CERTIFIED ARTIFICIAL INTELLIGENCE PRACTITIONER PROFESSIONAL (CAIPP)
The Certified Artificial Intelligence Practitioner Professional (CAIPP) program is a comprehensive, practice-oriented certification designed to build strong foundations and applied expertise in Artificial Intelligence. The course covers the complete AI lifecycle—from Mathematical Foundations and Machine Learning to Deep Learning, NLP, Reinforcement Learning and MLOps. With hands-on labs every week and an industry-focused capstone project, CAIPP prepares participants to design, develop, evaluate and deploy real-world AI solutions.
The CAIPP program emphasizes real-world problem solving and industry relevance, blending theory with extensive hands-on implementation using modern AI tools, frameworks and cloud platforms. Participants gain practical experience in data preparation, model selection, training, evaluation, optimization and deployment along with best practices for scalability, ethics and responsible AI. Through case studies, guided labs and a mentored capstone project, learners develop the confidence and competence to translate business requirements into production-ready AI systems, positioning them for roles such as AI Engineer, Machine Learning Engineer, Data Scientist and AI Solutions Architect.
LEARNING OUTCOMES:
1. Understand core AI, Machine Learning and Deep Learning concepts and industry applications.
2. Build and evaluate Supervised/ Unsupervised Machine Learning models. 3.Develop Deep Learning models for Computer Vision and Natural Language Processing.
4. Apply Transformers, Embedding and Large Language Model (LLM) concepts.
5. Implement Data Pipelines, Feature Engineering and model optimization techniques.
6. Deploy AI models using modern MLOps and deployment frameworks. 7.Apply responsible AI principles including fairness, explainability and governance.
8. Design and present an end-to-end AI capstone project aligned with industry standards.
COURSE CONTENTS:
• Introduction to Artificial Intelligence and AI Professional Landscape
• Mathematical Foundations for AI (Probability, Linear Algebra, Optimization)
• Machine Learning Fundamentals (Supervised, Unsupervised, Reinforcement Learning)
•Data Engineering, Feature Engineering and Data Pipelines
• Regression, Classification and Tree-Based Models
• Deep Learning Fundamentals and Neural Networks
• Unsupervised Learning and Dimensionality Reduction
• Computer Vision using Convolutional Neural Networks (CNNs)
• Natural Language Processing, Transformers and Large Language Models •Prompt Engineering, Fine-Tuning, and RLHF Concepts ,Reinforcement Learning (Practitioner Overview)
• Explainable AI, Fairness and Responsible AI Frameworks
•AI Deployment, MLOps, CI/CD and Model Monitoring
• Industry Use Cases and Full-Stack AI Product Development
•Capstone Project Implementation and Presentation
TARGET AUDIENCE:
IT professionals, Software Engineers and Developers seeking AI expertise, Data Analysts, Data Scientists and Business Analysts, Engineering, Computer Science and technology students, Managers, team leads and entrepreneurs leveraging AI for business innovation, Researchers and Academicians interested in applied AI, Professionals from non-technical backgrounds transitioning into AI , Anyone aspiring to build a career in Artificial Intelligence.
ELIGIBILITY:
Educational Qualification: Bachelor’s degree from a recognized institution
Technical Foundation: Basic understanding of AI, Machine Learning, Data Sciences
Field: Computer Science
For professionals with experience in Data Science, Machine Learning and AI
DISCOUNTS: Early bird registration, PIQC Alumni, PN/ NUST Students, Group nominations from the same organization.
COURSE DURATION:4 Months
DAYS: (Every Saturday)
Time: 2:00PM – 6:00PM (PKT)
Venue: Professional Development Centre (PDC) PDC-NUST-PNEC