Artificial Intelligence (AI) is the study of building intelligent machines. It is performed by studying how the human brain works while solving problems and using the findings to construct intelligent software and devices. This Artificial Intelligence for IT Professionals course will provide you with a comprehensive grasp of AI and its applications. The basic components of AI will be discussed, and the distinctions between AI, machine training, and deep learning. This one-day course will also teach you how to train artificial intelligence. You will learn about AI applications in knowledge management and human oversight of AI. They’ll also learn how to put AI into practice in a business setting. You will have an understanding of numerous AI implementation areas such as speech recognition, machine learning, neural networks, advanced robotics, and more by the end of this course.
AI FOR PROFESSIONALS TRAINING
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admin
- Description
- Curriculum
- FAQ
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Prerequisites
- This course does not require any prior knowledge.
- Basic statistics and programming experience, on the other hand, will be advantageous.
What will you gain after this course
- By learning this course, you will know about the behind-the-scenes approach that uses AI and machine learning to drive innovation.
- You will be able to examine how artificial intelligence (AI) is reshaping enterprises by examining marketing strategies and resources of competitive advantage.
- You will also know how to create and execute strategy while also driving innovation.
Jobs you can get
with your AI for Professionals Qualification
- IT Director
- IT Professional
- Executive Director
- Executive Manager
- Operations Director
Select your preferred training delivery mode
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Introduction to Artificial Intelligence (AI)
<ul><li>Introduction to Artificial Intelligence (AI)</li></ul>
Building Blocks of AI
<ul>
<li> Machine Learning</li>
<li> Deep Learning</li></ul>
<li> Machine Learning</li>
<li> Deep Learning</li></ul>
AI vs. Machine Learning vs. Deep Learning
<ul><li>AI vs. Machine Learning vs. Deep Learning</li></ul>
How to train AI?
<ul><li>How to train AI?</li></ul>
Implementing AI in an Organisation
<ul>
<li> Identify AI Opportunities</li>
<li> Develop an AI Roadmap</li>
<li> Identify AI Solutions</li>
<li> Identify Data Requirements</li></ul>
<li> Identify AI Opportunities</li>
<li> Develop an AI Roadmap</li>
<li> Identify AI Solutions</li>
<li> Identify Data Requirements</li></ul>
AI Use Cases in Information Management
<ul><li>AI Use Cases in Information Management</li></ul>
Case Studies
<ul><li>Case Studies</li></ul>
(Human) Supervision of AI
<ul><li>(Human) Supervision of AI</li></ul>
Implementation Areas of AI
<ul>
<li> Voice Recognition</li>
<li> Natural Language Generation (NLG)</li>
<li> Virtual Assistants</li>
<li> Cognitive Computing</li>
<li> Computer Vision</li>
<li> Recommendation Systems</li>
<li> Natural Language Processing</li>
<li> Neural Networks</li>
<li> Robotic Process Automation</li>
<li> Machine Learning Platform</li>
<li> Predictive Analysis</li>
<li> Biometric Recognition</li>
<li> Image Analysis</li>
<li> Deep Learning Platforms</li>
<li> Quantum Computing</li>
<li> Decision Making and Management</li>
<li> Hardware Optimisation</li>
</ul>
<li> Voice Recognition</li>
<li> Natural Language Generation (NLG)</li>
<li> Virtual Assistants</li>
<li> Cognitive Computing</li>
<li> Computer Vision</li>
<li> Recommendation Systems</li>
<li> Natural Language Processing</li>
<li> Neural Networks</li>
<li> Robotic Process Automation</li>
<li> Machine Learning Platform</li>
<li> Predictive Analysis</li>
<li> Biometric Recognition</li>
<li> Image Analysis</li>
<li> Deep Learning Platforms</li>
<li> Quantum Computing</li>
<li> Decision Making and Management</li>
<li> Hardware Optimisation</li>
</ul>
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Course details
Duration
Full time, Part-time, Evening and Weekends, Virtual online
Video
London, Flexible online
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