Training for AI Engineers | QA [Video]

AI governance, including ethics, compliance, and data governance processes.

Programming languages, typically Python, R, Java or C++.

Data science and machine learning and knowledge of algorithms, models, and frameworks.

Deep learning, including experience working with different types of artificial neural networks built from machine learning models.

Mathematics and statistics to interpret or develop machine learning or AI model algorithms.

NLP, natural language and text processing.

Cloud computing in AWS, Azure, or GCP: for deployment of bespoke machine learning or AI models, or to consume and deploy cloud-based AI services.

Software engineering and understanding of version control with git and knowledge of APIs.

DevOps knowledge of CI/CD pipelines and containerisation (as a deployment option).

Database management, including experience with SQL and NoSQL.