Course: The AI Practitioner

$89.00
$107.69 incl. vat

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duration: 4 hours |

Language: English (US) |

access duration: 90 days |

Details

Are you interested in a role as AI Practitioner? This course will give you an idea about the scope of the work and teach you some skills in the domain of artificial intelligence. You’ll learn to optimize AI models to deliver reliable outcomes in most of the cases. You get to know advanced optimization techniques for AI Development, including multiple optimization approaches like Gradient Descent, Momentum, Adam, AdaGrad and RMSprop optimization. You'll also learn about advanced techniques for hyper parameter tuning for AI development.

Result

After completing this course, you have more insight about the role and responsibilities of an AI Practitioner, optimizing AI solutions and tuning AI solutions.

Prerequisites

No formal prerequisites. However, prior knowledge of artificial intelligence is strongly recommended.

Target audience

Software Developer, Data analist

Content

The AI Practitioner

4 hours

The AI Practitioner: Role & Responsibilities

  • AI Practitioner is a cross-industry advanced AI Developer

  • position that has a growing demand in the modern world. Candidates
  • for this role need to demonstrate proficiency in optimizing and
  • tuning AI solutions to deliver the best possible performance in the
  • real world. AI Practitioners require more advanced knowledge of
  • algorithm implementations and should have a firm knowledge of
  • latest toolsets available. In this course, you'll be introduced to
  • the AI Practitioner role in the industry. You'll examine an AI
  • Practitioner's skillset and responsibilities in relation to AI
  • Developers, Data Scientists, and ML and AI Engineers. Finally,
  • you'll learn about the scope of work for AI Practitioners,
  • including their career opportunities and pathways.

The AI Practitioner: Optimizing AI Solutions

  • Optimization is required for any AI model to deliver reliable

  • outcomes in most of the use cases. AI Practitioners use their
  • knowledge of optimization techniques to choose and apply various
  • solutions and improve accuracy of existing models. In this course,
  • you'll learn about advanced optimization techniques for AI
  • Development, including multiple optimization approaches like
  • Gradient Descent, Momentum, Adam, AdaGrad and RMSprop optimization.
  • You'll examine how to determine the preferred optimization
  • technique to use and the overall benefits of optimization in AI.
  • Lastly, you'll have a chance to practice implementing optimization
  • techniques from scratch and applying them to real AI models.

The AI Practitioner: Tuning AI Solutions

  • Tuning hyper parameters when developing AI solutions is

  • essential since the same models might behave quite differently with
  • different parameters set. AI Practitioners recognize multiple hyper
  • parameter tuning approaches and are able to quickly determine best
  • set of hyper parameters for particular models using AI toolbox. In
  • this course, you'll learn advanced techniques for hyper parameter
  • tuning for AI development. You'll examine how to recognize the
  • hyper parameters in ML and DL models. You'll learn about multiple
  • hyper parameter tuning approaches and when to use each approach.
  • Finally, you'll have a chance to tune hyper parameters for a real
  • AI project using multiple techniques.

Course options

We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.

Optional practice exam (trial exam)

To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam. 

Optional practice lab

To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediatelyThe lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience. 

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