1. AI Fundamentals
Sessions 1–3- ›What AI is, how it is built, and where it is headed
← Higher Education
🤖AI & Machine Learning
From first principles to deployed AI.
A full-year Proficiency specialisation that takes students from AI fundamentals through statistics, classical machine learning, deep learning, computer vision, NLP and generative AI, to deploying real applied AI projects. The complete stack a working AI practitioner needs, taught at higher-education depth.
- 30 sessions
- 10 modules
- Proficiency level
- Recommended: foundational programming exposure helpful, not required
- One academic year, 2 sessions a week at 1 hour each
- Institution-enrolled, live instruction
Quick answer
AI & Machine Learning is a proficiency programme from NASCA: 30 sessions, taught live by a NASCA instructor, closing with a NASCA × World STEM Federation certificate.
From first principles to deployed AI.
What you'll learn
- ✓
Build a rigorous statistical and mathematical foundation for AI and machine learning
- ✓
Train, evaluate and tune machine learning and deep learning models
- ✓
Apply computer vision, NLP and generative AI techniques to real problems
- ✓
Deploy AI systems using MLOps practices and deliver a complete applied capstone
Skills you'll gain
- AI Fundamentals
- Statistics & Probability
- Python for Data Science
- Data Analytics
- Machine Learning
- Deep Learning & Neural Networks
- Computer Vision
- Natural Language Processing
- Generative AI & LLMs
- MLOps & AI Deployment
Tools you'll use
- Python
- NumPy / Pandas
- scikit-learn
- TensorFlow / PyTorch
- Hugging Face
- OpenCV
- Jupyter
- Cloud deployment platforms
Details to know
- •WSF-accredited, individually verifiable Proficiency certificate
- •Taught in English
- •Live instructor-led sessions, delivered inside your institution's calendar
Programme overview
From foundational machine learning through to applied generative and agentic AI, taught at the depth a Proficiency-level certification demands: statistics, model training and evaluation, and real applied projects, not a survey course.
Applied learning project
Across the final module students design, build and deploy a complete applied AI project, from data collection through a working, evaluated model, presented and defended as their capstone.
The curriculum
2. Mathematics & Statistics for AI
Sessions 4–6- ›The quantitative foundation every model rests on
3. Python for AI & Data Science
Sessions 7–9- ›The working language of applied AI
4. Data Science & Data Analytics
Sessions 10–12- ›Cleaning, exploring and reasoning about data
5. Machine Learning
Sessions 13–15- ›Supervised and unsupervised learning, trained and evaluated
6. Deep Learning & Neural Networks
Sessions 16–18- ›From perceptrons to modern architectures
7. Computer Vision
Sessions 19–21- ›Teaching machines to see and interpret images
8. Natural Language Processing
Sessions 22–24- ›Teaching machines to read, understand and generate language
9. Generative AI & Large Language Models
Sessions 25–27- ›Building with and reasoning about modern generative systems
10. AI Deployment, MLOps & Applied Projects
Sessions 28–30- ›Shipping AI responsibly, and the capstone build
Earn a certificate
Complete all 30 sessions and the capstone to earn a WSF-accredited Proficiency certificate in AI & Machine Learning.
Offered by NASCA, accredited by the World STEM Federation.
Run AI & Machine Learning with your next cohort.
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