Data Exploration
- Profiling & visual analysis
- Data quality checks
Machine Learning Training
In-company and fully customised. We build practical ML skills—grounded in maths, code and algorithms—so your team can deliver with confidence.
Intro
Machine learning is the driving force behind AI. It lets computers learn from data and environments. Behind the scenes are mathematics, code and algorithms. In this training, we teach your team how to design, implement and evaluate ML solutions the right way.
Who’s it for?
- Complete beginners — a structured, hands-on start.
- Experienced practitioners — sharpen fundamentals & delivery.
- Content and pace are tailored to your context and stack.
Curriculum Topics
Tailor depth and pace to your team. Start with fundamentals; extend into advanced topics as needed.
Data Preprocessing
- Missing values
- Scaling & normalisation
- Categorical encoding
- Outlier treatment
Data Engineering
- Class imbalance
- Transformations & feature pipelines
Supervised Models
- Linear & logistic regression
- LDA, QDA, Naïve Bayes
- k-Nearest Neighbours
- Ensembles:
- Random Forest
- Gradient Boosting, XGBoost, LightGBM, CatBoost
- Neural networks — Deep Learning 101
Unsupervised Models
- Dimensionality reduction: PCA, UMAP, t-SNE
- Clustering: k-Means, DBSCAN, HDBSCAN
- Anomaly detection: Isolation Forest
Model Improvements
- Feature selection
- Hyper-parameter tuning
- Threshold calibration
Concepts
- Bias–variance trade-off
- Metrics & model selection
- Optimisation & regularisation
- Train/validation/test splits
- Overfitting & leakage
Explainability
- Multicollinearity & omitted variables
- Statistical tests & diagnostics
- SHAP (Shapley) basics
Format
- In-company, highly customisable
- Mix of theory, live coding and hands-on exercises
Pricing: Single team price. For scheduling and a quote, please contact us.
Example Programmes
Beginners: 3-day course
A dense, hands-on introduction.
- Data preprocessing
- Model training
- Model fine-tuning
- Hands-on exercises
- Core theory behind the models
Beginners: 5-day course
Normal pace; broader coverage.
- Data preprocessing
- Model training
- Model fine-tuning
- Hands-on exercises
- Core theory behind the models
- Intro to deep learning
- Writing more optimised code
Intermediate: 3-day course
For teams with prior ML experience; faster pace to cover more ground.
- Data preprocessing & leakage pitfalls
- Model training
- Advanced fine-tuning & calibration
- Group exercises & code reviews
- Deeper model theory
Your Trainer
Rick Vink holds a Master’s in Physics and has been dedicated to teaching Data Science and Machine Learning full-time for over 8 years.
While his primary passion has been empowering the next generation of data scientists, he has also shaped industry practices by training countless professionals.
He brings a unique blend of deep theoretical knowledge and practical teaching experience, making complex concepts accessible, engaging and directly applicable in your work.
Ready to book your in-company training?
Tell us about your team, data and goals. We’ll confirm dates and send an quote.