A Comprehensive Hands-on Guide for Learning Python to Gain proficiency, productivity and power with a Project-Based Approach.
Python is among the most popular programming languages in the world. It’s ideal for beginners because it’s easy to read and write. It’s great for developers because it’s widely available with a strong support community, extensive documentation, and phenomenal libraries (both built-in and user-contributed). It’s leading the way in machine learning and data science due to its efficiency and speed. At the time of this writing, over 4,000 open jobs list Python as a skill, more than any other programming language.
By taking this course, you will become empowered in Python. You can leverage your Python skills in technical jobs, personal projects, and job interviews. You will gain an edge in data science, web development, and software development. You will be ready to solve real-world, challenging problems in Python and pursue advanced topics on your own.
Written by a team of expert authors, each component has been explicitly designed to engage and stimulate different parts of the brain so that you can retain and apply what you learn in a practical context with maximum impact. By completing the course from start to finish, you’ll walk away feeling capable of tackling any real-world Python development problem.
This book is for professionals, students and hobbyists who want to learn Python and apply it to solve challenging real-world problems. Although this is a beginner’s course, it’s helpful to know standard programming topics like variables, if-else statements and functions. Experience with another object-oriented program, though not essential, is beneficial. If Python is your first attempt at computer programming, we will cover the basics with adequate detail for a motivated student.
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Corey Wade, M.S. Mathematics, M.F.A. Writing & Consciousness, is the founder and director of Berkeley Coding Academy where he teaches Machine Learning and AI to teens from all over the world. Additionally, Corey chairs the Math Department at Berkeley Independent Study where he has received multiple grants to run after-school coding programs to help bridge the tech skills gap. Additional experiences include teaching Natural Language Processing with Hello World, developing Data Science curricula with Pathstream, and publishing statistics and machine learning models with Towards Data Science, Springboard, and Medium.
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