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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 and Data Analytics Boot Camp with The University of North Carolina at Chapel Hill. If you enroll in this Try It, your learner data will not be shared with The University of North Carolina at Chapel Hill unless you enroll in the Coding Boot Camp or Data Analytics 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 fundamentals of programming and Python, suitable for learners with no prior programming experience
Covers practical applications of Python, including data analysis, web development, and machine learning
Taught by instructors from the University of North Carolina at Chapel Hill, known for its strong academic reputation
Provides a strong foundation for beginners interested in pursuing data analysis or machine learning careers
This Try It serves as an introduction to the Coding Boot Camp and Data Analytics Boot Camp at the University of North Carolina at Chapel Hill

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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 Variables and Data Types
Strengthen your foundation by revisiting the concepts of variables and data types in Python.
Browse courses on Variables
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  • Review course materials or online resources on variables and data types.
  • Practice writing code snippets that demonstrate variable declaration and assignment.
  • Test your understanding by solving simple coding challenges involving variables and data types.
Read Introduction to Python
Build a foundation in Python by reading this book, which covers the basics of the language.
Show steps
  • Acquire the book through the library, purchase, or online resources.
  • Establish a dedicated time for reading and stick to it.
  • Take notes or highlight important concepts while reading.
  • Complete the practice exercises provided in the book.
Explore Python Documentation and Tutorials
Supplement your learning by seeking out additional resources and tutorials that delve deeper into Python concepts.
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Show steps
  • Visit the official Python documentation and explore various modules and functions.
  • Search online for tutorials that cover specific topics related to the course.
  • Follow along with the tutorials, taking notes and practicing the examples.
  • Experiment with different Python code snippets and test their functionality.
Five other activities
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Solve Python Coding Challenges
Enhance your Python skills by practicing coding challenges that test your ability to solve problems.
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Show steps
  • Identify reputable platforms or websites that offer Python coding challenges.
  • Select challenges that align with your skill level and course content.
  • Set aside dedicated time for solving these challenges.
  • Seek help from online forums or mentors if needed.
Attend a Python Workshop
Expand your knowledge and network by attending workshops led by experts in the field of Python.
Browse courses on Python
Show steps
  • Research and identify relevant Python workshops in your area or online.
  • Register for the workshop and prepare any necessary materials.
  • Attend the workshop, actively participate, and take notes.
  • Follow up with the organizers or presenters if you have any questions.
Create a Python Quiz
Solidify your understanding of Python concepts by creating a quiz that tests your knowledge.
Browse courses on Python
Show steps
  • Identify key topics covered in the course.
  • Formulate questions that cover different aspects of these topics.
  • Create a platform or use an existing one to host the quiz.
  • Share your quiz with peers or instructors for feedback.
Develop a Python Script
Apply your Python knowledge by creating a functional script that addresses a real-world problem.
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  • Identify a problem or task that can be solved using Python.
  • Design the script's logic and structure.
  • Write and debug the Python code.
  • Test the script thoroughly and make necessary modifications.
Build a Python Project
Deepen your understanding of Python by embarking on a project that challenges your skills and creativity.
Browse courses on Python
Show steps
  • Identify a project idea that aligns with your interests and course content.
  • Plan the project's scope, timeline, and necessary resources.
  • Develop and implement your Python code.
  • Test and debug your project thoroughly.
  • Document your project and share it with others.

Career center

Learners who complete Try It: Intro to Python will develop knowledge and skills that may be useful to these careers:
Web Developer
Web Developers use Python for web development, data analysis, and machine learning. This course provides a foundation in Python and dives into basic programming concepts like functions and variables.
Software Developer
Software Developers use Python for web development, data analysis, and machine learning. This course provides a foundation in Python and dives into basic programming concepts like functions and variables.
Software Engineer
Software Engineers use Python for web development, data analysis, and machine learning. This course provides a foundation in Python and dives into basic programming concepts like functions and variables.
Computer Scientist
A Computer Scientist can use Python to automate tasks and build a foundation in coding. This course is a great introduction to a career that requires knowledge of Python and similar programming languages.
IT Specialist
IT Specialists use Python to automate tasks and build a foundation in coding. This course provides a solid foundation in Python that is commonly used in this field and may be useful for getting started in an IT Specialist career.
IT Project Manager
IT Project Managers use Python to manage software projects and automate tasks as needed. This course provides a solid foundation in Python that is commonly used in this field and may be useful for getting started in an IT Project Manager career.
Information Security Analyst
Information Security Analysts use Python to automate tasks and build a foundation in coding. This course is an introduction to Python including some conditional statements.
Product Manager
Product Managers must understand the basics of programming. This course provides a solid foundation for building that understanding.
Systems Analyst
Systems Analysts use Python to automate tasks and build a foundation in coding. This course provides a solid foundation in Python that is commonly used in this field and may be useful for getting started in a Systems Analyst career.
Quantitative Analyst
Quantitative Analysts use Python for data analysis and visualization. This course can help you understand how to interact with a console using Python, which is a skill that Quantitative Analysts use.
Financial Analyst
Financial Analysts use Python for data analysis and visualization. This course can help you understand how to interact with a console using Python, which is a skill that Financial Analysts use.
Data Analyst
Data Analysts use Python for data analysis and visualization. This course can help you understand how to interact with a console using Python, which is a skill that Data Analysts use.
Data Engineer
Data Engineers use Python for large-scale data analysis and automation. This course provides a solid foundation in Python that is commonly used in this field and may be useful for getting started in a Data Engineering career.
Machine Learning Engineer
Machine Learning Engineers use Python to build and deploy machine learning models. This course can help build a foundation in Python that is commonly used in this field and may be useful for getting started in a Machine Learning Engineering career.
Webmaster
Webmasters use Python for web development, data analysis, and machine learning. This course provides a foundation in Python and dives into basic programming concepts like functions and variables.

Reading list

We've selected 15 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 and practical introduction to programming with Python, covering essential concepts like variables, functions, conditional statements, and data structures. It also includes hands-on projects to reinforce learning.
Focuses on practical applications of Python for automating everyday tasks, such as web scraping, data analysis, and scripting. It provides step-by-step instructions and real-world examples to help learners build useful programs.
Provides a gentle introduction to Python programming, starting with the basics and gradually building up to more advanced concepts. It includes clear explanations, code examples, and exercises to aid comprehension.
Approaches Python programming from a computer science perspective, emphasizing problem-solving and algorithmic thinking. It covers foundational concepts like data structures, algorithms, and object-oriented programming.
Delves into the nuances and best practices of Python programming, providing insights into advanced topics such as decorators, generators, and metaprogramming. It valuable resource for learners who want to master the subtleties of Python.
Covers the essential tools and techniques for data science in Python, including data manipulation, visualization, machine learning, and deep learning. It provides a practical guide to using Python libraries like NumPy, Pandas, and Scikit-learn for real-world data science projects.
Provides a comprehensive introduction to machine learning with Python, covering topics like supervised learning, unsupervised learning, and deep learning. It includes hands-on examples and case studies to demonstrate the practical applications of machine learning algorithms.
Focuses on using Python for data analysis tasks, including data cleaning, exploration, and visualization. It covers essential data analysis libraries like Pandas and Matplotlib, and provides practical examples and case studies to illustrate their usage.
Introduces Python web development using the Django framework. It covers essential concepts like models, views, and templates, and guides learners through building a complete web application from scratch.
Focuses on writing clean, idiomatic, and maintainable Python code. It provides guidelines and best practices for code style, testing, and debugging, and helps learners develop a deeper understanding of Python's underlying design principles.
Serves as a comprehensive reference for Python, covering the language's syntax, built-in functions, and standard library modules. It provides quick access to essential information for both beginners and experienced programmers.
Provides a collection of practical recipes and solutions for common programming tasks in Python. It covers a wide range of topics, including data manipulation, web development, and system administration, and serves as a valuable resource for learners who want to solve specific coding problems.
Covers the fundamentals of natural language processing (NLP) in Python, including text preprocessing, tokenization, stemming, and machine learning techniques for NLP tasks. It provides a comprehensive overview of NLP concepts and techniques for beginners and experienced programmers alike.
Introduces Python for financial data analysis and modeling. It covers topics like data acquisition, data cleaning, and financial calculations, and provides practical examples and case studies to demonstrate the application of Python in finance.

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