£216

Data Science, stats, machine learning and AI: a primer for managers

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51-53 Hatton Garden

Farringdon

London

EC1N 8HN

United Kingdom

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Refunds up to 30 days before event

Event description

Description

In all sectors, organisations are investing in data analysis. The manager who is responsible for this, whether outsourcing or recruiting a team, is constantly under pressure to keep up with emerging trends and to know how to evaluate vendors and job applicants. This is a difficult task, and although there are plenty of opportunities to learn the technical aspects of analysis, there is little to support the manager, who is not required to be an expert themselves.

The purpose of this one-day, highly interactive workshop is to fill that gap. Participants will be taken on a tour of the four overlapping terms: data science, statistics, machine learning and artificial intelligence. Talks will focus on achieving an intuitive grasp of how the most common analytical methods work; there will be very little mathematics and no programming. At each step, there will be small group activities that make the theory come to life with realistic scenarios.

This workshop will be led by Robert Grant, a statistician, trainer, coach and writer with twenty years' experience working with a wide range of data challenges, and clients in many different industries. Robert is a contributing developer of the open-source probabilistic modelling software Stan. He has taught individuals and groups from many different backgrounds, at St George's Medical School, Harvard Dubai Foundation, Kingston University, for clients like The Economist and the Cabinet Office, and online. His particular interest is in making his subject accessible to all.

Learning outcomes:

After taking this course, participants will:

  • understand what the different terms (data science, statistics, machine learning, artificial intelligence) mean; how they differ and how they came to have different names over time
  • feel more confident in evaluating job applicants for their expertise in these fields
  • understand the motivations and norms of technical staff from statistical or computing backgrounds
  • have some new skills to spot hype around analytical procedures and products such as software
  • understand the significance, and limitations, of big and streaming data for modern analysis
  • have an intuitive grasp of several analytical methods, such as deep learning and random forests, what their strengths and weaknesses are, and what kind of questions about data they can help to answer
  • understand the risks of poorly-defined questions, repeated analyses and dirty data
  • feel more confident in considering analytical options for data
  • have had an opportunity to network with their fellow participants, working in similar roles
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Date and Time

Location

etc Venues

51-53 Hatton Garden

Farringdon

London

EC1N 8HN

United Kingdom

View Map

Refund Policy

Refunds up to 30 days before event

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