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The ultimate guide to getting started!

TypeScript is an open source programming language developed by Microsoft that is based on JavaScript and adds optional static typing to it. It was developed to facilitate the development of large and complex JavaScript applications while maintaining the advantages of JavaScript such as flexibility and dynamics.

TypeScript code is compiled into JavaScript code that can be executed in all common browsers and JavaScript engines. This means that you can use TypeScript code to develop modern web applications, mobile apps and server-side applications without having to worry about compatibility.

The advantages of TypeScript over JavaScript:

  • Static typing: TypeScript adds static typing to JavaScript, meaning that the data types of variables and functions must be explicitly declared. This can help to avoid errors and make the code easier to understand and maintain.

  • Improved tools: TypeScript offers a range of improved tools that can help developers write, debug and test their code. These include auto-completion, error checking and refactoring tools.

  • Larger code bases: TypeScript is particularly well suited to the development of large and complex code bases. The static typing and improved tools can help to avoid errors and make the code easier to understand and maintain.

TypeScript is a popular choice for the development of:

  • Web applications: TypeScript is commonly used for the development of modern web applications, including Single Page Applications (SPAs) and Progressive Web Apps (PWAs).

  • Mobile apps: TypeScript can also be used for mobile app development with frameworks such as React Native and NativeScript.

  • Server-side applications: TypeScript can also be used to develop server-side applications with Node.js.

You can find more information about TypeScript on the official website.

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Useful information

Your FAQs to TypeScript

Welcome to our TypeScript FAQ section! Here we answer the most frequently asked questions about TypeScript to give you an understanding of this crucial implementation field.

There are several ways to use TypeScript in existing JavaScript projects:

  • Manual conversion: you can manually convert your JavaScript files into TypeScript files and then use the TypeScript compiler to compile them into JavaScript code.

  • Tools: There are several tools that can help you migrate your JavaScript projects to TypeScript step-by-step. These tools include the TypeScript Migration Tool from Microsoft and the TSLint linter.

  • Gradual introduction: You can use TypeScript first for new parts of your project and then gradually extend it to the existing code.

Yes, TypeScript can be used with most JavaScript libraries. However, there are some libraries specifically designed for use with TypeScript that can provide additional benefits. These libraries include the TypeScript Definition Files (d.ts) and the TypeScript Decorators.

You can debug TypeScript code with the same debugging tools you use for JavaScript code. Most modern development tools support TypeScript debugging, including Visual Studio Code, WebStorm and IntelliJ IDEA.

There are many resources where you can learn more about TypeScript. These include the official TypeScript documentation, various online tutorials and courses, as well as books and articles.

Yes, there is an active community for TypeScript developers. You can interact with other TypeScript developers online in forums and discussion groups and get help with problems.

TypeScript offers several ways to perform DOM manipulations. You can use the standard DOM API available in TypeScript, or you can use a TypeScript library such as TypeScript DOM, which offers additional features and benefits.

TypeScript offers several ways to manage asynchronous operations. You can use Promises, Callbacks or Async/Await. TypeScript supports all of these features and offers additional benefits such as type checking and error handling.

You can use various testing frameworks to write tests for your TypeScript code. These frameworks include Jasmine, Mocha and Jest. TypeScript offers additional advantages for writing

Useful information

Your FAQs to Generative AI

Welcome to our Generative AI FAQ section! Here we answer the most frequently asked questions about Generative AI to give you an understanding of this crucial implementation field.

Traditional AI focuses on analysing and understanding existing data, while Generative AI can create new, creative content.

There are different types of Generative AI models, such as GANs, autoencoders and variational autoencoders. Each model has its own strengths and weaknesses.

There are various ways to learn Generative AI:

  • Online courses: there are many online courses that introduce the basics of Generative AI and show you how to use the technology yourself.

  • Bootcamps: Bootcamps offer an intensive learning experience in a short period of time and provide you with the necessary skills to work with Generative AI.

  • Self-study: You can also use books, articles and tutorials to learn Generative AI on your own.

There are many resources for Generative AI, including:

  • Open-source libraries: there are several open-source libraries that can help you work with Generative AI, such as TensorFlow, PyTorch and JAX.

  • Online communities: There are many online communities where you can interact with other people interested in Generative AI.

  • Forums and blogs: There are many forums and blogs where you can find information and tutorials on Generative AI.

There are a growing number of jobs in the field of Generative AI, including

  • Generative AI Engineer: develops and implements Generative AI models.

  • Generative AI Researcher: Researches new Generative AI technologies.

  • Generative AI Artist: Uses Generative AI to create artwork.

  • Generative AI Content Creator: Creates content with the help of Generative AI, e.g. texts, images or videos.

Based on current salary data from Germany, you can expect the following average salaries in the field of Generative AI:

  • Starting salary: approx. €54,703 gross per year

  • Advanced positions: approx. € 62,572 gross per year

  • Management positions: approx. € 97,500 gross per year

(These are only average values and your individual salary may differ)

To prepare for a career in Generative AI, you should:

  • Learn maths and computer science: basic knowledge of maths and computer science is important to understand how Generative AI works.

  • Learn programming: You should be able to programme in a programming language such as Python or R.

  • Introduce machine learning: Machine Learning is the foundation of Generative AI, so you should familiarise yourself with the basics of Machine Learning.

  • Work on Generative AI projects: There are many open source Generative AI projects that you can get involved in. This is a good way to gain practical experience and build your portfolio.

Generative AI has the potential to change society in many ways, e.g:

  • New forms of art and entertainment: Generative AI can be used to create new forms of art and entertainment that were previously unthinkable.

  • Personalised products and services: Generative AI can be used to create personalised products and services tailored to each individual's unique needs.

  • New scientific insights: Generative AI can be used to gain new scientific insights, e.g. by analysing complex data sets.

Improved quality of life: Generative AI can be used to improve people's quality of life, e.g. by developing new medical treatments or more efficient energy systems.

At neue fische, we integrate AI learning content into every bootcamp where it makes sense in terms of content. If you are interested in this, you should take a closer look at our Web Development and Data Science bootcamp. And we will soon be launching a short format on-demand Generative AI course, in which you can learn flexibly at your own pace from anywhere at any time. Stay tuned!

Bootcamps offer a structured learning environment, live lessons, practical projects and direct feedback from lecturers/coaches and fellow students. Compared to self-study, they enable faster learning progress as they focus on intensive, focussed training.

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