Certified Artificial Intelligence Practitioner (CAIP)

The Certified Artificial Intelligence Practitioner (CAIP) program is designed for data science practitioners who are new to the field of artificial intelligence and want to develop a vendor-neutral, cross-industry foundational understanding of AI and Machine Learning (ML) concepts, technologies, algorithms, and applications that will enable them to become competent practitioners in a wide range of AI-related job functions. Artificial intelligence (AI) and machine learning (ML) have become indispensable tools for numerous organizations. When utilized effectively, these tools provide actionable insights that drive crucial business decisions and enable organizations to develop thrilling, new, and innovative products and services.

AIBM has a “learn to ace” philosophy, and our team consists of professional and expert educators who ensure that your abilities and skills are enhanced by effectively acquiring course-specific knowledge. This course is designed to provide in-depth knowledge of AI and machine learning to solve critical business problems, using a methodical workflow to develop sound solutions, and demonstrating how to use open-source, commercially available tools to develop, test, and deploy proper solutions while protecting the user’s privacy. This specialized course will prepare professionals in data science who are transitioning into the field of artificial intelligence for the CAIP certification exam.

Certification Program Objectives:

Upon completing the Certified Artificial Intelligence Practitioner (CAIP) program, participants will acquire a diverse skill set, including the ability to:

  • Identify and assess business problems that AI/ML can address, as well as AI/ML-specific solutions.
  • Apply machine learning algorithms to the two most prevalent supervised problems, regression and classification, in addition to the most prevalent unsupervised problem, clustering.
  • Understand the workflow’s essential duties, such as data analysis and model training, and how machine learning tasks can be automated.
  • Explore the most advanced machine learning and deep learning algorithms.
  • Within a workflow, develop a number of effective models to solve business problems.
  • Describe the general strategy for applying AI and ML to solve a specific business problem.
  • Collect and refine a dataset in advance of training and testing.
  • Completing a machine learning model and presenting the results to the intended audience.

Certification Eligibility Criteria:

To apply for certification from The American Institute of Business and Management (AIBM) and its allied institutions, candidates must meet at least one of the following criteria:

  • A Bachelor’s degree from a recognized institution

And/or

  • 2 to 5 years of relevant work experience in the related professional field.

Note: Applicants who do not hold a Bachelor’s degree but possess exceptional professional experience and hold significant positions within their organizations in a relevant field may also be considered for certification on a case-by-case basis, subject to the approval of the AIBM evaluation committee.

Certifying Examination:

  • To be certified as CIAP, student should take up a 1.5 hours online exam conducted by AIBM.
  • The qualifying exam would consist of 50 multiple choice questions, testing core certification modules.
  • Professionals with relevant experience and other qualifying criteria may be exempted from the examination.

Certification Modules: 

  1. Foundations of Artificial Intelligence
  2. Machine Learning and Its Extensions
  3. AI Implementations and Applications
  4. Navigating AI’s Landscape in Business
  5. Ethical Considerations in AI Development and Deployment
  6. AI Governance and Regulation

* The modules of the certification are constantly updated and are subject to change.

Who Should Do This Certification:

  • Individuals with knowledge or a firm grasp of one or two of the following disciplines: software development, applied mathematics and statistics, and business analysis.
  • Individuals/students working as a programmer who are interested in applying machine learning algorithms to business problems, or a data analyst who is familiar with applying mathematics and statistics to business problems.
  • Individuals with several years of experience in the field of information technology and some programming skills.
  • Individuals who desire to advance their career prospects in the field of technology and data science in accordance with business objectives.