Professional Certificate in Business Analytics, Data Science and Decision-Making

Overview

About this course.

The Professional Certificate in Business Analytics, Data Science and Decision-Making is designed to equip participants with real-world analytical skills for business decision-making. Learners progress from foundational data analytics understanding, to visualisation, Python-based analysis, forecasting, and emerging AI trends – building capability to operate confidently in a data-driven environment.

Tools used across the programme: Excel, Power Query, Python, large language models (conceptual), and BI visualisation with Tableau or Power BI, plus Google Launchpad access.

Curriculum

What you will be able to do.

By the end of this programme, participants will be able to:

• Understand descriptive, diagnostic, predictive and prescriptive analytics, and how each informs business decisions
• Explain AI concepts and how large language models enhance productivity and data workflows
• Use Excel and Power Query to clean, transform and prepare datasets
• Apply basic Python for filtering, loading and manipulating structured and unstructured data
• Select and apply effective visualisation techniques, and design dashboards and reports using Power BI or Tableau
• Build compelling data stories to communicate insights
• Apply predictive and forecasting techniques using Python, including regression and machine-learning basics
• Conduct data mining for knowledge discovery, and design simple database and dimensional data models
• Understand data warehousing, web analytics and digital metrics
• Integrate AI and analytical outputs into business strategy for decision-making

Programme structure

Four modules, 56 hours.

• Introduction to analytics: concepts, techniques and tools (7 hrs) – types of analytics, data cleaning and data quality, structured versus unstructured sources, Power Query against Excel formulas, and Power Pivot. Includes a dataset import and transformation workflow
• Data visualisation (16 hrs) – visualisation techniques, storytelling with data, presenting data for decisions, and dashboard development in Power BI or Tableau. Includes building an interactive business dashboard
• Applied business analytics with Python and predictive forecasting (21 hrs) – Python in BI workflows, the M language and its limits, pandas and data frames, filtering and grouping, regression and time-series forecasting on sales, churn and HR turnover, and hands-on work with an LLM including bias, governance and privacy
• Emerging AI future (12 hrs) – big data definition and use, the AI and analytics hype cycle, the infrastructure and architecture behind big data, and cognitive analytics with IBM watsonx

Capstone project: a data-driven business decision report applying all four modules – cleaning, analysing, visualising, modelling, forecasting and presenting insights that support a strategic business decision, demonstrating end-to-end analytics competency from raw data to recommendation.

Audience

Who should attend.

Professionals who want to leverage data for improved insights, strategic planning and business innovation, including:

• Business professionals and decision-makers
• Business and marketing analysts
• Supervisors and managers transitioning into data-driven decision roles
• Entrepreneurs and consultants
• Junior technical professionals seeking to upskill

No prior coding experience is required.

Details

Delivery and fee.

Fees and structure are those on the current course outline. Confirmed dates for every course are on our upcoming intakes page; the Executive Education team confirms the next intake on enquiry.

How we teach

Learning you can apply on Monday.

Our teaching approach incorporates syndicate learning, case studies, regular assessments and immersion in real-life industry projects. Assessment varies by course, combining assignments, tests and participation.