Get Started with Python from Coursera

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

What's inside

Syllabus

Hello, Python!

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.

Functions and conditional statements

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.

Loops and strings

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.

Data structures in Python

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.

Course 2 end-of-course project

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.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Taught by Google employees, who are recognized experts in data analytics

For learners who want to enhance their data analysis capabilities

Covers core programming concepts, including variables, data types, functions, and loops

Provides an introduction to Python libraries such as NumPy and pandas, which are essential for advanced data analysis

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Get Started with Python with these activities:

Python Refresher Course

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Review Python basics through a refresher course or online resources to strengthen your foundation before starting the course.

Browse courses on Python Basics

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Enroll in a Python refresher course or find online tutorials
Review core Python concepts and syntax
Practice writing simple Python programs

Python Crash Course

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Read 'Python Crash Course' to quickly gain familiarity with Python basics and data analysis techniques.

View Python Crash Course, 3rd Edition: A Hands-On,... on Amazon

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Acquire a copy of the book or borrow it from a library
Set aside dedicated time for reading and practice
Read each chapter thoroughly and work through the exercises
Build small projects to apply your knowledge

Python Study Group

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Join or start a Python study group to learn from and collaborate with other students.

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Find a group or reach out to fellow students to form a group
Set regular meeting times and a schedule
Discuss topics, solve problems, and share knowledge
Provide feedback and support to each other

Three other activities

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Show all six activities

Python Practice Problems

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Solve Python practice problems on sites like HackerRank or LeetCode to reinforce your understanding of Python fundamentals.

Browse courses on Python Basics

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Create an account on a coding practice platform
Review the problems and select one to solve
Read through the problem statement and write out a solution
Implement your solution in Python
Test your solution against the given test cases

Python Tutorial for Data Analysis

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Follow a guided tutorial on Python for data analysis to gain hands-on experience with data manipulation and visualization.

Browse courses on Data Manipulation

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Find a reputable tutorial or course on Python for data analysis
Set aside dedicated time to work through the tutorial
Follow the instructions and complete the exercises
Experiment with the code and try to solve additional problems

Python Data Analysis Project

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Complete a small data analysis project using Python to apply your skills and build a portfolio.

Browse courses on Data Visualization

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Identify a suitable data set for analysis
Load the data into Python and explore it
Perform data analysis and create visualizations
Write a report or presentation to summarize your findings

Career center

Learners who complete Get Started with Python will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist combines programming skills such as Python and statistical knowledge to interpret large amounts of data. This course in Python, provided by Google, can help aspiring Data Scientists build a strong foundation for a successful career as they learn about essential programming concepts and how to solve complex problems with data.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts use a variety of analytical techniques and tools to transform raw data into actionable insights for businesses. By taking this comprehensive course in Python, Data Analysts can enhance their data analysis skills and improve their ability to solve real-world data-driven problems.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Machine Learning Engineers design, develop, and implement machine learning algorithms and models to automate complex tasks. This course in Python can provide a solid understanding of fundamental programming concepts for Machine Learning Engineers, helping them stay competitive in the field.

See salaries and explore the career path for Machine Learning Engineer

Software Engineer

Software Engineers apply their expertise in programming and computer science to design, develop, and maintain software systems. By enrolling in this beginner-friendly course in Python, Software Engineers can strengthen their proficiency in a widely used programming language and enhance their problem-solving skills.

See salaries and explore the career path for Software Engineer

Data Engineer

Data Engineers manage and process large volumes of data to make it usable for analysis and decision-making. This course in Python, offered by Google, can equip aspiring Data Engineers with the necessary programming skills to extract, transform, and load data, enabling them to excel in their roles.

See salaries and explore the career path for Data Engineer

Business Analyst

Business Analysts use data and analytical techniques to identify areas for improvement and optimize business processes. This course in Python can enhance their analytical skills and provide them with the tools to derive meaningful insights from data, driving informed decision-making within their organizations.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians collect, analyze, and interpret data to draw meaningful conclusions. This course in Python can bolster their technical abilities by providing a solid foundation in programming, which is increasingly used in statistical analysis, modeling, and data visualization, allowing them to stay at the forefront of their field.

See salaries and explore the career path for Statistician

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. The Python programming language is widely adopted in quantitative finance. By taking this beginner-friendly course in Python, aspiring Quantitative Analysts can build a solid foundation in programming and enhance their problem-solving skills, making them more competitive in this specialized field.

See salaries and explore the career path for Quantitative Analyst

Financial Analyst

Financial Analysts use financial data to make recommendations on investments and financial decisions. This course in Python can provide Financial Analysts with the programming skills necessary to extract, analyze, and visualize financial data, enabling them to perform complex financial modeling and analysis more efficiently.

See salaries and explore the career path for Financial Analyst

Marketing Analyst

Marketing Analysts use data and analytics to understand consumer behavior and market trends. This course in Python can provide them with the programming skills needed to collect, clean, and analyze marketing data, enabling them to make data-driven marketing decisions and optimize campaign performance.

See salaries and explore the career path for Marketing Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex business problems. This course in Python can equip them with the programming skills necessary to build optimization models, simulate scenarios, and analyze data, enabling them to contribute more effectively to data-driven decision making within their organizations.

See salaries and explore the career path for Operations Research Analyst

Actuary

Actuaries use mathematical and statistical models to assess risk and make financial decisions. This course in Python can provide them with the programming skills needed to analyze large amounts of data, develop financial models, and perform complex calculations, enabling them to excel in their roles and contribute to informed decision making within the insurance and finance industries.

See salaries and explore the career path for Actuary

Risk Analyst

Risk Analysts identify, assess, and manage risks within organizations. This course in Python can provide them with the programming skills needed to analyze data, build risk models, and perform simulations, enabling them to stay competitive in this rapidly evolving field.

See salaries and explore the career path for Risk Analyst

Software Developer

Software Developers design, develop, and maintain software applications. This course in Python can provide Software Developers with a strong foundation in a widely used programming language, enabling them to build robust, scalable, and maintainable software solutions.

See salaries and explore the career path for Software Developer

Web Developer

Web Developers design and develop websites and web applications. This course in Python can provide aspiring Web Developers with the programming skills necessary to create user-friendly, interactive, and visually appealing websites, enabling them to pursue their passion for web development.

See salaries and explore the career path for Web Developer