Get Started with Python

This course is part of Google Advanced Data Analytics Professional Certificate

Instructor: Google Career Certificates

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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

Details to know

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Assessments

20 quizzes

Taught in English

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This course is part of the Google Advanced Data Analytics Professional Certificate

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

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Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
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There are 5 modules in this course

This is the second of seven courses in the Google Advanced 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 the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate. 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 begin by exploring the basics of Python programming and why Python is such a powerful tool for data analysis. 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 videos7 readings4 quizzes3 ungraded labs

12 videosTotal 47 minutes

Introduction to Course 2 4 minutesPreview module
Welcome to module 11 minute
Adrian: My path to a data career2 minutes
Introduction to Python5 minutes
Discover more about Python6 minutes
Jupyter Notebooks2 minutes
Object-oriented programming4 minutes
Hamza: How Python helped my data science career2 minutes
Variables and data types5 minutes
Create precise variable names4 minutes
Data types and conversions4 minutes
Wrap-up1 minute

7 readingsTotal 130 minutes

Helpful resources and tips20 minutes
Course 2 overview20 minutes
Python versus other programming languages20 minutes
How to use Jupyter Notebooks20 minutes
More about object-oriented programming20 minutes
Explore Python syntax20 minutes
Glossary terms from Module 110 minutes

4 quizzesTotal 70 minutes

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

3 ungraded labsTotal 50 minutes

Annotated follow-along guide: Hello, Python!20 minutes
Activity: Use Python syntax20 minutes
Exemplar: Use Python Syntax10 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 quizzes5 ungraded labs

8 videosTotal 39 minutes

Welcome to module 23 minutesPreview module
Lateefat: Tips to address challenges when learning to code3 minutes
Define functions and returning values 6 minutes
Write clean code3 minutes
Use comments to scaffold your code6 minutes
Make comparisons using operators4 minutes
Use if, elif, else statements to make decisions10 minutes
Wrap-up1 minute

4 readingsTotal 60 minutes

Reference guide: Functions20 minutes
Reference guide: Python operators10 minutes
Reference guide: Conditional statements10 minutes
Glossary terms from module 220 minutes

3 quizzesTotal 59 minutes

Test your knowledge: Functions6 minutes
Test your knowledge: Conditional statements 8 minutes
Module 2 challenge45 minutes

5 ungraded labsTotal 80 minutes

Annotated follow-along guide: Functions and conditional statements20 minutes
Activity: Functions20 minutes
Exemplar: Functions10 minutes
Activity: Conditional statements20 minutes
Exemplar: Conditional statements10 minutes

Here, you’ll learn how to use iterative statements, or loops, to automate repetitive tasks. You’ll also learn how to manipulate strings using slicing, indexing, and formatting.

What's included

9 videos5 readings4 quizzes7 ungraded labs

9 videosTotal 40 minutes

Welcome to module 32 minutesPreview module
Michelle: Approach problems with an analytical mindset3 minutes
Introduction to while loops8 minutes
Introduction to for loops4 minutes
Loops with multiple range() parameters3 minutes
Work with strings3 minutes
String slicing6 minutes
Format strings4 minutes
Wrap-up2 minutes

5 readingsTotal 100 minutes

Loops, break, and continue statements20 minutes
For loops20 minutes
String indexing and slicing20 minutes
String formatting and regular expressions20 minutes
Glossary terms from module 320 minutes

4 quizzesTotal 68 minutes

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

7 ungraded labsTotal 110 minutes

Annotated follow-along guide: Loops and strings20 minutes
Activity: While loops20 minutes
Exemplar: While loops10 minutes
Activity: For loops20 minutes
Exemplar: For loops10 minutes
Activity: Strings20 minutes
Exemplar: Strings10 minutes

Now, you’ll explore fundamental data structures such as lists, tuples, dictionaries, sets, and arrays. 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

17 videos12 readings5 quizzes9 ungraded labs

17 videosTotal 87 minutes

Welcome to module 42 minutesPreview module
Introduction to lists4 minutes
Modify the contents of a list4 minutes
Introduction to tuples4 minutes
More with loops, lists, and tuples5 minutes
Introduction to dictionaries4 minutes
Dictionary methods4 minutes
Introduction to sets5 minutes
The power of packages4 minutes
Introduction to NumPy4 minutes
Basic array operations6 minutes
Introduction to pandas4 minutes
pandas basics10 minutes
Boolean masking5 minutes
Grouping and aggregation5 minutes
Merging and joining data8 minutes
Wrap-up 1 minute

12 readingsTotal 150 minutes

Reference guide: Lists20 minutes
Compare lists, strings, and tuples20 minutes
zip(), enumerate(), and list comprehension10 minutes
Reference guide: Dictionaries10 minutes
Reference guide: Sets10 minutes
Understand Python libraries, packages, and modules10 minutes
Python’s new versions and features10 minutes
Reference guide: Arrays10 minutes
The fundamentals of pandas10 minutes
Boolean masking in pandas 10 minutes
More on grouping and aggregation10 minutes
Glossary terms from module 4 20 minutes

5 quizzesTotal 83 minutes

Test your knowledge: Lists and tuples8 minutes
Test your knowledge: Dictionaries and sets6 minutes
Test your knowledge: Arrays and vectors with NumPy6 minutes
Test your knowledge: Dataframes with pandas8 minutes
Module 4 challenge 55 minutes

9 ungraded labsTotal 140 minutes

Annotated follow-along guide: Data structures in Python20 minutes
Activity: Lists & tuples 20 minutes
Exemplar: Lists & tuples 10 minutes
Activity: Dictionaries & sets20 minutes
Exemplar: Dictionaries & sets10 minutes
Activity: Arrays and vectors with NumPy20 minutes
Exemplar: Arrays and vectors with NumPy10 minutes
Activity: Dataframes with pandas20 minutes
Exemplar: Dataframes with pandas10 minutes

You will put everything you have learned about Python so far into practice with an end-of-course project. You will select a business problem from a list of options and use the given data to solve the problem. This project is an opportunity to demonstrate your skills and build a professional portfolio you can use to showcase your work to potential employers.