Course : Certified Artificial Intelligence Professional – CAIP®, PECB CertificationCourse Materials in English
Practical course - 5d
- 35h00 - Ref. PAH
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 | Explain the fundamental principles of AI and its various applications |
| Perform data analysis and create relevant visualizations to support AI projects |
| Apply machine learning techniques to real-world problems, including supervised, unsupervised, and reinforcement learning |
| Implement simple neural network architectures and advanced deep learning architectures such as CNNs |
| Understanding Natural Language Processing (NLP) Systems and Computer Vision Methodologies |
| Understanding Robotics and Expert Systems for AI-Driven Automation |
| Identify and mitigate AI-related risks while ensuring regulatory compliance |
| Develop ethical AI strategies aligned with organizational values and societal needs |
Intended audience
AI professionals, data scientists, and AI experts; IT managers and AI project managers; managers and decision-makers; risk and compliance officers; and future AI managers or executives.
Prerequisites
A general understanding of the basics of programming is recommended.
Certification
The exam consists of an 80-question multiple-choice test, available in English, to be completed in 3 hours as an open-book exam. Upon completion of the course, a certificate of completion for 31 CPD (Continuing Professional Development) credits will be issued. Candidates who have completed the training but failed the exam may retake it once free of charge within 12 months of the original exam date.
Course schedule
1 Fundamentals of AI and Data Analysis
- Fundamental Concepts and Principles of Artificial Intelligence.
- Data analysis and visualization.
2 Machine Learning
- Fundamentals of Data Science and Machine Learning.
- The Life Cycle of a Machine Learning Project.
- Supervised learning.
- Unsupervised learning.
- Advanced machine learning and expanded applications.
3 Deep Learning and Natural Language Processing
- Fundamental Concepts of NLP.
- Basic and intermediate NLP techniques.
- Modern NLP: Transformers and Large Language Models (LLMs).
- Applications of NLP and Future Prospects.
- Fundamental Concepts of Deep Learning.
- Deep learning architectures and advanced techniques.
4 Computer Vision, Robotics, AI Strategy, Governance, and Risk Management
- Generative models and specialized architectures.
- Deep Learning and Future Prospects.
- Computer Vision.
- Robotics.
- AI Safety.
- AI Governance and Strategy.
5 Areas of expertise covered by the exam:
- Area 1: Fundamental concepts and principles of artificial intelligence.
- Area 2: Data Analysis and Visualization.
- Area 3: Machine Learning Modeling.
- Area 4: Deep learning and natural language processing.
- Area 5: Knowledge and Applications of Computer Vision and Robotics.
- Area 6: AI Security.
- Area 7: AI Ethics, Governance, and Strategy.
PARTICIPANTS
AI professionals, data scientists, and AI experts; IT managers and AI project managers; managers and decision-makers; risk and compliance officers; and future AI managers or executives.
PREREQUISITES
A general understanding of the basics of programming is recommended.
TRAINER QUALIFICATIONS
The experts leading the training are specialists in the covered subjects. They have been approved by our instructional teams for both their professional knowledge and their teaching ability, for each course they teach. They have at least five to ten years of experience in their field and hold (or have held) decision-making positions in companies.
ASSESSMENT TERMS
The trainer evaluates each participant’s academic progress throughout the training using multiple choice, scenarios, hands-on work and more.
Participants also complete a placement test before and after the course to measure the skills they’ve developed.
TERMS AND DEADLINES
Registration must be completed 24 hours before the start of the training.
ACCESSIBILITY FOR PEOPLE WITH DISABILITIES
Do you need special accessibility accommodations? Contact Mrs. Fosse, Disability Manager, at psh-accueil@orsys.fr to review your request and its feasibility.
AI professionals, data scientists, and AI experts; IT managers and AI project managers; managers and decision-makers; risk and compliance officers; and future AI managers or executives.
PREREQUISITES
A general understanding of the basics of programming is recommended.
TRAINER QUALIFICATIONS
The experts leading the training are specialists in the covered subjects. They have been approved by our instructional teams for both their professional knowledge and their teaching ability, for each course they teach. They have at least five to ten years of experience in their field and hold (or have held) decision-making positions in companies.
ASSESSMENT TERMS
The trainer evaluates each participant’s academic progress throughout the training using multiple choice, scenarios, hands-on work and more.
Participants also complete a placement test before and after the course to measure the skills they’ve developed.
TEACHING AIDS AND TECHNICAL RESOURCES
• The main teaching aids and instructional methods used in the training are audiovisual aids, documentation and course material, hands-on application exercises and corrected exercises for practical training courses, case studies and coverage of real cases for training seminars.
• At the end of each course or seminar, ORSYS provides participants with a course evaluation questionnaire that is analysed by our instructional teams.
• A check-in sheet for each half-day of attendance is provided at the end of the training, along with a course completion certificate if the trainee attended the entire session.
• The main teaching aids and instructional methods used in the training are audiovisual aids, documentation and course material, hands-on application exercises and corrected exercises for practical training courses, case studies and coverage of real cases for training seminars.
• At the end of each course or seminar, ORSYS provides participants with a course evaluation questionnaire that is analysed by our instructional teams.
• A check-in sheet for each half-day of attendance is provided at the end of the training, along with a course completion certificate if the trainee attended the entire session.
TERMS AND DEADLINES
Registration must be completed 24 hours before the start of the training.
ACCESSIBILITY FOR PEOPLE WITH DISABILITIES
Do you need special accessibility accommodations? Contact Mrs. Fosse, Disability Manager, at psh-accueil@orsys.fr to review your request and its feasibility.
This programme is an original creation, developed by the teaching teams at ORSYS Formation. Any reproduction, representation, adaptation or use, in whole or in part, without the prior written authorisation of ORSYS, is strictly prohibited. ORSYS reserves the right to take any action necessary to protect its intellectual property rights.
Dates and locations
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Remote class
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Date garantie en présentiel ou à distance
Session garantie
This programme is an original creation, developed by the teaching teams at ORSYS Formation. Any reproduction, representation, adaptation or use, in whole or in part, without the prior written authorisation of ORSYS, is strictly prohibited. ORSYS reserves the right to take any action necessary to protect its intellectual property rights.