TrainingApril 2025· 3 min read

Aurora team earns AI certifications from Talent Garden, Infofactory and Databricks

The Aurora team has obtained formal certifications from companies specialised in AI technology development and training, covering the full spectrum of competencies required to design, develop and implement artificial intelligence solutions in real business contexts.

Topics covered

The training programme covered the entire AI solution lifecycle, from theoretical foundations to practical implementations. Topics ranged from the basics of supervised and unsupervised machine learning through to the most recent architectures and language model customisation techniques:

Supervised Machine LearningUnsupervised Machine LearningTransformer architecturesLarge Language Models (LLM)Prompt EngineeringRAG (Retrieval-Augmented Generation)LLM Fine TuningModel trainingAPI integrationGenerative AIAI risks and limitationsEthics and responsible AIProduction deploymentModel evaluation

Particular attention was paid not only to the advantages of AI technologies, but also to their limitations and risks: model hallucinations, context window constraints, bias issues, data confidentiality management and cloud provider dependency. Understanding limitations is an essential part of responsible consulting.

The value of continuous training at Aurora

The world of artificial intelligence moves at unprecedented speed. New models, new architectures and new techniques emerge monthly: GPT-4, then Claude, then Gemini, then open-source models like Llama and Mistral, then mixture-of-experts architectures, then reasoning models. Keeping pace requires systematic commitment to training, not sporadic efforts.

At Aurora, continuous learning is considered a professional responsibility towards clients: every solution we propose must be based on the best technologies currently available, not those we simply have the most familiarity with. This means investing consistently in certified training, following research publications, testing new models and updating recommendations accordingly.

"Continuous learning in AI is not optional — it is a structural necessity. Models change every month, techniques evolve, and what was considered state-of-the-art six months ago may already be superseded. This is why systematic training is one of Aurora's founding values."

The certifications obtained with Talent Garden, Infofactory and Databricks represent one milestone in this journey, not a destination. Training will continue at the same pace as the industry evolves.