The lack of skilled AI engineers is mentioned as the top barrier for executing AI initiatives
Only 15% of AI projects make it to production (source Gartner). The most mentioned root cause is a shortage of skilled talent. In the next years, 133 million new jobs in the AI domain will emerge which will make this skill gap even bigger: which means that for every Data Scientist, two to three AI Engineers are required.
GAIn® introduces the AI Engineers track to bridge this skill gap.
The GAIn® AI Engineering track is a 3-year (virtual) program aimed at developing professionals in the field of Data and AI who have the ambition to develop themselves as specialists to drive scalable impact with AI and Data solutions in a production environment.
The biggest problem facing machine learning today isn’t the need for better algorithms (…). It’s getting machine learning from the laptops to production. That’s the real gap.
The GAIn AI Engineers track equips professionals with all skills to build robust AI and data solutions at scale in a production environment. You learn how to master technology topics such as model operationalization, data pipelines & AI application building and AI platform services. And how to effectively work together in multi-disciplinary teams with Machine Learning experts and business professionals.
All courses are based on real-life best practices such as model operationalization, data storage & integration, application development and cloud platform services. The track addresses one of the key requirements for scalable AI: strong collaboration with machine learning experts and business professionals. Integrating skills from the Machine Learning & Statistics, Impact & Opportunity and Leadership & Change domains, is an integral part of the program.
The program starts with a 6-week full-time bootcamp. In the second year, the ‘Expert’ track broadens the participant’s skill-set as an all-round AI Engineer. The final stage of the program is the 1-year ‘Master’ track which enables participants to specialize, for example as AI engineering or AI cloud platform specialists, or as AI solution architects.
☆☆ AI Foundation and AI & Data Bootcamp: Providing the basis
In the bootcamp, you learn the fundamental skills in your journey towards becoming an AI Engineering specialist. With your 2 star certification you will lay the foundation to drive scalable impact with AI and data solutions in a production environment. At the end of the AI & Data Bootcamp, you are able to build an AI application. You learn how to develop effective code in python and work with version control in Git. Implementing a data model and operationalize models behind an API complete the technical skill set of the AI & Data Bootcamp.
Making impact with your AI application requires besides technological knowledge also efficient collaboration with data scientists and business professionals. This starts by understanding the AI process and the most common used AI techniques. As a Practitioner you are able to define how your role and the data scientists role are connected and communicate about AI solutions in an effective way. This results in presenting in the opportunities of your solution with impact in a business context.
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☆☆☆ AI Engineering Expert
With the three-star AI Engineering certification, you obtain an all-round skillset that allows you to build AI and operationalize data solutions in a production environment. As an AI engineering expert, you can operationalize AI models at scale leveraging leading cloud technologies. That means that you learn to set up a database architecture, build and orchestrate automated CI/CD data-pipelines, containerize apps and write infrastructure as code. With a strong focus on the operationalization of their solutions, AI Engineering Experts drive technical design to realize business value and can lead multi-disciplinary meetings to agree on AI solution design.
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☆☆☆☆ AI Engineering Master
With the advanced AI Engineering Program you develop yourself as a specialist in one of the core areas of the Engineering domain. You are able to process unstructured (real-time) data in a production system and implement application security & configuration management.
As an AI Engineering Master, you ensure that your AI solution is up to speed with latest innovations. You have a clear perspective on AI solution architecture and lead your organization by driving AI solution decisions.
Across all star certifications we link theory and practice to ensure that participants are able to bring all learnings directly into practice in their own business context:
- Every training week is designed around a specific impact theme, in which different courses are combined to integrate hard and soft skills.
- Both the Expert and Master programs are completed with a 3-month assignment. In this exchange-program participants create their own project and execute this from start to finish.
- During the entire program participants receive individual coaching focused on personal learning goals. These coaching sessions help participants to discuss the challenges they encounter in their work and help them to craft their personal learning track.