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Introduction to Python Programming

Kyle Stewart-Franz, Abe Feinberg, and Brynn Claypoole

Review fundamental Python programming syntax and concepts.

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What's inside

Syllabus

Welcome to Introduction to Python! Here's an overview of the course.

Familiarize yourself with the building blocks of Python! Learn about data types and operators, built-in functions, type conversion, whitespace, and style guidelines.

Use data structures to order and group different data types together! Learn about the types of data structures in Python, along with more useful built-in functions and operators.

Build logic into your code with control flow tools! Learn about conditional statements, repeating code with loops and useful built-in functions, and list comprehensions.

Learn how to use functions to improve and reuse your code! Learn about functions, variable scope, documentation, lambda expressions, iterators, and generators.

Set up your own programming environment to write and run Python scripts locally! Learn good scripting practices, interact with different inputs, and discover awesome tools.

Learn the basics of NumPy and how to use it to create and manipulate arrays.

Learn the basics of Pandas Series and DataFrames and how to use them to load and process data.

In this lesson we cover some advanced topics of iterators and generators. You are not required to complete this but we have provided these to give you a taste of these.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides a comprehensive overview of fundamental Python programming concepts

Taught by experienced instructors who are recognized for their work in Python

Covers essential data structures, logic tools, and control flow

Develops proficiency in using functions to improve and reuse code

Provides hands-on guidance on setting up a programming environment

Introduces the basics of NumPy for array manipulation and Pandas for data processing

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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 Introduction to Python Programming with these activities:

Organize your notes and course materials

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Organize your notes and materials from the course to create a condensed and accessible knowledge base.

Browse courses on Python

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Review your notes and highlight important concepts and examples.
Create a document or digital notebook to compile your organized notes.

Review Python syntax and basic concepts

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Review the fundamentals of Python syntax and concepts to strengthen your programming skills.

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Go through your Python notes or resources to refresh your memory on syntax.
Practice writing simple Python code snippets to recall basic concepts.

Review key concepts of Python data structures

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Revisit the key concepts of Python data structures to ensure a solid foundation for working with data.

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Review your Python notes or search online for summaries of data structures.
Try implementing simple data structures like lists, tuples, and dictionaries in Python.

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Review Head First Python

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Review a book on Python to refresh your programming skills and prepare for writing your own Python scripts.

View Head First Python: A Learner's Guide to the... on Amazon

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Read the book once to get a feel for Python's features and syntax.
Review the chapters a second time to build a stronger understanding of the material.
Take notes on the Python syntax and features that you find most interesting or confusing.

Follow online tutorials on Python syntax and data structures

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Explore online tutorials to strengthen your Python knowledge through demonstrations and interactive exercises.

Browse courses on Python

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Identify online tutorials that cover Python syntax and data structures.
Work through the tutorials, taking notes and experimenting with the code.
Complete the exercises provided in the tutorials to test your understanding.

Practice Python coding challenges on LeetCode

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Regularly work on coding challenges on LeetCode to enhance your problem-solving abilities and refine your Python skills.

Browse courses on Python

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Register an account on LeetCode and explore the available coding challenges.
Select challenges that align with the Python topics covered in the course.
Set aside dedicated time each week to work on solving LeetCode challenges.

Build a simple Python script to automate a task

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Develop a practical Python script to automate a task, applying your programming skills to solve a real-world problem.

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Identify a task that you can automate using Python, such as sending emails or scraping data.
Design and implement a Python script to automate the task.
Test and refine your script to ensure its functionality and accuracy.

Mentor a junior Python developer

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Share your Python knowledge by mentoring a junior developer, reinforcing your understanding through teaching and guidance.

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Identify a junior Python developer who you can mentor.
Schedule regular mentoring sessions to provide guidance and support.
Review and provide feedback on the junior developer's code and projects.

Career center

Learners who complete Introduction to Python Programming will develop knowledge and skills that may be useful to these careers:

Software Engineer

The first step to becoming a Software Engineer is learning a programming language. This course introduces you to the Python programming language, building a strong foundation for your future in tech and preparing you for popular interviews and technical assessments. This course teaches you skills like conditionals, loops, functions, data structures, debugging, and writing your own Python scripts. These are foundational skills needed to pass coding assessments and progress as a Software Engineer.

See salaries and explore the career path for Software Engineer

Data Analyst

A Data Analyst can use Python for data cleaning, data manipulation, and data visualization. This course introduces you to many of these skills, including using data structures, building functions, and understanding control flow. The course also teaches you about NumPy and Pandas, popular Python libraries for working with data.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Machine Learning Engineers use Python for tasks like data preprocessing, feature engineering, model training, and model evaluation. This course may be helpful for this career path as it introduces you to data structures, functions, and control flow.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use Python for tasks similar to Data Analysts. They may also use Python for more advanced analysis and modeling. This course may be helpful for this career path as it introduces you to data structures, functions, and control flow.

See salaries and explore the career path for Data Scientist

Web Developer

Python is not typically used for front-end development. However, Python is a popular backend language. This course can help you build a foundation in Python, which can be helpful for a career in web development.

See salaries and explore the career path for Web Developer

DevOps Engineer

DevOps Engineers use Python for tasks like automating infrastructure, deploying applications, and monitoring systems. This course can help you build a foundation in Python, which can be helpful for a career in DevOps engineering.

See salaries and explore the career path for DevOps Engineer

Statistician

Statisticians use Python for tasks like data analysis, model development, and inference. This course may be helpful for this career path as it introduces you to data structures, functions, and control flow. The course also teaches you about NumPy and Pandas, popular Python libraries for working with data.

See salaries and explore the career path for Statistician

Business Analyst

Business Analysts use Python for tasks like data analysis, process improvement, and project management. This course may be helpful for this career path as it introduces you to data structures, functions, and control flow. The course also teaches you about NumPy and Pandas, popular Python libraries for working with data.

See salaries and explore the career path for Business Analyst

Financial Analyst

Financial Analysts use Python for tasks like data analysis, model development, and risk management. This course may be helpful for this career path as it introduces you to data structures, functions, and control flow. The course also teaches you about NumPy and Pandas, popular Python libraries for working with data.

See salaries and explore the career path for Financial Analyst

Quantitative Analyst

Quantitative Analysts use Python for tasks like data analysis, model development, and risk management. This course may be helpful for this career path as it introduces you to data structures, functions, and control flow. The course also teaches you about NumPy and Pandas, popular Python libraries for working with data.

See salaries and explore the career path for Quantitative Analyst

Actuary

Actuaries use Python for tasks like data analysis, model development, and risk management. This course may be helpful for this career path as it introduces you to data structures, functions, and control flow. The course also teaches you about NumPy and Pandas, popular Python libraries for working with data.

See salaries and explore the career path for Actuary

Operations Research Analyst

Operations Research Analysts use Python for tasks like data analysis, model development, and optimization. This course may be helpful for this career path as it introduces you to data structures, functions, and control flow. The course also teaches you about NumPy and Pandas, popular Python libraries for working with data.

See salaries and explore the career path for Operations Research Analyst

Data Engineer

Data Engineers use Python for tasks like data integration, data transformation, and data warehousing. This course may be helpful for this career path as it introduces you to data structures, functions, and control flow. The course also teaches you about NumPy and Pandas, popular Python libraries for working with data.

See salaries and explore the career path for Data Engineer

Cloud Engineer

Cloud Engineers use Python for tasks like infrastructure automation, deployment, and management. This course can help you build a foundation in Python, which can be helpful for a career in cloud engineering.

See salaries and explore the career path for Cloud Engineer

Software Tester

Software Testers use Python for tasks like test automation, performance testing, and security testing. This course can help you build a foundation in Python, which can be helpful for a career in software testing.

See salaries and explore the career path for Software Tester

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 Introduction to Python Programming.

A Byte of Python

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Provides a comprehensive introduction to Python programming, covering the basics of the language as well as more advanced topics such as object-oriented programming and data structures. It good starting point for those who are new to Python or want to brush up on their skills.

Introduction to Python Programming

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What's inside

Syllabus

Good to know

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Activities

Career center

Reading list

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