The phrase "give some training" is correct and usable in written English.
It can be used when referring to the act of providing instruction or education to someone.
Example: "The company decided to give some training to new employees to help them understand the software better."
Alternatives: "provide some training" or "offer some training."
They have given some training that, according to one American commander, includes discussion of human rights.
A spectator unfamiliar with Dessay's capabilities might have taken her not for an opera singer who can act but for an actor with a surprisingly pretty little voice — a voice that, given some training, might really turn into something.
A Haringey Council spokesman said: "It is reasonable for any employer to ensure that staff in the full glare of the media spotlight are given some training to help them deal with this sort of unusual situation".
I do think it would be good if older people like me, who are used to reading the paper in its print form rather than online, could be given some training in how to engage with the online content.
Neil Fraser, now chairman of the Gaelic Media Service, recalls: "If Calum had been given some training after that or if decent management had appeared on the scene then the quality of his voice would have made him an international star". In the absence of such interventions, Kennedy had to find other ways of making a living.
Think back to your early experiences as a manager - your "Management 101 class". You were probably given some training or direction on goal setting.
"If the woman who delivers [the children] is one who has been given some training and who can prevent complications and who can understand risks... women will have a better chance of survival.
Given some training data, the idea of boosting is to iteratively train a function that describes this relationship.
So these are some of the problems and so we really need to be given some training on some of these things (NHIS official, Male).
We use the expectation maximization (EM) algorithm to find a maximum a posteriori (MAP) estimate of the parameters given some training data, allowing the model to adapt to genomes and transcriptomes that may deviate from the assumed distributions for normal genomes and thus model the data more accurately.
