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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 Coding Boot Camp with the University of New Hampshire. If you enroll in this Try It, your learner data will not be shared with the University of New Hampshire unless you enroll in the 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
Examines foundational concepts such as functions, variables, decision-making, and console interactions, making it suitable for complete beginners
Provides an introduction to boot camps that combine data analysis and machine learning, offering a pathway to careers in data science and analytics
Explores Python's versatility and applicability in a wide range of industries, including energy, finance, healthcare, and IT
Covers topics such as web development, scientific computing, data visualization, and machine learning, demonstrating Python's broad capabilities
Provides hands-on coding exercises to reinforce understanding and enable learners to apply Python concepts to practical projects

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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:
Review Python for Beginners
Introduce key concepts of Python and its basic syntax and structure, providing a solid foundation for the course.
Show steps
  • Read the first four chapters of the book.
  • Complete the corresponding exercises and quizzes in the book.
  • Write a short Python program that prints 'Hello World'.
Python Study Group
Foster a collaborative learning environment by encouraging students to form study groups and work together.
Show steps
  • Find a group of students to form a study group with.
  • Meet regularly to discuss course material.
  • Work together on assignments and projects.
Python Tutoring
Facilitate peer-to-peer learning by having students tutor others in Python, strengthening their understanding of the subject.
Show steps
  • Identify a student who needs support with Python.
  • Schedule a tutoring session.
  • Prepare for the session by reviewing Python concepts.
  • Provide guidance and support to the student during the session.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Python Coding Challenges
Provide hands-on practice with Python coding problems, reinforcing the concepts learned in the course.
Show steps
  • Register for an online coding challenge platform.
  • Solve at least 10 Python coding challenges.
  • Review your solutions against provided solutions or discuss with peers.
Python Workshop: Data Analysis with Pandas
Provide an opportunity for students to develop practical skills in data analysis using Python's Pandas library.
Show steps
  • Register for a Python workshop focused on data analysis with Pandas.
  • Attend the workshop and actively participate in the activities.
  • Apply the learned concepts to a real-world dataset.
Python Tutorial Blog
Encourage students to articulate their understanding by creating a blog that explains Python concepts and shares coding examples.
Show steps
  • Create a new blog or website.
  • Choose a Python topic to write about.
  • Research and gather information about the topic.
  • Write a clear and concise blog post.
  • Include code snippets or examples to illustrate the concepts.
Contribute to Open Source Python Projects
Expose students to the practical applications of Python by having them contribute to open-source projects.
Show steps
  • Identify an open-source Python project to contribute to.
  • Fork the project repository and create a branch.
  • Implement a new feature or fix a bug.
  • Submit a pull request with your changes.

Career center

Learners who complete Try It: Intro to Python will develop knowledge and skills that may be useful to these careers:
Software Engineer
A Software Engineer uses their knowledge of Python, learned in Intro to Python, to build and maintain computer applications. Intro to Python will help teach you how to write scripts for automating tasks, build web applications, and collect data from websites.
Machine Learning Engineer
Machine Learning Engineers use Python to build and train machine learning models. Intro to Python will provide you with the foundation you need to succeed in this role. You will learn how to use Python for data analysis, data visualization, and machine learning.
Data Analyst
Data Analysts are experts in analyzing data to identify trends and patterns. This course will provide you with the foundation in Python you need to succeed in this role. You will learn how to write scripts for automating tasks, collect data from websites, and perform data analysis.
Data Scientist
Data Scientists use Python to analyze data and solve complex problems. Intro to Python will provide you with the foundation you need to succeed in this role. You will learn how to use Python for data analysis, data visualization, and machine learning.
Web Developer
Web Developers use Python to build and maintain websites. Intro to Python will provide you with the foundation you need to succeed in this role. You will learn how to use Python for web development, data analysis, and data visualization.
Financial Analyst
Financial Analysts use Python to analyze financial data and make investment recommendations. Intro to Python will provide you with the foundation you need to succeed in this role. You will learn how to use Python for data analysis, data visualization, and financial modeling.
Business Analyst
Business Analysts use Python to analyze business data and identify trends. Intro to Python will provide you with the foundation you need to succeed in this role. You will learn how to use Python for data analysis, data visualization, and business intelligence.
Operations Research Analyst
Operations Research Analysts use Python to solve complex problems in a variety of industries. Intro to Python will provide you with the foundation you need to succeed in this role. You will learn how to use Python for data analysis, data visualization, and optimization.
Risk Analyst
Risk Analysts use Python to identify and assess risks. Intro to Python will provide you with the foundation you need to succeed in this role. You will learn how to use Python for data analysis, data visualization, and risk modeling.
Quantitative Analyst
Quantitative Analysts use Python to develop and test financial models. Intro to Python will provide you with the foundation you need to succeed in this role. You will learn how to use Python for data analysis, data visualization, and financial modeling.
Epidemiologist
Epidemiologists use Python to track and analyze the spread of diseases. Intro to Python will provide you with the foundation you need to succeed in this role. You will learn how to use Python for data analysis, data visualization, and epidemiological modeling.
Statistician
Statisticians use Python to analyze data and draw conclusions. Intro to Python will provide you with the foundation you need to succeed in this role. You will learn how to use Python for data analysis, data visualization, and statistical modeling.
Actuary
Actuaries use Python to analyze financial and insurance data. Intro to Python will provide you with the foundation you need to succeed in this role. You will learn how to use Python for data analysis, data visualization, and financial modeling.
Biostatistician
Biostatisticians use Python to analyze biological and medical data. Intro to Python will provide you with the foundation you need to succeed in this role. You will learn how to use Python for data analysis, data visualization, and biostatistical modeling.
Marketing Analyst
Marketing Analysts use Python to analyze marketing data and identify trends. Intro to Python will provide you with the foundation you need to succeed in this role. You will learn how to use Python for data analysis, data visualization, and marketing analytics.

Reading list

We've selected 11 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.
Beginners can quickly get started with Python and use it to automate daily tasks on their computers. Also introduces foundational Python concepts like loops, conditionals, and functions.
An intermediate-level book that focuses on Python's capabilities for data manipulation and analysis. Covers topics like data cleaning, wrangling, and working with libraries such as NumPy and Pandas.
For those with some prior Python experience, this book provides practical advice on improving code quality, performance, and maintainability.
Addresses more advanced Python concepts like iterators, decorators, and metaprogramming while providing a deeper understanding of the language's design principles and idioms.
An extensive collection of Python recipes for solving common programming problems, providing numerous solutions for tasks like data manipulation, web development, and system administration.
A comprehensive guide to Python programming, covering all aspects of the language from basic syntax to object-oriented programming and advanced concepts. Serves as a useful reference for developers at various levels.
A thorough and detailed guide to Python programming, covering both the basics and advanced topics. Written in a clear and engaging style, it provides a solid foundation for developers of all levels.
Provides insights into best practices for writing automated tests in Python. Covers topics like unit testing, integration testing, and mocking, and is particularly useful for developers interested in ensuring the quality of their code.

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