This intermediate 5 days programme provides professionals with a rigorous, practice-oriented grounding in Business Intelligence & Analytics for Finance Professionals. Designed for those working across the Digital & Technology sector, the course combines established theoretical frameworks with current industry practice through expert-led instruction, structured case studies, and hands-on workshops.
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About this programme
This intermediate 5 days programme provides professionals with a rigorous, practice-oriented grounding in Business Intelligence & Analytics for Finance Professionals. Designed for those working across the Digital & Technology sector, the course combines established theoretical frameworks with current industry practice through expert-led instruction, structured case studies, and hands-on workshops.
Participants will engage with the most relevant tools, standards, and methodologies used in Data Analytics today. By the final day, delegates will leave with a clear personal action plan and the confidence to apply their learning immediately, contributing to improved performance, compliance, and competitive advantage within their organisations.
Equip professionals with the knowledge, skills, and frameworks required to excel in Business Intelligence & Analytics for Finance Professionals, driving measurable improvement in Digital & Technology performance and delivering tangible value to their organisations.
11 key learning outcomes
Understand the strategic landscape of digital transformation and its impact on the energy sector
Apply data analytics and visualisation techniques to extract actionable insights from operational datasets
Evaluate AI and machine learning applications relevant to oil and gas, energy, and industrial operations
Assess cybersecurity risks in operational technology environments and apply mitigation frameworks
Design digital use cases that deliver measurable business value and operational improvement
Communicate digital strategy and technology roadmaps to senior leadership and business stakeholders
Apply cloud computing concepts and data architecture principles to enterprise digital initiatives
Understand and apply relevant digital standards, governance frameworks, and data management practices
Evaluate emerging technologies — IoT, digital twins, RPA, and blockchain — for energy sector applications
Build and prioritise a digital transformation roadmap aligned to organisational goals and capabilities
Apply change management principles to drive digital adoption across technical and non-technical teams
5 training days · 15 modules · hands-on workshops
Establish the data science workflow and core programming skills for analytical work.
Python EDA exercise: teams load a provided oil and gas production dataset into Pandas, perform exploratory analysis, visualise key relationships, and present three data quality issues found.
Build and evaluate supervised learning models for prediction and classification tasks.
Predictive model build: teams train a production decline prediction model on a provided dataset, tune hyperparameters, and evaluate performance using cross-validation.
Apply clustering, anomaly detection, and time series methods to operational datasets.
Anomaly detection exercise: teams apply Isolation Forest and statistical threshold methods to a SCADA sensor dataset, compare detection results, and visualise flagged anomalies.
Apply neural network architectures to image, text, and sensor data in energy sector contexts.
Computer vision application: teams fine-tune a pre-trained CNN on a provided industrial inspection image dataset and evaluate detection accuracy for corrosion or defect classification.
Deploy, monitor, and govern machine learning models in production environments.
Capstone AI project: teams present a complete ML pipeline for their chosen energy sector use case, covering data preparation, model selection, evaluation, deployment plan, and governance considerations.
This programme is designed for professionals across these roles
Professionals working with data to generate insights, models, and business intelligence
Engineers managing information technology or operational technology systems and infrastructure
Leaders responsible for digital strategy, technology investment, and transformation programmes
Security teams protecting operational technology and digital assets in industrial environments
Operations, maintenance, and engineering staff adopting digital tools in their work processes
Innovation champions tasked with identifying and delivering digital use cases across the business
Upcoming public dates — enrol anytime
This course carries internationally recognised professional credits
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Speak with our training advisors to confirm availability, group rates, and customised in-house options.