A new AI Expert Roadmap developed by German software company AMAI is garnering keen interest from aspiring AI professionals around the world. The project presents a series of clear and easy-to-follow charts “demonstrating the paths that you can take and the technologies that you would want to adopt in order to become a data scientist, machine learning or AI expert.”
AI’s ever-expanding role in our everyday lives has more and more people and enterprises seeking efficient ways to learn AI basics and gain insights on industry trends. The AI Expert Roadmap is designed to do just that. The project was originally created as a training guide for AMAI employees in the tech-rich city of Karlsruhe. It proved so useful that they released it on GitHub last week, where it has already received over 3,500 stars.
This interactive roadmap is user-friendly and can be customized. The content listed in each sub-module can be linked to a designated website, and learners can easily find definitions and expanded content for each term via Wikipedia or other sources. The AMAI team says the roadmap will be automatically updated as new research appears.
The roadmap aims to not only provide learners with an overall concept of artificial intelligence but also to guide their exploration and studies in different areas of the field. The developers do not encourage simply targeting the most advanced or “hip and trendy” technologies. In scientific research, they stress, one needs to know which tool is best for a given task, and so users are advised to “grow some understanding of why one tool would better suited for some cases than the other.”
Paths include data science, machine learning, deep learning, and data engineering. Each lists essential resources such as papers with code, version control, semantic versioning, changelogs, etc. The developers advise beginners to start with data science basics to acquire a foundation and then transition to machine learning and deep learning or data engineering.
For more on the AI Expert Roadmap, visit the project GitHub.
Reporter: Yuan Yuan | Editor: Michael Sarazen
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