The programme will provide an overview of data analytics within the organisation to generate business insights and intelligence using statistical and computational techniques and tools, algorithms, predictive data modelling and data visualisation. This modular course is developed to equip learners with skills to conduct organisational data collection, preparation, analysis, and data analytics capability by improving business performance criteria and data design for organizational processes. Learners will be able to uncover actionable comprehensions from data and identify opportunities within their respective departments or organisation where data can be influenced.
Upon successful completion of this modular course, learners can choose a career to become a Data Analyst, Associate Data Engineer, Business Analyst, Associate Business Analyst, Data Engineer, Senior Data Engineer, and Data Architect. This modular course transfers the knowledge, skills, and abilities related to data analytics.
- Interpret implications of data patterns for organizational benefits of business insight
- Select relevant methods for data preparation
- Manage data science projects by selecting relevant methods for data transformation
- Prioritize relevant methods for Data Visualization
- Manage organisational capacity and business problems using an appropriate method of data analysis that automates analytical model building
- Run complex data mining models using relevant methods to provide business insights
- Communicate the results of data science projects using methods to explore a data set visually and analytically
- Apply relevant methods, tools, and techniques to manage the capacity to perform data science projects
- Make recommendations to guide organisational decision-making to measure the performance of the data science team
IT Executives/Managers, Risk Analyst/Management, Business Analyst, Data Analyst, Banking Executives/Managers, Software Engineers, System Engineers will find this course very insightful with hands-on practical experience.
- Interpret the data patterns in business cases and benefits of business acumen.
- Select relevant methods to appraise solutions and provide insights.
- Select appropriate methods to interpret patterns in data and manage data science projects.
- Prioritise data science projects to implement data models to examine business assumptions.
- Manage organisational capacity, business problems and provide insights for functional projects.
- Run complex data mining models to provide insights in accordance with the standard procedures.
- Communicate the results of data science projects using few methods to investigate data set visually and analytically to reveal results for the relevant projects.
- Apply relevant methods, tools, and techniques to manage the capacity to perform data science projects.
- Make recommendations to guide organizational decision making by applying methods to measure the performance of the data science team.