Program Overview
Data Science is not only for technical professionals! Data Science can be done by people from various backgrounds, such as Business, Commerce, Accounting, Audit and Risk, HR, Marketing, and Finance, to name just a few. The only needed thing is a desire to learn and develop your career further with new digital skills.
By using Data Science in your work, you will accelerate the innovation and productivity of your team and organisation. At the same time, your decision-making will become much better because you will rely on hard facts obtained from the data, and your intuition, developed over the years.
This training program seeks to give people from various non-technical backgrounds the initial skills and knowledge to start using Data Science in their everyday work. Its focus is on doing Data Science without any programming. Therefore, you will not be learning Python, Java, Scala or any other language. Instead, you will be doing Data Science in no time, using a business-friendly tool with a visual model and a well-defined process.
So, ask yourself today, “Do I want to join the Digital Future now?” Then, join us to start the journey!
Learning Outcomes
After attending this program you will be able to:
- Understand the end-to-end process of Data Science
- Perform practical Data Science work
- Apply Data Science in solving specific business problems
- Use Data Science to improve employee productivity
- Drive change without spending big amounts on expensive Data Science tools
Intended Audience
- Finance and Accounting Professionals
- HR professionals
- Engineers
- Marketing Professionals
- Internal and external auditors, CPAs and CAs
- Banking professionals
- Government employees
- Governance, risk management and compliance professionals
- Corporate managers
- Logistics Professionals
Program Outline
- Welcome and Introduction
- The Need for Data Science (DS)
- What is DS – Definition
- Structure of the Session
- The Data Science Process
- Determine the Business Question
- Get the Data
- Prepare the Data
- Analyse the Data
- Answer the Question
- The Data Science Tool - KNIME
- Overview
- Main Functionality
- Demonstration – Creating a project and performing an analysis
- Data Science 101
- Introduction and Characteristics
- Case Study Review – HR
- Practical Exercise 1 - Analysing Employees
- Data Science 201
- Introduction and Characteristics
- Case Study Review
- Fraud
- Sales Performance
- Practical Exercise 2 - Analysing Salespeople, Revenue and Locations
- Session End
- Q&A
- Comments
- End
