Certificate In Data Science
The Programme
Enterprises across the globe are shifting their focus to data-driven goals and decision-making. In fact, the International Data Corporation reports that worldwide data will grow 61% to 175 zettabytes by 2025*. So, why is data science so important? Because it enables organisations to efficiently process and interpret data that can be used to make informed business decisions & drive growth, optimisation, and performance. One can learn how to process and understand data that can be used to drive better, smarter decisions within your organisation.
Programme Objective
- Createand implement business strategies leveraging data science.
- Makedata-driven decisions to solve business problems using data insights.
- Demonstratehow analytics can be combined with experiments to make data-informed recommendations for business growth.
- Explainthe key challenges and risks in data science projects.
- Evaluate an organisation’s data strategy and recommend ways to achieve a sustainable competitive advantage.
- Analyse organisational needs and drive business improvement through data science future trends.
Pogramme Learning Outcome
- Transition into a data-centric senior management role
- Gather analytical expertise to handle greater responsibilities.
- Utilise predictive models to build effective strategies that address key issues in business operations and product quality.
- Become a leader for sustainable business growth.
- Spearhead complete ownership of key business tasks and understand underlying strategic implications.
Programme Delivery Methodology:
Face to Face or Online Training
- Practical/ Lab Exercise
- eCoaching
Duration:
5 days
Entry Requirement
No coding is required; however, a basic knowledge of Excel would be beneficial.
Assessment Method
Continuous assessment and the various practical exercise
Learning Materials
There will be a student manual and lab workbook for each participant.
Course Outline
Module 1: Leveraging Data As A Competitive Edge
Module 2: Data Analytics In Action
Module 3: Basic Statistics For Data Analysis
Module 4: Predictive Analytics
Module 5: Field Experiments And Causality
Module 6: Machine Learning Models For Data Analytics
Module 8: Data Science To Drive Business Value
Module 9: Addressing Key Challenges And Risks In Data Science Projects
Module 10: Data Science And The Future