Programming in Python Course by Meta

Please note that this track does not offer a certificate for learners who earn a passing grade. A Verified Certificate costs $299 and provides unlimited access to full course materials, activities, tests, and forums. At the end of the course, learners who earn a passing grade can receive a certificate. This course is offered by the Raspberry Pi Foundation on FutureLearn. By the end of the course, you’ll create your own text-based adventure game. You’ll code using Datacamp’s in-browser programming environment, making it easy to get started with minimal setup.

Each week has two auto-graded quizzes and a weekly project that is peer-graded. Why is it so easy for a computer to not do what you tell it to do? These are the questions that you’ll be able to answer by the end of the first part of the course.

Python Courses

If you’re in that position, this course is an excellent pick for you. The course runs for 6 weeks, with each week being 4 to 5 hours long. You’ll learn through video lectures and supplementary notes, and practice what you’ve learnt in weekly exercises. Next, you’ll move on to more advanced topics like loops and iterations, and how to avoid creating infinite loops. A brief section on recursion —  a fundamental (but tricky!) programming concept — is also included. You’ll start by learning about programming in general and why learning to automate things with your computer can be a time-saving skill.

• Scrape data from the popular HackerNews website and display only the most important articles for you to read for a specific day.
• A word of caution, though – this beginner course isn’t meant to be easy.
• These classes should contain the shape attributes as well as methods for calculating the area or getting a string representation of the shape.
• Moving on, you’ll learn about lists and how to use them to store data.

R is a statistical programming language and is commonly used for manipulating data, statistical analysis, and data visualization. It tends to be better for creating graphics, building statistical models, and utilizing its robust ecosystem of statistical packages. Join Harvard Professor David J. Malan in this online course that will introduce you to programming using Python, a popular language for data science and more.

Is there a Python 1 and 2?

If you’re debating on whether or not you should learn Python, the answer is probably yes. As any developer will attest, it’s a great addition to almost any tech stack — and it consistently ranks highly among the most popularly used programming languages. With SciPy, you’ll learn and apply the basics of linear and logistic regression, and learn how to use random forests to analyze a movie dataset. Coincidentally, according to the World Economic Forum’s Future of Jobs Report, the demand for machine learning and data science specialists will be growing faster than for any other field through 2025. Python is also the language of choice for machine learning and data analysis, with 70% of practitioners preferring Python over other similar languages.

By the end, you will have a stack of impressive projects that you have built that you can show off. This Python coding bootcamp from Andrei Neagoie has become one of the most popular and highly rated Python coding bootcamps online. Learn Python from scratch, get hired, and have fun along the way with the most modern, up-to-date (fully updated for 2024) Python coding bootcamp on the web! We guarantee you that this is the best Python coding bootcamp that you can find if you want to go from an absolute beginner to the exact steps of how to become a Python Developer in 2024. Rest everything was pretty simple and its good for beginners.

Python for Data Science, AI & Development

By the end of the project you’ll understand how to create classes and attributes that serve as budget categories, and then print a graph in the command line representing the percentage spent per category. Lastly, you’ll study variables, the different types of variables, and the role they play in programs. After setting up your programming environment, you’ll be introduced to the basic principles of programming, like the difference between compiling and executing code and the write-run-debug cycle. You’ll know how to analyze the results of running your code and use those results to revise it. Although only basic arithmetic is necessary, Computing in Python is a robust course meant for learners who want to gain a comprehensive understanding of programming and beyond.

Scientific computing is most commonly needed in specialized and technical industries, like engineering or data science. In each project, you will be given some starter code and will be tasked with completing it. The course consists of 5 weeks of material, and you are expected to spend 9–10 hours a week learning.

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I recommend it for anyone who needs to learn python programming. Students who earn a satisfactory score on 9 problem sets (i.e., programming assignments) and a final project are eligible for a certificate. This is a self-paced course–you may take CS50x on your own schedule. You’ll also extend other people’s classes through concepts known as inheritance and polymorphism. For instance, you’ll add new attributes and methods to a “Character class” to make an “Enemy class” that your player can fight. This course is 9 weeks long and you are expected to spend around 14 to 16 hours on lesson materials per week.

So you’ll really get to practice OOP, and in particular, inheritance. Next, you’ll be introduced to the paradigm of procedural programming in Python. The course makes you realize that a program is just sequences of lines of code that is executed to fulfill a purpose, and that programs can be chained to achieve more complex python developer training functionality. The course is broken down into 7 weeks, with each week containing about 4 hours of video lectures and programming tasks. The lectures themselves are based on the book that can be found on the accompanying course website, and they’ve been translated into 9 languages, if English isn’t your strong suit.

This module delves into the unique ways to collect data by the use of APIs and web scraping. It further explores data collection by explaining how to read and collect data when dealing with different file formats. Practice and reflect on the skills you learned in this course. Python’s popularity stems largely from its power and versatility. Below, we’ll explore the reasons behind Python’s popularity and its various applications to help you decide whether or not the language is right for you. However, while the specialization on Coursera is paid, on freeCodeCamp you can earn a free certificate of completion.

Supercharge your coding environment with popular modules libraries and tools for Python. You’ll also learn about the different types of testing and how to write a test. You’ll also learn how to handle errors with the “try-except” blocks before cementing your understanding by building a guess-the-number game.

The course comes with an online book that serves as a basis. Also, each week is dedicated to a specific area of computer science and programming. You are encouraged to skip areas you already know to make the best use of your time. You’ll have a clear roadmap to developing the skills to build your own projects, get hired, and advance your career. This module teaches the basics of Python and begins by exploring some of the different data types such as integers, real numbers, and strings. Continue with the module and learn how to use expressions in mathematical operations, store values in variables, and the many different ways to manipulate strings.