Learn Python Basics with This In-Depth Video Course

Python has seen explosive growth in popularity over the past decade, and for good reason. This versatile, beginner-friendly language is used across many domains, from web development to data science to DevOps and more. According to the 2021 Stack Overflow Developer Survey, Python ranks as the third most popular programming language among professional developers, behind only JavaScript and HTML/CSS.

Rank	Programming Language	% of Respondents Using Professionally
1	JavaScript	64.96%
2	HTML/CSS	56.07%
3	Python	41.84%
4	SQL	41.72%
5	Java	35.32%

Source: Stack Overflow Developer Survey 2021

If you‘ve been wanting to learn Python but aren‘t sure where to begin, you‘re in luck. Experienced developer and educator Mike Dane created an excellent in-depth video course that will teach you the basics of Python from the ground up. In just 4.5 hours, you‘ll go from installing Python to building real projects as you follow along with Mike‘s clear explanations and examples.

Why Learn Python?

Python‘s popularity stems from its versatility, simple and readable syntax, and extensive ecosystem of libraries and frameworks. It‘s used for everything from automating system administration tasks to powering the backend of web applications to training machine learning models. Python‘s gentle learning curve makes it an ideal first language, while its depth and robustness make it a favorite of seasoned developers as well.

Python embraces a design philosophy that emphasizes code readability, notably using indentation to delimit code blocks rather than curly brackets or keywords. This makes Python code highly readable and maintainable compared to many other languages. The Python community has also developed a strong culture around best practices for writing "pythonic" code, captured in the Zen of Python principles (try typing import this in a Python shell).

While Python is an interpreted language and can be slower than compiled languages like C++, its performance is more than adequate for most applications. And for computationally-intensive tasks, Python can interface with lower-level languages like C or Rust, or delegate work to highly optimized libraries like NumPy.

Installing Python and PyCharm

Before diving into writing Python code, you‘ll need to set up your development environment. The first step is installing Python itself. Mike walks through downloading and installing Python on Windows, Mac, and Linux.

Next up is PyCharm, the most popular integrated development environment (IDE) for Python. While you can write Python code in a basic text editor, PyCharm provides powerful features like auto-completion, debugging, refactoring, and more that make writing Python a breeze. Mike explains how to install the free Community Edition of PyCharm and configure it for Python development.

PyCharm‘s feature set goes far beyond just editing Python code. Some of the most useful features for Python development include:

• Smart code completion, auto-importing, and code snippets
• Refactoring and quick fixes to optimize and clean up code
• Visual debugging with breakpoints, step-through, and variable inspection
• Integrated unit testing and code coverage
• Virtual environment management for isolated Python setups per-project
• Code analysis to surface syntax errors, potential bugs, style issues and more
• Scientific mode with Jupyter notebook integration for data science work
• Built-in terminal, database tools, REST client, and more

Getting Started with Python in PyCharm

With Python and PyCharm installed, you‘re ready to start coding. Mike demonstrates how to create a new Python project in PyCharm and walks through writing your first "Hello World" program. You‘ll learn how to use the Python interactive shell directly in PyCharm to execute commands and see results immediately.

PyCharm makes running Python files simple. Mike explains how to create and execute Python files within a project. You‘ll be able to write code in the editor and run it with just a keystroke to view the output.

Python Language Basics

Mike‘s course provides a thorough introduction to core Python concepts and language features. You‘ll learn about:

• Variables and data types: how to store and work with text, numbers, booleans and more
• Strings: creating, concatenating and manipulating text
• Numbers: performing math operations and conversions
• Lists and tuples: storing ordered collections of items
• Dictionaries: storing key-value pairs
• Operators and expressions: writing expressions with arithmetic, comparison, logical and other operators
• Control flow: using if/else conditional logic, for loops to iterate, and while loops to repeat
• Functions: writing reusable pieces of code to perform tasks

Each concept is broken down with clear explanations and examples. Mike paces the material to make it easy to follow along, building concepts iteratively throughout the course. Hands-on exercises and projects let you put your new Python skills to work.

Hands-on Python Projects in PyCharm

The best way to learn is by doing. Throughout the course, Mike guides you in building non-trivial Python projects that leverage what you‘ve learned:

• Basic calculator: create a program that takes user input and performs arithmetic operations
• Mad Libs word game: generate dynamic stories based on user word choices
• Translator app: convert words or phrases from one language to another

For each project, Mike breaks down the requirements, plans out the solution, and codes it live while explaining his thought process. You‘ll be able to follow along in PyCharm and see how the concepts you‘ve learned can be combined to build functioning programs.

Intermediate Python Concepts

Beyond the basics, Mike introduces some intermediate-level Python programming concepts:

• File I/O: reading data from and writing data to external files
• Exception handling: gracefully handling errors with try/except blocks
• Modules and packages: leveraging pre-built functionality by importing modules, and using pip to install packages
• Object-oriented programming: an introduction to classes, objects, methods and inheritance – a paradigm used heavily in modern Python development

Object-oriented programming (OOP) is a key paradigm to understand when working on larger Python projects. It allows you to define your own types (classes) that bundle data and functionality together, providing encapsulation and enabling code reuse through inheritance. Python has strong support for OOP including class-based inheritance, duck typing, and magic methods. Mastering OOP concepts will enable you to write more modular, maintainable Python code and work with many popular libraries and frameworks that leverage OOP heavily.

Walking through examples of each concept, Mike demonstrates how these features work and discusses some common use cases. With an understanding of these concepts, you‘ll be able to write more robust, organized and maintainable Python code.

The Python Ecosystem

One of Python‘s greatest strengths is its rich ecosystem of open source packages. The Python Package Index (PyPI) hosts over 350,000 packages spanning web frameworks, data analysis tools, utility libraries and more. Some of the most popular Python packages include:

• Django and Flask for web development
• NumPy, pandas, and Matplotlib for data manipulation and visualization
• requests for HTTP communication
• Beautiful Soup for web scraping
• scikit-learn for machine learning
• pytest for testing Python code

Whatever your domain of interest, there‘s likely a Python package that can help you be more productive. The pip package manager makes it easy to install and manage Python packages in your projects. Virtual environments allow you to isolate package dependencies per-project, avoiding conflicts between different projects‘ requirements. PyCharm has excellent support for working with virtual environments and managing packages.

When starting a new Python project, it‘s often helpful to look for existing packages that can solve pieces of your problem rather than reinventing the wheel. Leveraging well-tested, widely-used open source packages can save significant development time and lead to more robust, maintainable solutions. Of course, it‘s important to evaluate packages for their quality, security, maintenance status and licensing before committing to using them.

Python 2 vs Python 3

One important note for new Python learners is the distinction between Python 2 and Python 3. Python 3 was introduced in 2008 as a major update to the language that included backwards-incompatible changes. Python 2 reached end-of-life status in 2020, meaning it no longer receives bug fixes or security updates.

While some legacy codebases still use Python 2, all new Python development should use Python 3, which has been the recommended version for many years now. Python 3 includes many language and library improvements, and most popular packages now only support Python 3. Mike‘s course uses Python 3 throughout.

Career Prospects for Python Developers

As a Python developer, you‘ll be in high demand across many industries. According to data from Indeed, the average Python developer salary in the United States is $119,082 per year, with salaries ranging up to over $200,000 depending on location and experience level.

Python developers are needed in a wide variety of roles, including:

• Backend web developers
• Data analysts and data scientists
• Machine learning engineers
• DevOps and automation specialists
• Quality assurance engineers
• Security analysts
• Network programmers

Python‘s versatility and broad adoption make it a valuable skill in today‘s job market. Demand for Python developers continues to grow along with Python‘s usage across many domains.

Where to Go From Here

By the end of this in-depth video course, you‘ll have a solid understanding of Python basics and be able to build your own programs and scripts. But the learning doesn‘t stop there. Mike provides links to additional resources to deepen your Python knowledge, including documentation, tutorials, courses, and books.

To cement your understanding and expand your skills, Mike suggests tackling some Python project ideas like web scrapers, database-driven apps, and data analysis scripts. Building projects is the best way to learn, so choose something that interests you and get coding! You can share your projects on GitHub to show off your work and collaborate with other developers.

As you continue your Python journey, some great resources to leverage include:

• The official Python documentation and tutorial
• Real Python‘s in-depth articles and tutorials
• Codecademy‘s interactive Python courses
• The Python Crash Course book
• Corey Schafer‘s YouTube channel with Python tutorials and walkthroughs

Joining a local Python user group or online community like the Python subreddit or Slack groups can also accelerate your learning by connecting you with other Pythonistas to share knowledge and projects with.

Python‘s popularity and beginner-friendliness have also made it a common choice for coding bootcamps and computer science programs. If you‘re considering a career transition or want to go deeper with software engineering, enrolling in a structured program can provide a focused, immersive learning experience.

Conclusion

Learning Python opens up a world of possibilities, from automating repetitive tasks to building sophisticated applications. While it may seem daunting at first, Python‘s gentle learning curve and supportive community make it an ideal language for beginners. With dedication and practice, you‘ll soon be able to harness the power of Python to bring your ideas to life.

So what are you waiting for? Dive into Mike Dane‘s excellent Python basics video course, follow along in PyCharm, and start your Python programming journey today! Before long, you‘ll be creating your own Python projects with confidence. Happy coding!