Become a certified Data Scientist or Generative AI Engineer.
Choose Data Science or Generative AI, each about 16 weeks part-time. Both include hands-on JupyterLab practice, real-world case studies and a capstone project, and both prepare you for a Vecorra certification.
Choose a programme
Pick the one that matches the work you want to do. Both end in a Vecorra certification.
Become a certified Data Scientist.
About 16 weeks at around 6 hours a week, starting from Python, SQL and statistics and moving through machine learning, model evaluation, data engineering, deployment and monitoring, responsible AI, business communication, LLMs for data scientists and project discovery to a consulting-style capstone and a team challenge set by an employer. Every section has hands-on JupyterLab practice with exercises that check your own answers, and the programme prepares you for Vecorra certification.
14 sections · About 16 weeks at around 6 hours a week (about 100 hours), plus an optional pre-course of about 10 hours
£699 one-off, or 4 monthly payments of £174.75 · the course for life, the lab for six months · included for cohort members
- Python, SQL and data analysis foundations
- Statistics: probability, hypothesis testing, confidence intervals
- Machine learning modelling with scikit-learn
- Model evaluation, cross-validation and leakage-avoidance
- Responsible AI: fairness, transparency and governance
- Model deployment, monitoring and cloud data platforms
- Business communication: turning analysis into decisions stakeholders act on
- Consulting-style capstone for a fictional UK energy supplier
Become a certified Generative AI Engineer.
About 16 weeks at around 5 hours a week. It starts with software-engineering basics (Python services, Git, testing, FastAPI, Docker), then covers LLMs, RAG, fine-tuning, agents and MCP, evaluation, safety and AWS deployment. It ends with an industry capstone, solution discovery and a real employer challenge, and prepares you for the VCA-GAI certification.
12 sections · About 16 weeks at around 5 hours a week (about 85 hours)
£699 one-off, or 4 monthly payments of £174.75 · the course for life, the lab for six months · included for cohort members
- AI engineering bridge: Python services, Git, testing, FastAPI and Docker
- LLM foundations: tokens, embeddings, attention and transformers
- Prompt engineering and structured outputs with the OpenAI API
- RAG and embeddings: vector search, hybrid retrieval, evaluation
- Fine-tuning and adaptation, including PEFT/LoRA
- Agents, tool use and the Model Context Protocol (MCP)
- Evaluation and LLMOps: golden sets, tracing, regression testing
- Safety, security and EU AI Act-aware governance
- AWS production: Bedrock, ECR, App Runner/ECS, CloudWatch, IAM and CI/CD
- Industry capstone for an independent, portfolio-grade build
- Solution discovery and delivery, then a real employer challenge (TechAccess NI) with handover
You register once, then choose a programme from your student portal. Each is a one-off purchase — the course for life, the lab for six months — and free if you've been added to a cohort.
Coming soon
Machine Learning Engineering
Pipelines, validation, model selection and serving.
MLOps & Cloud
CI/CD for ML, registries, drift detection and infrastructure.
NLP Engineering
Text classification, entity extraction and fine-tuning.
Computer Vision
Detection, segmentation, augmentation and vision deployment.
How it works
Learn
Work through short, practical lessons. Each course is split into focused modules.
Practise in JupyterLab
Every student gets a personal JupyterLab workspace in the cloud, with the course notebooks and datasets ready to run.
Quiz
Take a quiz after every module. You get feedback straight away, with an explanation for each answer.
Sit the certification
When you finish the curriculum, take the Vecorra certification for your programme: a theory exam and a hands-on practical lab.
We support reasonable adjustments, including extra time on certification exams. See our accessibility statement.
Certification
Each certification has a theory exam of 50 questions drawn from a bank of 1,000, plus a practical lab where your own work is graded as well as a multiple-choice paper.
Vecorra Certified Data Scientist
A 50-question theory exam drawn from a bank of 1,000 questions, plus a practical lab in the same JupyterLab environment you used during the programme.
Vecorra Certified Generative AI Engineer
A 50-question theory exam drawn from a bank of 1,000 questions, plus a practical lab in the same JupyterLab environment you used during the programme.
Your own JupyterLab workspace, in the cloud.
There is nothing to install. Open your workspace from any lesson and the notebooks and datasets are already there, including the OpenAI-powered labs on the Generative AI programme. The practical exam uses the same environment.
Register as a student# work/training/machine-learning/03_tree_ensembles.ipynb
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import cross_val_score
model = RandomForestClassifier(n_estimators=300)
scores = cross_val_score(model, X, y, cv=5, scoring="roc_auc")
# mean AUC: 0.91 — nice. now try tuning max_depth…
Ready to start?
Register, pick a programme and learn at your own pace. You finish with a certification and a capstone project for your portfolio.