Data Analytics with AI Bootcamp
About This Course
This course equips learners with the practical knowledge and skills to perform Data Collection and Analysis, Data Analysis and Interpretation, and Common Data Environment Management (CDEM) to support business and project decision-making. Learners will develop competencies to collect, extract, validate, organise, and interpret data according to defined business and project requirements while applying data governance principles to ensure data quality, integrity, security, and compliance throughout the data lifecycle.
Learners will utilise SQL and relational database concepts to retrieve, structure, prepare, clean, and transform datasets before applying exploratory data analysis, statistical techniques, Artificial Intelligence (AI)-assisted analytics, and Automated Machine Learning (AutoML) to analyse and interpret data, extract meaningful patterns, trends, predictive insights, and evidence-based recommendations that improve organisational performance and decision-making.
The course further develops competencies in Common Data Environment Management (CDEM) by enabling learners to implement Common Data Environment (CDE) principles and data governance practices to manage, maintain, govern, and share project and organisational data. Learners will improve information accessibility, facilitate collaboration, support project delivery, and strengthen evidence-based decision-making across business functions.
Through realistic workplace datasets and business scenarios, learners will develop interactive dashboards and analytical reports to communicate analytical findings, monitor organisational performance, report impact indicators, and present evidence-based recommendations that support operational excellence, continuous improvement, and strategic business outcomes.
What You'll Learn
Perform Data Collection and Analysis by collecting, extracting, validating, organising, and interpreting data according to defined business and project requirements while applying data governance principles to ensure data quality, integrity, security, and compliance throughout the data lifecycle.
Utilise SQL and relational database concepts to retrieve, structure, prepare, clean, and transform datasets for analysis in accordance with organisational data governance requirements.
Perform Data Analysis and Interpretation by applying exploratory data analysis and statistical techniques to analyse, interpret, and evaluate datasets, extract meaningful patterns, trends, predictive insights, and actionable business recommendations that improve organisational performance and support evidence-based decision-making.
Leverage Artificial Intelligence (AI)-assisted analytics and Automated Machine Learning (AutoML) tools to generate predictive insights, support predictive modelling, and enhance business and project decision-making.
Perform Common Data Environment Management (CDEM) by implementing Common Data Environment (CDE) principles and data governance practices to manage, maintain, govern, and share project and organisational data, improving collaboration, information accessibility, decision-making, and project delivery efficiency.
Develop interactive dashboards and analytical reports to communicate analytical findings, monitor organisational performance, report key performance and impact indicators, and present evidence-based recommendations that support operational excellence, continuous improvement, and strategic business decision-making.
Entry Requirements
Learners should possess a minimum of 3 GCE 'O' Level passes, including English, or an equivalent qualification. Alternatively, learners should possess Workplace Literacy and Numeracy (WPLN) Level 5 or equivalent to understand course materials, participate in learning activities, and complete written and practical assessments. Learners should have basic computer literacy, including the ability to operate common office productivity applications and manage digital files. No prior work experience in data analytics, business intelligence, SQL, Artificial Intelligence (AI), or Common Data Environment (CDE) management is required. Prior knowledge of data analytics, SQL, AI, or CDE management is not required, although familiarity with spreadsheet applications such as Microsoft Excel would be advantageous.