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What are the benefits of training for PRINCE2?

Knowledge Hut

What is PRINCE2 certification training? About two days of training is recommended for each of them and self-study is also allowed. Curriculum Trainings cover in detail the PRINCE2 integrated environment, the 7 principles, the 7 themes, the 7 processes and project tailoring. Thus, both complement each other.

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On-the-job Training: Importance, Types, And Methods

Knowledge Hut

Many organizations use training methods to improve potential hires' preexisting skills and knowledge. Training methods vary according to the type of job, the nature of the industry, and the cost of selecting a particular training method. What is On-the-Job Training?

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How Important is Training & Development in 2024

Knowledge Hut

Training and development are critical for any professional. While on-the-job learning is more likely to be cost-effective and pertinent, professionals generally undertake off-the-job training. Training offers a major chance to nurture the knowledge base you have, but many find the development opportunities cost-prohibitive.

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Register now and save 50% on training at Data + AI Summit

databricks

For a limited time, we're offering 50% off training and certification at Data + AI Summit with the following code: TRAIN50FOTY. This offer.

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Logarithm: A logging engine for AI training workflows and services

Engineering at Meta

In this post, we present the design behind Logarithm, and show how it powers AI training debugging use cases. A common example of metadata is rank ID in machine learning (ML) training, when multiple sequences of log lines are multiplexed into a single log stream (e.g., neuron activations) and gradients during training.

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Introducing the next-gen Meta Training and Inference Accelerator

Engineering at Meta

We are sharing details of our next generation chip in our Meta Training and Inference Accelerator (MTIA) family. MTIA is a long-term bet to provide the most efficient architecture for Meta’s unique workloads.

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Turbocharged Training: Optimizing the Databricks Mosaic AI stack with FP8

databricks

Benchmarking for training (dense) models at scale. We demonstrate great performance (very high MFU) and highlight our use of NVIDIA's Transformer Engine, along with PyTorch FSDP and DTensor.