Introduction to Data Analysis Using Python

This course is part of Google Data Analytics Professional Certificate

Instructor: Google Career Certificates

Access provided by Colegio de Estudios Superiores de Administracion - CESA

20,052 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

47 reviews

Beginner level

No prior experience required

Flexible schedule

3 weeks at 10 hours a week

Learn at your own pace

96%

Most learners liked this course

4 modules

Gain insight into a topic and learn the fundamentals.

47 reviews

Beginner level

No prior experience required

Flexible schedule

3 weeks at 10 hours a week

Learn at your own pace

96%

Most learners liked this course

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

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

16 assignments

Taught in English

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Build your Data Analysis expertise

This course is part of the Google Data Analytics Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate from Google

There are 4 modules in this course

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.

What's included

12 videos10 readings4 assignments3 ungraded labs

12 videos Total 46 minutes

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

10 readings Total 84 minutes

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

4 assignments Total 70 minutes

Test your knowledge: Get started with the course 6 minutes
Test your knowledge: The power of Python 6 minutes
Test your knowledge: Using Python syntax 8 minutes
Module 1 challenge 50 minutes

3 ungraded labs Total 100 minutes

Annotated follow-along guide: Hello, Python! 20 minutes
Activity: Use Python syntax 60 minutes
Exemplar: Use Python Syntax 20 minutes

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

8 videos Total 40 minutes

Welcome to module 2 3 minutes
Lateefat: Tips to address challenges when learning to code 3 minutes
Define functions and return values 6 minutes
Write clean code 4 minutes
Use comments to scaffold your code 7 minutes
Make comparisons using operators 4 minutes
Use if, elif, else statements to make decisions 11 minutes
Wrap-up 1 minute

4 readings Total 32 minutes

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

3 assignments Total 64 minutes

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

5 ungraded labs Total 180 minutes

Annotated follow-along guide: Functions and conditional statements 20 minutes
Activity: Functions 60 minutes
Exemplar: Functions 20 minutes
Activity: Conditional statements 60 minutes
Exemplar: Conditional statements 20 minutes

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

9 videos Total 40 minutes

Welcome to module 3 3 minutes
Michelle: Approach problems with an analytical mindset 3 minutes
Introduction to while loops 9 minutes
Introduction to for loops 4 minutes
Loops with multiple range() parameters 4 minutes
Work with strings 4 minutes
String slicing 7 minutes
Format strings 5 minutes
Wrap-up 2 minutes

5 readings Total 40 minutes

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

4 assignments Total 68 minutes

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

7 ungraded labs Total 260 minutes

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

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.