Certified Artificial Intelligence Foundation (CAIF)
Course Overview
GSDC’s global accredited Artificial Intelligence Foundation displays proven knowledge and competencies of methodology which is used to design and build a non-human system simulating human intelligent behaviour. This artificial intelligence certification exam tests candidates’ knowledge and understanding of the terminologies and key AI principles.
You will become AI certified while improving your capability to build and design an AI system with the help of machine learning. This qualification will help you to understand how businesses receive benefits of having AI-enabled systems and the challenges associated with building such systems.
Course Fee: $200
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1. Learn Principles and terminologies of human and Artificial Intelligence (AI).
2. Machine learning best practices.
3. Describe how AI is part of ‘Universal Design,’ and ‘The Fourth Industrial Revolution’.
4. Learn to avoid challenges of Artificial Intelligence.
5. Learn and manage the risks of Artificial Intelligence.
6. Learn to drive AI-based projects effectively.
• Engineers, Scientists
• Chief technical officers
• Chief information officers
• Change practitioners and managers
• Service architects
• Program head or Project head
• Portfolio strategists
• Process architects
• Business strategists and consultants
• Web page developers
• Showcase your expertise.
• Learn to build smarter systems.
• Stay ahead of your career.
• Enhance your understanding of AI
Programming knowledge is beneficial for this particular certification.
• 40 multiple-choice questions
• Participants must score a minimum of 65% of the total marks (i.e. 26 out of 40) to pass this examination.
• 60-minutes duration.
In case the participant does not score the passing percentage, they will be granted a 2nd attempt at no additional cost. Re-examination can be taken up to 30 days from the date of the 1st exam attempt.
Examination Syllabus
Section 1
• AI importance in today’s business.
• Fundamentals of AI, Machine Learning, and Deep Learning.
• AI implementation and challenges.
• Fundamentals of AI, Machine Learning, and Deep Learning.
• AI implementation and challenges.
Section 2
• Customer experience (CxDNA) model for AI implementation
• Use of AI to create demand, to enable sales, and to drive customer service.
• Analyze customer segments, conversion rate optimization.
• Use of AI to create demand, to enable sales, and to drive customer service.
• Analyze customer segments, conversion rate optimization.
Section 3
• How AI can be used to optimize your operating processes to increase agility, reducing costs, enhance quality.
• AI in Operations Ecosystem: Sourcing, Making, Storing, Routing, and Delivering products and services.
• AI in Operations Ecosystem: Sourcing, Making, Storing, Routing, and Delivering products and services.
Section 4
• AI for business support functions like Human Resource Management, Financial Management, IT Systems Management, and Risk Management.
• AI-driven candidate screening.
• AI-driven collections management.
• AI-driven code development.
• AI for fraud prevention.
• AI-driven candidate screening.
• AI-driven collections management.
• AI-driven code development.
• AI for fraud prevention.
Section 5
• AI for Travel and Tourism.
• AI for Healthcare.
• AI for Automobiles.
• AI for Banking.
• AI for Healthcare.
• AI for Automobiles.
• AI for Banking.
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