AI & Machine Learning

Track 1 – 

AI & Machine Learning FAQs

Anyone who wants to use AI to create value—business leaders and product owners, data analysts and scientists, software/ML engineers, marketers and operations teams, educators and policymakers, and non-technical professionals who need no-code tools to automate tasks, analyze data, and improve decisions.

Artificial Intelligence (AI) enables computers to perform tasks that typically require human intelligence—understanding language, recognizing patterns, generating content, and making predictions. Machine Learning (ML) is the subset of AI that learns from data to improve performance over time. Our training covers core concepts (supervised/unsupervised learning, deep learning, generative AI), practical business use cases, prompt engineering, responsible/ethical AI, and how to evaluate models safely and effectively.

 

We teach the tools used in real projects: Python basics, NumPy, pandas, scikit-learn, TensorFlow, and PyTorch; MLOps with MLflow/Kubeflow; vector databases and retrieval-augmented generation (RAG); and prompt engineering for ChatGPT-class models.
Certification & standards pathways include: ACTVET/CPD-UK accredited courses, vendor tracks (AWS Machine Learning Specialty, Azure AI Engineer, Google Professional ML Engineer), and Responsible AI/governance best practices. No-code options include AutoML platforms and business-user tools.

 

  • Essentials (no-code): 1 day

  • Practitioner (hands-on with code): 2–3 days

  • Professional/Certification bootcamps: 5 days (with project & assessment)
    Delivery formats: in-person (Abu Dhabi/Dubai), live online, or on-site corporate cohorts. Language: English or Arabic. All programs include guided labs, templates, and a capstone aligned to your industry.