50分钟
Test your knowledge: While loops 6分钟
Test your knowledge: For loops 6分钟
Test your knowledge: Strings 6分钟

7个非评分实验室总计260分钟

Annotated follow-along guide: Loops and strings 20分钟
Activity: While loops 60分钟
Exemplar: While loops 20分钟
Activity: For loops 60分钟
Exemplar: For loops 20分钟
Activity: Strings 60分钟
Exemplar: Strings 20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.