Calling All Data Scientists!

McKinsey, in a December 2021 AI survey, came up with a few conclusions that are worth paying attention to: 1) Nearly two- thirds of the respondents said that their companies’ investments in AI will continue to increase over the next three years 2) Over 64% also run their AI workloads on public or hybrid cloud.

DAC, for the very first time, is offering a unique hands-on workshop for Data Scientists. In this workshop offered by Catalit, Data Scientists (and aspiring Data Scientists) will learn how to formulate, train and improve ML models, by using both classic and deep learning algorithms.

Participants will learn to use Google Colab notebooks to train and iterate models. Deep Python knowledge is not needed. In this fast-paced class, you will get a quick introduction to machine learning before moving on to hands-on work. The three-hour course has 2 modules:

Module 1: Introduction to machine learning in Python

At the end of this module the participants will have learnt how to prepare the data and feed it to a machine learning model, as well as how to evaluate the model accuracy.

Module 2: Improving machine learning models

In this module participants are encouraged to iterate on the model they built in module 1 and learn the most useful concept in machine learning: rapid iteration. Concepts around feature engineering, data imputation, feature selection, model improvement, metrics and model performance evaluation in real world will be discussed.

At the end of the two modules, participants will have learnt methods to successfully apply machine learning to problems in their work.

More information about the training is available at the DAC site.