Corporate AI & Technology Training Catalog

AI Security & Red Teaming Preventing Unexpected Code Execution in LLM and Agent Systems RuneLab Academy · 12 hours

Teaches how to prevent remote code execution (RCE) and injection vulnerabilities caused by executing LLM- and agent-generated Python, SQL, shell or template outputs using AST validation and safe output handling.

12 hours

Live Course

5 modules

AI Security & Red Teaming Sandboxing and Isolated Execution Environments for AI Agents RuneLab Academy · 12 hours

Teaches how to isolate code-executing, file-processing and browser-using AI agents inside secure sandboxes using Firecracker microVMs, gVisor, Kata Containers, WebAssembly and strict network egress controls.

12 hours

Live Course

5 modules

Model Security & AI in Cybersecurity AI and Machine Learning Model Security Fundamentals RuneLab Academy · 12 hours

Covers model extraction, membership inference, model inversion, poisoning and evasion attacks against machine learning and deep learning models using the MITRE ATLAS framework, along with practical defenses.

12 hours

Live Course

5 modules

Model Security & AI in Cybersecurity Adversarial Machine Learning: Evasion Attacks and Robustness Defenses RuneLab Academy · 12 hours

Hands-on training on FGSM, PGD, Carlini & Wagner, AutoAttack and black-box evasion attacks using the IBM Adversarial Robustness Toolbox (ART), paired with adversarial training and certified robustness defenses.

12 hours

Live Course

5 modules

Model Security & AI in Cybersecurity AI Data Poisoning and Backdoor Attacks in Training and Fine-Tuning RuneLab Academy · 12 hours

Teaches how to detect and prevent label flipping, clean-label poisoning and hidden backdoor/trojan attacks in training and fine-tuning datasets using spectral signatures, activation clustering and data sanitisation.

12 hours

Live Course

5 modules

Model Security & AI in Cybersecurity Deep Learning Model Security: Architectures, Weights and Inference Protection RuneLab Academy · 18 hours

In-depth training on protecting vision, audio, biometric and multimodal deep neural networks against weight and architecture theft, feature reconstruction, sponge latency attacks and inference-layer compromises.

18 hours

Live Course

5 modules

Model Security & AI in Cybersecurity MLOps Security and DevSecOps for Machine Learning Pipelines RuneLab Academy · 12 hours

Teaches how to secure the end-to-end MLOps lifecycle—across data pipelines, Jupyter workspaces, MLflow, Kubeflow, model registries, CI/CD and KServe/Kubernetes serving—using Sigstore/Cosign, ModelScan and Zero Trust controls.

12 hours

Live Course

5 modules

Model Security & AI in Cybersecurity LLM Application Security: OWASP Top 10 and Prompt Injection Defense RuneLab Academy · 12 hours

Covers the full OWASP Top 10 for LLM Applications—including direct and indirect prompt injection, improper output handling, unbounded consumption and sensitive data disclosure—from a secure software development (SSDLC) perspective.

12 hours

Live Course

5 modules

Model Security & AI in Cybersecurity AI Red Teaming and Machine Learning Model Penetration Testing RuneLab Academy · 12 hours

Hands-on training on conducting end-to-end penetration tests against classical ML, deep learning and LLM APIs using MITRE ATLAS, Counterfit, ART, garak and PyRIT, and producing actionable pentest reports.

12 hours

Live Course

5 modules

Model Security & AI in Cybersecurity AI Applications in Cybersecurity Operations and Defense RuneLab Academy · 12 hours

Hands-on training on applying machine learning and LLMs across cybersecurity—from phishing and malware detection to vulnerability prioritisation, cyber threat intelligence (CTI) analysis and SecOps assistants.

12 hours

Live Course

5 modules

Model Security & AI in Cybersecurity AI-Driven Cyber Threat Detection for Endpoint, Network and Cloud RuneLab Academy · 12 hours

Teaches how to detect malware, ransomware, C2 traffic and multi-stage attack chains across EDR, NDR and cloud telemetry using behavioural machine learning, sequence models and graph analytics.

12 hours

Live Course

5 modules

Model Security & AI in Cybersecurity Anomaly Detection with Machine Learning for Security and Operations RuneLab Academy · 12 hours

Teaches how to build unsupervised and semi-supervised anomaly detection pipelines on logs, network traffic and user behaviour (UEBA) using Isolation Forests, Autoencoders, time-series and graph methods while minimising false positives.

12 hours

Live Course

5 modules

Model Security & AI in Cybersecurity AI-Powered SIEM and Modern SOC Operations RuneLab Academy · 12 hours

Teaches how to integrate LLM assistants, natural-language-to-KQL/SPL query generation, automated alert enrichment, triage agents and incident summarisation safely into SIEM, SOAR and modern SOC operations.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Machine Learning Fundamentals RuneLab Academy · 12 hours

Supervised and unsupervised learning, train/test splits, overfitting, core metrics and first models in scikit-learn, so technical teams can frame a business problem as an ML task and build a sound baseline.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Advanced Machine Learning RuneLab Academy · 12 hours

Gradient boosting, ensembles and stacking, hyperparameter optimisation with Optuna, imbalanced data, probability calibration and custom loss functions for experienced data scientists building production-grade models.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Machine Learning for Data Analysis RuneLab Academy · 12 hours

Takes analysts beyond classic reporting with segmentation, driver analysis, anomaly flagging and simple predictive models in Python, scikit-learn and SHAP, producing analyses that tie insight to business decisions.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Feature Engineering for Machine Learning RuneLab Academy · 18 hours

Categorical encoding, time and window-based features, target encoding, interaction and text features, feature selection and feature stores: a systematic approach to the step that most improves model performance on tabular data.

18 hours

Live Course

5 modules

Machine Learning & Applied Data Science Model Evaluation and Explainability RuneLab Academy · 12 hours

Choosing the right metrics, evaluation tied to business KPIs, error analysis, fairness checks and model explanation with SHAP, LIME and PDP, so models can be presented to stakeholders reliably and understandably.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Model Validation and Model Risk Management RuneLab Academy · 12 hours

Independent model validation: data and conceptual soundness checks, backtesting, stability (PSI), challenger models, stress tests and findings reporting, producing a validation report aligned with a model risk management framework.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Time Series Forecasting RuneLab Academy · 12 hours

Time series forecasting with ARIMA, ETS, Prophet and LightGBM-based approaches, working hands-on with seasonality, exogenous variables, hierarchical series, backtesting and prediction intervals to build reliable forecasts.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Anomaly Detection with Machine Learning RuneLab Academy · 12 hours

Detecting unusual behaviour in unlabelled data with statistical methods, Isolation Forest, LOF, autoencoders and time series anomaly techniques, including threshold setting, alert fatigue and evaluation strategies.

12 hours

Live Course

5 modules

End-to-end machine learning with Scikit-learn, XGBoost, LightGBM, and CatBoost, covering feature engineering, Optuna hyperparameter tuning, imbalanced data, and SHAP/LIME explainability.

24 hours

Live Course

3 modules

Machine Learning & Applied Data Science Fraud Detection with Machine Learning RuneLab Academy · 12 hours

Behavioural features, gradient boosting, anomaly scores and hybrid rule-model setups for payment, insurance and account fraud, with hands-on work on extreme class imbalance, delayed labels and operational threshold management.

12 hours

Live Course

5 modules

Machine Learning & Applied Data Science Risk Scoring and Credit Scorecard Modelling RuneLab Academy · 12 hours

Variable analysis with WoE/IV, logistic regression scorecards, gradient boosting alternatives, reject inference and score calibration for credit, insurance and supplier risk, building explainable and auditable risk scores.

12 hours

Live Course

5 modules