The Global AI Network (GAIn®) is an open, members driven association supporting the development of AI training and certification to the global market. The GAIN portfolio consists of more than 60 badges (training modules), divided over four levels, ranging from Foundation to Master. The GAIn portfolio offers training and certification for all stakeholders in the organization and is aimed at identifying and transforming key processes with AI.
The GAIN portfolio explained
We use GAIn® to build AI skills across the organization.
The 5 core values of GAIN
GAIn is aimed at building all the skills within organizations to radically change key processes with AI to increase productivity. The GAIn portfolio realizes this goal by operating from five core values. the 5 core values are listed below.
1. A modular approach for multiple target groups
In order to answer the multidisciplinary challenges of AI, the GAIn portfolio is developed around three core tracks. The Data Scientist and AI for Business Tracks are built on the successful programs of MIacadamy with over 13 years of experience in the data science- and over 9 years of experience in the business track. The AI Engineer tracks are relatively new and consist of 27 tech badges with a focus on cloud infrastructure, model operationalization, and app development. These are the core tech disciplines needed to radically change processes with algorithms at scale.
In order to create one language, all programs are preceded by a 2-day AI Foundation Program with a special executive version for the C-level of companies.
The total portfolio of GAIn is organized in ten programs all with their own star certification and consists of more than 60 individual course modules and is totaling 114 training days.
2. Build an integrated skillset
All programs integrate 4 key areas relevant to grasp the full potential of AI. For each role in the organization, it is essential to develop a basis in all four areas since use cases are developed in cross-functional teams where understanding each other is key. Besides the basis in all areas, AI experts and leaders also require a deeper understanding of one of the areas, the so-called T-shape. The four areas are:
- Impact & Opportunities: Focuses on designing the use case, aimed at realizing impact
- Leadership & Change: Focuses on setting strategic priorities and building a data-driven culture
- Machine Learning & Statistics: Focuses on developing analytics and advanced modeling skills, including model management
- Data & Technology: Focuses on strong data, ETL, and deep technical skills, including bringing models into production
Especially in the area of Data & Technology, we have seen rapid developments over the last few years, where the knowledge of implementing the AI solution in a robust and scalable way is key.
3. Focus on lasting breakthroughs
Developing an AI solution is one thing, but implementing a solution that will create real lasting value often proves to be a big challenge.
Therefore all GAIn badges have a key focus on creating impact. This is done by working with real-life datasets and challenges and learning which steps are needed to get your idea implemented. For example, the badge Model Operationalization focuses on implementing the technical solution in such a way that it can be used in the business process, including putting the right feedback loops in place to monitor and improve.
4. Content development by the top of the field practitioners
90% of the badges are developed by experts with extensive experience in transforming blue-chip companies.
For example one of our partners at MIcompany Wouter leads the badge on Use case Leadership. It brings together more than 10 years of transformation project experience, in a module full of real-life challenges and how to deal with them. For the 3-year Technology track, this means that our top experts on cloud infrastructure, model operationalization, and app development have translated their knowledge from many use case projects and transformation challenges into hands-on training badges ranging from automating data pipelines, to cloud containerization to cloud infrastructure as code.
The other 10% of the badges are created by top scientists of leading universities from different countries such as Israel – on Baysian and complex networks, The Netherlands – on advanced Econometrics and Germany – on creating shareholder value with AI.
5. Globally scalable through a standardized learning approach
All badges are standardized and certified based on years of hands-on didactical experience. This means that all badges follow a similar design in theory versus case work, that they use high-quality standardized material and end with an exam to test required skill levels. When you pass the exam you receive the accompanying badge certificate. By obtaining all badges at a level you can obtain the star-certification – thereby demonstrating that you master all relevant techniques at that star level.