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Python is one of the most popular and in-demand programming languages in the world — largely because of how readable and versatile it is. If you’re interested in learning Python, this free, introductory course will demonstrate how learning to code in Python could benefit your career. No previous programming experience is required.

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Python is one of the most popular and in-demand programming languages in the world — largely because of how readable and versatile it is. If you’re interested in learning Python, this free, introductory course will demonstrate how learning to code in Python could benefit your career. No previous programming experience is required.

From analyzing large datasets to building web applications, Python can be used for a variety of projects including:

- Writing scripts for automating tasks

-Web development

-Collecting data from websites (also known as “web scraping”)

-Scientific and numeric computing

-Data analysis

-Data visualization

-Machine learning

Python is also a useful skill applicable to roles across a wide range of industries, including:

-Energy

-Finance

-Healthcare

-Marketing

-IT

-Retail

This course is an introduction to our Boot Camps, which combine data analysis and machine learning to prepare learners for careers such as data analysts, financial analysts, data scientists, and more.

This Try It is offered in support of the Data Analytics Boot Camp and Coding Boot Camp with The Ohio State University. If you enroll in this Try It, your learner data will not be shared with The Ohio State University unless you enroll in the Data Analytics Boot Camp or Coding Boot Camp.

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What's inside

Learning objectives

  • -what python is and where it’s used.
  • -functions, the bits of code that tell python what to do.
  • -how to create and name variables.
  • -how to build conditional logic to automate dual-alternative decision-making.
  • -how to use python for advanced decision making with nested if/else statements.
  • -how python interacts with a console.
  • -how to code simple programs and use conditional statements to automate decision-making.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Introduces Python and its versatile applications, catering to beginners with no prior programming experience
Covers a range of practical use cases, from data analysis and web development to scientific computing and machine learning, demonstrating Python's wide applicability
Explores key Python concepts like functions, variables, and conditional logic, laying a solid foundation for further programming endeavors
Provides a hands-on approach to programming, allowing learners to apply their knowledge and build simple programs
Part of a series of Boot Camps offered by The Ohio State University, offering a structured pathway for career advancement in data analytics and machine learning
Assumes no prior programming knowledge, making it accessible to absolute beginners

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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 Try It: Intro to Python with these activities:
Refresh Python syntax
Understanding Python syntax is essential for success in this course. This activity will help you review the basics of Python syntax and ensure you are ready to build on this foundation.
Browse courses on Python Syntax
Show steps
  • Review online tutorials on Python syntax
  • Complete practice exercises on Python syntax
  • Take a quiz on Python syntax to test your understanding
Read Python Crash Course, 2nd Edition by Eric Matthes
This book provides a comprehensive introduction to Python and is a valuable resource for beginners who want to learn the basics of Python.
Show steps
  • Purchase or borrow a copy of the book
  • Read the book cover-to-cover
  • Complete the practice exercises in the book
Create a Python learning resource collection
Compiling your own collection of Python learning resources will help you organize your learning materials and make it easier to find the information you need.
Show steps
  • Gather Python learning resources from various sources
  • Categorize and organize the resources
  • Create a central location for your resource collection
Two other activities
Expand to see all activities and additional details
Show all five activities
Create a Python program
Creating your own Python program will allow you to apply your Python skills to a practical problem and demonstrate your understanding of Python concepts.
Show steps
  • Identify a problem that you can solve using Python
  • Design and code a Python program to solve the problem
  • Test and debug your program to ensure it works correctly
  • Document your program and share it with others
Contribute to an open source Python project
Contributing to an open source Python project will allow you to apply your Python skills to a real-world project and make a meaningful contribution to the Python community.
Show steps
  • Identify an open source Python project that interests you
  • Read the project documentation and familiarize yourself with the codebase
  • Identify an area where you can contribute
  • Submit a pull request with your proposed changes

Career center

Learners who complete Try It: Intro to Python will develop knowledge and skills that may be useful to these careers:
Financial Analyst
Financial analysts use data to make recommendations about investments and financial decisions. Python is a popular programming language for financial analysts because it is easy to learn and use, and it has a wide range of libraries and tools for financial analysis. This course provides an introduction to Python, including how to use it to automate tasks, collect data from websites, and perform data analysis. This course may be particularly useful for financial analysts who are looking to learn more about Python or who want to use Python for financial analysis projects.
Data Analyst
Data analysts are responsible for collecting, cleaning, and analyzing data to extract meaningful insights. Python is a popular programming language for data analysts because it is easy to learn and use, and it has a wide range of libraries and tools for data analysis. This course provides an introduction to Python, including how to use it to automate tasks, collect data from websites, and perform data analysis. This course may be particularly useful for data analysts who are looking to learn more about Python or who want to use Python for data analysis projects.
Data Scientist
Data scientists use data to build models and make predictions. Python is a popular programming language for data scientists because it is easy to learn and use, and it has a wide range of libraries and tools for machine learning and data science. This course provides an introduction to Python, including how to use it to automate tasks, collect data from websites, and perform data analysis. This course may be particularly useful for data scientists who are looking to learn more about Python or who want to use Python for data science projects.
Operations Research Analyst
Operations research analysts use data to solve business problems. Python is a popular programming language for operations research analysts because it is easy to learn and use, and it has a wide range of libraries and tools for optimization. This course provides an introduction to Python, including how to use it to automate tasks, collect data from websites, and perform data analysis. This course may be particularly useful for operations research analysts who are looking to learn more about Python or who want to use Python for operations research projects.
Statistician
Statisticians collect, analyze, and interpret data. Python is a popular programming language for statisticians because it is easy to learn and use, and it has a wide range of libraries and tools for statistics. This course provides an introduction to Python, including how to use it to automate tasks, collect data from websites, and perform data analysis. This course may be particularly useful for statisticians who are looking to learn more about Python or who want to use Python for statistics projects.
Software Engineer
Software engineers design, develop, and maintain software systems. Python is a popular programming language for software engineers because it is easy to learn and use, and it has a wide range of libraries and tools for software development. This course provides an introduction to Python, including how to use it to build simple programs and use conditional statements to automate decision-making. This course may be particularly useful for software engineers who are looking to learn more about Python or who want to use Python for software development projects.
Web Developer
Web developers design and develop websites. Python is a popular programming language for web developers because it is easy to learn and use, and it has a wide range of libraries and tools for web development. This course provides an introduction to Python, including how to use it to build simple programs and use conditional statements to automate decision-making. This course may be particularly useful for web developers who are looking to learn more about Python or who want to use Python for web development projects.
Risk Analyst
Risk analysts use data to identify and assess risks. Python is a popular programming language for risk analysts because it is easy to learn and use, and it has a wide range of libraries and tools for risk analysis. This course provides an introduction to Python, including how to use it to automate tasks, collect data from websites, and perform data analysis. This course may be particularly useful for risk analysts who are looking to learn more about Python or who want to use Python for risk analysis projects.
Data Engineer
Data engineers design, build, and maintain data pipelines. Python is a popular programming language for data engineers because it is easy to learn and use, and it has a wide range of libraries and tools for data engineering. This course provides an introduction to Python, including how to use it to automate tasks, collect data from websites, and perform data analysis. This course may be particularly useful for data engineers who are looking to learn more about Python or who want to use Python for data engineering projects.
Data Visualization Specialist
Data visualization specialists design and create visual representations of data. Python is a popular programming language for data visualization specialists because it is easy to learn and use, and it has a wide range of libraries and tools for data visualization. This course provides an introduction to Python, including how to use it to automate tasks, collect data from websites, and perform data analysis. This course may be particularly useful for data visualization specialists who are looking to learn more about Python or who want to use Python for data visualization projects.
Quantitative Analyst
Quantitative analysts use data to make investment decisions. Python is a popular programming language for quantitative analysts because it is easy to learn and use, and it has a wide range of libraries and tools for financial analysis. This course provides an introduction to Python, including how to use it to automate tasks, collect data from websites, and perform data analysis. This course may be particularly useful for quantitative analysts who are looking to learn more about Python or who want to use Python for quantitative analysis projects.
Actuary
Actuaries use data to assess and manage risk. Python is a popular programming language for actuaries because it is easy to learn and use, and it has a wide range of libraries and tools for financial analysis. This course provides an introduction to Python, including how to use it to automate tasks, collect data from websites, and perform data analysis. This course may be particularly useful for actuaries who are looking to learn more about Python or who want to use Python for actuarial projects.
Market Researcher
Market researchers collect and analyze data about markets and customers. Python is a popular programming language for market researchers because it is easy to learn and use, and it has a wide range of libraries and tools for data analysis. This course provides an introduction to Python, including how to use it to automate tasks, collect data from websites, and perform data analysis. This course may be particularly useful for market researchers who are looking to learn more about Python or who want to use Python for market research projects.
Machine Learning Engineer
Machine learning engineers design, build, and maintain machine learning models. Python is a popular programming language for machine learning engineers because it is easy to learn and use, and it has a wide range of libraries and tools for machine learning. This course provides an introduction to Python, including how to use it to build simple programs and use conditional statements to automate decision-making. This course may be particularly useful for machine learning engineers who are looking to learn more about Python or who want to use Python for machine learning projects.
Business Analyst
Business analysts use data to solve business problems. Python is a popular programming language for business analysts because it is easy to learn and use, and it has a wide range of libraries and tools for data analysis. This course provides an introduction to Python, including how to use it to automate tasks, collect data from websites, and perform data analysis. This course may be particularly useful for business analysts who are looking to learn more about Python or who want to use Python for business analysis projects.

Reading list

We've selected 16 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Try It: Intro to Python.
Provides a comprehensive introduction to Python, covering the basics of programming, data structures, and algorithms. It good choice for beginners who want to learn Python from scratch.
Practical guide to using Python for automating tasks. It is full of step-by-step instructions and examples that show how to use Python to solve real-world problems.
Comprehensive guide to using Python for data analysis. It covers everything from data cleaning and wrangling to statistical modeling and machine learning.
Comprehensive guide to using Python for machine learning. It covers everything from supervised and unsupervised learning to deep learning.
Deep dive into the Python language. It covers advanced topics such as object-oriented programming, decorators, and metaprogramming.
Comprehensive introduction to Python and computer science. It covers a wide range of topics, from the basics of programming to object-oriented programming and data structures.
Collection of recipes that show how to solve common programming problems in Python. It valuable reference for Python programmers of all levels.
Comprehensive reference for Python. It covers everything from the basics of the language to advanced topics such as object-oriented programming, concurrency, and networking.
Comprehensive reference for the Python standard library. It covers everything from the basics of the library to advanced topics such as concurrency, networking, and database access.
Concise reference for the Python language. It covers the essentials of the language, from the basics to advanced topics such as object-oriented programming and data structures.
Small and portable reference for the Python language. It covers the essentials of the language, from the basics to advanced topics such as object-oriented programming and data structures.
Comprehensive introduction to Python 3. It covers everything from the basics of the language to advanced topics such as object-oriented programming, concurrency, and networking.
Concise introduction to Python. It covers the basics of the language, from the basics to advanced topics such as object-oriented programming and data structures.
Humorous and approachable introduction to Python. It covers the basics of the language, from the basics to advanced topics such as object-oriented programming and data structures.

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