Introduction AI and Machine Learning

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This introduction AI and Machine Learning training provides a  kickstart for everybody who wants to start with Machine Learning.

This training is available as a classroom training as well as a webinar: live connected to the instructor using Skype or Zoom.

AI and Machine Learning is one of the most exciting, innovative and disruptive developments in digital technology.

In this training you will learn the essential principles of Machine Learning and Data Science. You will learn about the latest tools and means available which will enable you and your employees to start right away with Machine Learning.

For years Machine Learning was the strict domain of specialists of Harvard etc. An enormous investment was needed to start a Machine Learning project, in knowledge and hardware. Now complex algorithms (open source code libraries) and user friendly (graphical) tools like Azure Machine Learning(ML), AWS Sagemaker, IBM Watson etc. are available.

Innovation is an important driver for a successful enterprise. More and more businesses enter new markets by using data and information hidden within their organization.

In IT “adaptive” is the buzzword.

To reduce costs of IT or to arm your IT against Advanced Persistent Threats (APT) or to manage thousands of Microservices and containers, a dynamic, smart, solution is vital. Think of Self Healing and UEBA (User Entity Behaviour Analysis).

The IoT produces a huge amount of data, and this amount will only increase. This, combined with cheap storage in the Cloud and user friendly ML tools, enables you to start now with Machine Learning.

After attending this AI and Machine Learning training you will have the basic knowledge of Machine Learning and know which tools are available to start directly with Machine Learning. You will receive references (books, courses, online resources) that enable you to increase your knowledge of Machine Learning.

You can find a detailed agenda at the end of this page.

AI and Machine Learning
AI and Machine Learning

Course duration

This AI and Machine Learning training is offered in one session of 4 hours.

Price

The Web Infra Academy uses two price models: per student or per training. For more information or a quotation please contact us or use the form at the end of this page.

  • Classroom:                                  495,00 Euro per student
  • Webinar – Remote/online:      345,00 Euro per student (using Skype or Zoom)
  • E-learning                                    under development
  • Blended                                        under development

Course dates classroom training

Session 1

  • 20-03-2020, from 09:00 to 13:00, location Nieuwegein, The Netherlands.

Session 2

  • 01-05-2020, from 09:00 to 13:00, location Nieuwegein, The Netherlands.

Session 3

  • 07-09-2020, from 09:00 to 13:00, location Nieuwegein, The Netherlands.

Session 4

  • 06-11-2020, from 09:00 to 13:00, location Nieuwegein, The Netherlands.

Course dates Webinar – remote/online

Session 1

  • 10-04-2020, time will depend on participants, location: online.

Session 2

  • 26-06-2020, time will depend on participants, location: online.

Please register using the form at the end of this page.

This AI and Machine Learning training  is also offered by our partner Global Knowledge,  code training GKAIML.

Voorkennis

Target audience

Business managers, Product Owners, IT managers, architects and designers, DevOps engineers, IT specialists

Agenda Introduction AI and Machine Learning training

  • What is AI en Machine Learning?
  • History of AI and Machine Learning
  • Terminology AI and Machine Learning (Deep learning, General AI, Narrow AI, Singularity, Friendly AI etc. etc)
  • Why now: the 7 “key enablers”
  • Relationship Big Data, IoT and AI/Machine Learning
  • Basic knowledge Data Science
  • The potential of AI and Machine Learning
  • Basic methods for Machine Learning (supervised, unsupervised, deep learning etc.)
  • Which code libraries (algorithms) are available for the different Machine Learning methods
  • Which tools are available for Machine Learning
  • Examples of applied Machine Learning
  • How can I apply Machine Learning in my organization
  • Risks and ethics of AI and Machine Learning: Bias etc.
  • Resources for learning

If you have any questions or are interested in this course, please contact us or use the form below:

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