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Intro to Python

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 University of Richmond. If you enroll in this Try It, your learner data will not be shared with University of Richmond unless you enroll in the Coding Boot Camp or Data Analytics Boot Camp.

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
Provides a foundational introduction to Python, useful for both beginners with zero prior programming experience and those looking to strengthen their existing Python skills
Introduces core Python concepts and practices, enabling learners to become familiar with the basics of the language
Covers essential topics such as functions, variables, conditional logic, and Python console interaction, providing a well-rounded understanding of Python's capabilities
Focuses on developing programming skills in Python, making it suitable for learners seeking to apply Python in practical settings and projects
Provides hands-on coding practice through examples and exercises, allowing learners to apply their understanding of Python concepts
Serves as an introductory preparation for individuals interested in pursuing careers as data analysts, financial analysts, data scientists, and more

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Career center

Learners who complete Try It: Intro to Python will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst mines data to uncover insights and trends, and turns it into valuable information for decision making. This course introduces Python programming, a skill commonly used by Data Analysts on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in a Data Analyst.
Data Engineer
A Data Engineer builds, maintains, and manages the infrastructure that stores and processes data, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Data Engineers on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in a Data Engineer.
Statistician
A Statistician collects, analyzes, interprets, and presents data, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Statisticians on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in a Statistician.
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models to automate complex tasks, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Machine Learning Engineers on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in a Machine Learning Engineer.
Operations Research Analyst
An Operations Research Analyst uses advanced analytical techniques to solve complex business problems, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Operations Research Analysts on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in an Operations Research Analyst.
Actuary
An Actuary analyzes the financial consequences of risk and uncertainty, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Actuaries on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in an Actuary.
Risk Analyst
A Risk Analyst identifies, assesses, and manages financial risks, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Risk Analysts on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in a Risk Analyst.
Quantitative Analyst
A Quantitative Analyst applies mathematical and statistical methods to financial data to assess risk and make investment decisions, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Quantitative Analysts on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in a Quantitative Analyst.
Biostatistician
A Biostatistician applies statistical methods to biological and medical data, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Biostatisticians on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in a Biostatistician.
Financial Analyst
A Financial Analyst analyzes financial data to make investment recommendations, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Financial Analysts on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in a Financial Analyst.
Insurance Analyst
An Insurance Analyst evaluates insurance risks and develops insurance products, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Insurance Analysts on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in an Insurance Analyst.
Fraud Analyst
A Fraud Analyst identifies and investigates fraudulent activities, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Fraud Analysts on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in a Fraud Analyst.
Market Researcher
A Market Researcher conducts research on target markets and consumer behavior to help businesses make informed decisions, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Market Researchers on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in a Marketing Researcher.
Marketing Analyst
A Marketing Analyst analyzes marketing data to improve marketing campaigns, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Marketing Analysts on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in a Marketing Analyst.
Business Analyst
A Business Analyst analyzes business processes and systems to improve efficiency and effectiveness, and often works with Data Analysts. This course introduces Python programming, a skill commonly used by Business Analysts on the job. By taking this course, you may build a foundation in Python and begin preparing for what employers seek in a Business Analyst.

Reading list

We've selected 13 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.
This practical, hands-on guide offers lots of exercises, projects, and examples to help you actively learn Python. It teaches important fundamentals of data science, machine learning, automation, and more.
Delves deeply into Python's core language features and idioms. It provides insights into how to write effective, maintainable, and idiomatic Python code.
This comprehensive guide to Python 3 covers a wide range of topics, including object-oriented programming, data structures, and web development. It good reference for Python programmers of all levels.
Focuses on data analysis with Python. It's helpful as a reference guide for working with data in Python, and it covers data loading, cleaning, manipulation, and visualization.
Offers a curated, in-depth introduction to Python. It provides a solid grounding for those who want a deeper understanding of Python and how it works.
Serves as a comprehensive reference guide to Python. It provides a concise overview of all major topics and serves as a useful tool for experienced Python programmers.
Provides an accessible introduction to Python and its applications in data science. It covers concepts like data structures, algorithms, and data visualization, making it a good resource for those interested in data analysis.
For those interested in machine learning with Python, this book covers supervised and unsupervised learning, natural language processing, and deep learning. It provides hands-on practice with real-world datasets and popular machine learning libraries.
This open-source book is designed for beginners and covers a wide range of Python topics, from basic syntax to data structures and object-oriented programming.
Perfect for those interested in automation. It guides you in automating essential tasks, such as sending emails, scraping data, making web requests, and more.

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