Foundations that translate to decisions
Understand AI, ML, DL, training vs inference, and key limitations like data dependency, overfitting, and domain shift—so you can interpret outcomes, not just headlines.
The Certified AI Practitioner (CAIP) exam is intended for professionals and students who wish to validate their ability to build, deploy, and manage AI solutions in real - world enviornments.
Learn with labs & projects at your own pace.
Timed questions with instant feedback & review.
CAIP is built for professionals who need to evaluate AI claims, choose fit-for-purpose methods, and apply responsible practices—without requiring coding or advanced math.
Understand AI, ML, DL, training vs inference, and key limitations like data dependency, overfitting, and domain shift—so you can interpret outcomes, not just headlines.
Move beyond buzzwords: supervised vs unsupervised vs reinforcement learning, NLP and vision basics, and what GenAI can (and cannot) do—plus how to manage hallucinations.
Learn practitioner-ready governance: fairness, transparency, accountability, privacy concepts (PII, minimization, retention), and risk controls that align with modern regulatory expectations.
Designed for professionals applying these capabilities in real delivery environments.
For professionals shipping models, pipelines and AI-enabled products.
For people responsible for development, evaluation, deployment and monitoring.
For teams translating requirements into reliable, responsible AI solutions.
For advisors guiding architecture, adoption, risk and implementation choices.
The assessment spans the domains below. Weightings indicate relative emphasis in the exam.
AI vs ML vs DL hierarchy and everyday examples Historical evolution: Turing → expert systems → ML → deep learning → GenAI Rule-based systems vs data-driven learning Key terms: algo...
Supervised, unsupervised, and reinforcement learning—when to use each NLP fundamentals: chatbots, translation, sentiment, summarization Computer vision: detection, recognition, ins...
Data quality, quantity, and bias impacts on reliability and fairness Structured vs unstructured vs semi-structured data (tables, text, JSON/XML) Training vs validation vs testing—g...
Finance, healthcare, retail & supply chain, manufacturing, public sector patterns Everyday AI: recommendations, assistants, maps, spam filters, smart photos Enterprise trends: deci...
Fairness, transparency, accountability—practical definitions Bias sources: data, algorithmic, societal (with examples) Governance basics: policies, reviews, monitoring, incident re...
AI in transformation: automation, personalization, insights, innovation Maturity stages: experimenting → operationalizing → scaling → transforming Build vs buy considerations: tale...
AI literacy: probabilistic outputs, limits, and why verification matters Communicating AI with clarity: analogies and outcome-driven messaging Identifying use cases: repetitive, da...
A 90-minute assessment with 250 questions, a 70% passing threshold, delivered through the GIofAI Exam Portal.
The value of the certification is the combination of controlled assessment, identity verification, domain-level performance evidence and a verifiable professional credential.
A professional GIofAI designation supported by a digital certificate and official transcript. The transcript records section-level performance, giving the credential more context than a simple completion badge.
Identity-verified assessment under controlled examination conditions.
Section-wise performance information for a clearer view of your assessed capability.
A professional credential designed to be verifiable and shareable with employers and professional networks.
Use CAIP as a core credential before moving into deeper specialisations.
Get the certification overview, domain weightings, exam format and preparation guidance in one concise guide.
CAIP validates the ability to apply foundational AI concepts, understand core methods (including GenAI), work with data fundamentals, and make responsible AI decisions in real-world scenarios—without requiring coding or advanced math.
Typical delivery is closed book with no external assistance. Environment checks and monitoring help ensure fairness and integrity for all candidates.
 CAIP is typically 50–60 multiple-choice questions (commonly 55). Duration is configurable from 60–120 minutes, with 60–90 minutes recommended for standard delivery.
The pass threshold is 70%. Each question carries equal weight, and there is no negative marking.
Candidates may retake up to two times within six months of the first attempt, with a recommended waiting period of seven days between attempts. Retakes may require a separate purchase.
Register for the CAIP assessment, review the syllabus weightage, and sit the exam when you’re prepared. Designed for professionals who need confident AI judgment—across foundations, methods, data, and responsible practice.