Is Codecademy Free? Pricing and FAQs

In this article, we will talk about Codecademy’s pricing and frequently asked questions.

Codecademy is one of the better-known online learning platforms for learning how to code, mainly because they offer free courses.

It has numerous resources, like important definitions and code syntax, and a vast community stretching from its online forums to Discord, where everyone’s goal is to help each other and learn how to code.

Their website offers activities, coding challenges, and even practice projects, which are all extremely useful, even if you are learning to code elsewhere.

CodeAcademy courses have grown over the years. Before it mostly focused on learning programming languages, like CCS & HTML, javascript, Python etc., Nowadays, they even offer “career paths” that consists of at least 39 -131 lessons to help beginners learn a new profession, like Data Science, Software development, Back-end Engineering and more.

Check out the full list of career paths available here

So, how does one learn with Codecademy?

These online courses are comprised of interactive tutorials and quizzes, you’ll always have to apply what you are learning in real-world projects, which will give you the best hands-on approach to your learning experience.

It is also very easy to browse and find what course might be the most functional to you depending on your topics of interest, like game development or web design, and you will be recommended the appropriate courses that are tailored to these topics. Both free and paid.

You can also explore courses by skill levels, although they only have beginner and intermediate courses. Or, you can browse by skill paths, which are tailored experiences to learn a new specific skill.

How much does Codecademy cost?

Codeacademy divides its pricing into 3 main categories, for individuals, students, and teams.

For Individuals:

• Basic Membership: Free
• Plus Subscription: $17.49/mo billed annually (totaling $209.88) or $34.99 billed monthly
• Pro Subscription: $29.99/mo billed annually (totaling $359.88) or $59.99 billed monthly

On the basic membership, which only requires you to create an account with them, you will have access to free courses, and learning resources, but you’ll have limited use of the practice exercises on their mobile app.

The key difference between the Plus and the Pro plans is that the pro subscription grants you access to career paths, as well as other benefits like access to Code Challenges, Career services, and a Professional certificate.

For Students:

Students in an institution that will earn them a degree (like a university or community college) will have the opportunity to get the Pro plan for 50% less than regular individuals so around $179.94 and can only be billed annually. Please note that you’ll have to undergo a verification process in other to be approved for this plan.

For Teams:

The team pricing page indicates that teams will cost $299 per user yearly, and for enterprises, you must reach out directly for a quote. Please note that no distinction in the number of users required for each is made on their website, and would be wise to reach out to them directly before considering any purchases.

FAQS

---

Codecademy Courses Overview

Career Paths

Currently, they have 13 career paths available and they are as follows (in no specific order):

1. Data Scientist: Machine Learning Specialist

What does a Machine learning specialist do?

A Machine Learning Specialist is responsible for analyzing and interpreting complex data sets to extract meaningful insights and patterns. They develop and implement machine learning models and algorithms to solve real-world problems. They work closely with cross-functional teams to identify business challenges and develop data-driven solutions. Additionally, they are skilled in programming languages and statistical tools to manipulate and analyze data efficiently.

2. Data Scientist: Analytics Specialist

What does an Analytics Specialists do?

Data Scientist: Analytics Specialist focuses on analyzing and interpreting data to derive insights and make data-driven decisions. They may use statistical methods, data visualization, and data exploration techniques to extract valuable information from the data.

3. Computer Science Path

What do Computer Scientists do?

They work on designing and creating computer programs, software, and applications to solve problems and perform specific tasks. Computer scientists also research new computing technologies, algorithms, and ways to improve computer systems and processes. They play a crucial role in shaping the digital world we live in, contributing to advancements in various fields like artificial intelligence, cybersecurity, data analysis, and more.

4. iOS Developer

What do Computer Scientists do?

An iOS developer is a software engineer who specializes in creating applications for Apple’s iOS operating system, which powers devices like iPhones and iPads. They use programming languages like Swift and Objective-C to write the code that brings these applications to life. Their role involves designing and developing user-friendly and intuitive interfaces, implementing functionality and features, and troubleshooting issues to ensure smooth performance.

5. Data Scientist: Inference Specialist

A Data Scientist: Inference Specialist is responsible for drawing meaningful insights and conclusions from data. They analyze large datasets using statistical techniques and machine learning algorithms to identify patterns, trends, and correlations. Their role involves applying statistical inference methods to make predictions and draw conclusions about populations based on sample data. They communicate their findings to stakeholders and help guide decision-making processes based on data-driven insights. Inference Specialists play a crucial role in leveraging data to make informed business decisions and drive strategic initiatives.

6. Code Foundations Path

I personally would not classify this path as a “career path”, but it is offered as one, and the gist of the course is that it would introduce you to the basic concepts of coding in Data Science Computer Science or Web development so you can make a more informed decision when you are choosing your preferred career.

7. Full Stack Engineer Path

What do Fullstack Engineers do?

A Fullstack Engineer is a versatile professional who is skilled in both front-end and back-end development. They have expertise in building and maintaining web applications from start to finish. On the front-end, they work on the user interface and user experience, designing and implementing the visual components of a website. On the back-end, they handle the server-side logic, database management, and integration of various systems. Their role is to ensure seamless communication between the front-end and back-end components, resulting in a fully functional and responsive web application. Fullstack Engineers are proficient in programming languages such as HTML, CSS, JavaScript, and have knowledge of server-side technologies like Node.js and databases like MySQL or MongoDB.

8. Front-End Engineer Path

What do front-end engineers do?

A Front-End Engineer is responsible for creating and implementing the visual elements of a website or application that users interact with. They focus on the user interface and user experience, ensuring that the website is visually appealing, easy to navigate, and responsive across different devices. They work with programming languages like HTML, CSS, and JavaScript to bring designs to life and enhance the interactivity of the website. Their role also involves collaborating with designers and back-end developers to integrate the front-end components seamlessly into the overall system.

9. Back-End Engineer Path

What do back-end engineers do?

A Backend Engineer is responsible for the behind-the-scenes functionality of a website or application. They work on the server-side of the software, handling data storage, retrieval, and processing. Backend Engineers use programming languages like Python, Java, or Ruby to build the logic and functionality that supports the user interface created by front-end developers. Their role involves managing databases, APIs, and server infrastructure to ensure the smooth operation and performance of the application.

10. Business Intelligence Data Analyst

What do business intelligence data analysts do?

A Business Intelligence Data Analyst is responsible for gathering and analyzing data to help businesses make informed decisions. They work with large datasets, extracting valuable insights and trends. They use tools and techniques to clean, transform, and organize data for analysis. Business Intelligence Data Analysts create visualizations and reports to present findings to stakeholders and help them understand complex data. Their role is crucial in helping businesses improve efficiency, identify opportunities, and make data-driven decisions.

11. Data Engineer

What do Data engineers do?

A Data Engineer is responsible for designing, building, and maintaining the infrastructure that supports data storage and processing. They work with large volumes of data, ensuring its accuracy, reliability, and availability. Data Engineers develop and maintain data pipelines, extracting data from various sources and transforming it into a usable format. They collaborate with Data Scientists and Analysts to ensure data is accessible for analysis and reporting.

12. Data Scientist: Natural Language Processing Specialist

What do data scientists who specialize in natural language processing do?

A Data Scientist specializing in Natural Language Processing (NLP) focuses on teaching computers how to understand and process human language. They develop algorithms and models that enable machines to analyze and interpret text or speech data. NLP Specialists work on tasks like sentiment analysis, language translation, and chatbot development. They use techniques like machine learning and deep learning to extract meaningful insights from textual data. Their work helps improve communication between humans and machines, making it easier for computers to understand and respond to human language.

13. Machine Learning/AI Engineer Career Path

What do machine learning specialists do?

A Machine Learning/AI Engineer is responsible for developing and implementing machine learning algorithms and AI models to solve complex problems. They work with large datasets to train and optimize models that can make accurate predictions or decisions. These engineers focus on creating systems that can learn from data and improve their performance over time. They use programming languages like Python and tools like TensorFlow or PyTorch to build and deploy machine learning models.

Skill Paths Available at Codecademy:

If you are interested in becoming a Java Developer, Data Analyst or IT Support Specialist, Check out our review on Merit America