Corporate AI & Technology Training Catalog

Machine Learning & Applied Data Science Customer Churn and Propensity Modelling RuneLab Academy · 12 hours

Churn, purchase and cross-sell propensity models covering target definition, customer behaviour features, survival analysis, uplift modelling and campaign targeting, turning predictions into measurable retention and sales actions.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Recommendation Systems RuneLab Academy · 12 hours

Collaborative filtering, content-based and hybrid recommenders, matrix factorisation, implicit feedback, cold-start strategies and ranking metrics for building personalised product and content recommendation engines.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Predictive Maintenance with Machine Learning RuneLab Academy · 12 hours

Failure probability and remaining useful life (RUL) prediction from sensor, telemetry and maintenance logs, with hands-on signal feature engineering, health indices, early-warning thresholds and maintenance cost optimisation.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Demand Forecasting for Supply Chain and Retail RuneLab Academy · 12 hours

SKU-location demand forecasting covering promotions, price elasticity, stockout censoring adjustment, intermittent demand (Croston/ADIDA), hierarchical reconciliation and probabilistic forecasts tied to safety stock.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Optimization and Decision Systems RuneLab Academy · 12 hours

Bridging predictive models and mathematical optimisation: LP/MILP formulation, capacity, scheduling, routing and budget/price allocation with OR-Tools and Pyomo, plus stochastic and contextual decision systems under uncertainty.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Model Development with XGBoost and LightGBM RuneLab Academy · 12 hours

Mastering tabular gradient boosting with XGBoost, LightGBM and CatBoost: tree-growth strategies, native categorical and missing-value handling, ranking/quantile/custom objectives, monotonic constraints, Optuna and fast inference.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Automated Machine Learning (AutoML) RuneLab Academy · 12 hours

Automated model selection, hyperparameter search and multi-layer stacking with AutoGluon, FLAML and Optuna, covering compute budget management, leakage checks and moving from rapid baselines to production.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Explainable AI (XAI) RuneLab Academy · 12 hours

Glass-box models (EBM, GAM), TreeSHAP/KernelSHAP, ALE, counterfactual explanations (DiCE), uncertainty quantification and regulatory compliance for producing auditable, actionable explanations in high-stakes decisions.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Causal Inference and Uplift Analytics RuneLab Academy · 12 hours

Moving from correlation to causation with DAGs, propensity scores, Double Machine Learning (EconML/DoWhy), heterogeneous treatment effects (CATE) and Difference-in-Differences to measure price, campaign and policy impact.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Federated Learning and Privacy-Preserving ML RuneLab Academy · 12 hours

Collaborative model training across institutions or edge devices without centralising raw data: Flower framework, FedAvg/FedProx, non-IID data, differential privacy (Opacus) and secure aggregation.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Online Machine Learning and Streaming Analytics RuneLab Academy · 12 hours

Incremental learning on streaming data with River, prequential evaluation, concept drift detection (ADWIN, Page-Hinkley) and contextual bandits for continuous adaptation in real-time systems.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Graph Analytics and Graph Machine Learning RuneLab Academy · 12 hours

Modelling relational data with NetworkX and PyTorch Geometric: centrality and community algorithms, graph features, Node2Vec and GCN/GraphSAGE/GAT for node, link and subgraph prediction in fraud rings and supply networks.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Tabular and Time-Series Foundation Models (TabPFN, Chronos, TimesFM) RuneLab Academy · 12 hours

In-context learning on tabular data with TabPFN v2, plus zero-shot and fine-tuned time-series forecasting with Chronos, TimesFM, Moirai and Lag-Llama, benchmarked against GBDTs and classical models.

12 hours

Live Course

5 modules

Comprehensive deep learning training with PyTorch 2.x covering tensor operations, autograd, CNNs, Transformers, LLM fine-tuning (LoRA/QLoRA), diffusion models, GNNs, and production deployment.

42 hours

Live Course

12 modules

Deep Learning & Natural Language Processing Deep Learning Fundamentals RuneLab Academy · 18 hours

Neural networks, forward pass, backpropagation, activation and loss functions, AdamW, dropout and batch normalisation, giving engineers the skills to build and train their first deep learning models in PyTorch.

18 hours

Live Course

5 modules

Deep Learning & Natural Language Processing Advanced Deep Learning RuneLab Academy · 18 hours

Stable, large-scale deep learning covering BF16/FP16 mixed precision, multi-GPU training with DDP/FSDP, self-supervised and contrastive pretraining, metric learning, knowledge distillation and GPU profiling.

18 hours

Live Course

5 modules

Deep Learning & Natural Language Processing Modern Neural Network Architectures RuneLab Academy · 18 hours

From ResNet and ConvNeXt to Vision Transformers (ViT), Swin, hybrid backbones, State Space Models (Mamba), Mixture-of-Experts (MoE) and multimodal fusion: selecting and designing architectures for your problem and hardware.

18 hours

Live Course

5 modules

Deep Learning & Natural Language Processing Transformer Architectures in Depth RuneLab Academy · 18 hours

Self-attention mechanics, Multi-Head and Grouped-Query Attention, RoPE positional encodings, encoder/decoder/encoder-decoder families, KV caching and FlashAttention, implemented from scratch in PyTorch and with Hugging Face.

18 hours

Live Course

5 modules

Deep Learning & Natural Language Processing Deep Learning with TensorFlow and Keras RuneLab Academy · 18 hours

The Keras 3 and TensorFlow 2 ecosystem: Functional/Subclassing APIs, high-throughput tf.data pipelines, custom GradientTape loops, tf.distribute and enterprise deployment via SavedModel, TF Serving and TFLite.

18 hours

Live Course

5 modules

Deep Learning & Natural Language Processing Model Compression and Edge AI Deployment RuneLab Academy · 12 hours

Quantisation (PTQ, QAT, INT8/INT4), structured pruning, knowledge distillation and deployment with ONNX Runtime, TensorRT, OpenVINO and LiteRT (TFLite) for lower cloud GPU costs and fast edge inference.

12 hours

Live Course

5 modules

Deep Learning & Natural Language Processing Deep Generative Models and Architectures RuneLab Academy · 12 hours

Foundations and architectures of deep generative modelling: VAEs, GANs, Normalizing Flows, Denoising Diffusion (DDPM/Latent Diffusion), Flow Matching and autoregressive models for synthetic data and multimodal generation.

12 hours

Live Course

5 modules

Deep Learning & Natural Language Processing Reinforcement Learning and Sequential Decision Making RuneLab Academy · 12 hours

MDPs, Q-Learning, DQN, Policy Gradients (PPO, SAC), contextual bandits and Offline RL using Gymnasium and Stable-Baselines3 for dynamic pricing, resource allocation and sequential control problems.

12 hours

Live Course

5 modules

Deep Learning & Natural Language Processing Deep Learning for Fraud Detection RuneLab Academy · 18 hours

Deep fraud models over transaction sequences, session clickstreams and payment networks: Transformer/RNN sequence encoders, autoencoder anomaly scores, GNNs for fraud rings and hybrid GBDT+DL architectures.

18 hours

Live Course

5 modules

Deep Learning & Natural Language Processing Deep Learning for Defect and Fault Detection RuneLab Academy · 18 hours

Deep defect and fault detection across inspection images, acoustic/vibration signals and system logs using PatchCore/PaDiM, Anomalib, YOLO/segmentation, 1D-CNNs/autoencoders and normal-only training.

18 hours

Live Course

5 modules