In this School, you will learn
- Digital Data Mining With Application in R
- Data Mining and Big Data Mining for Business Analytics
- Project Management
- Data Visualisation.
- Digital Survey Data Collection.
- Presentation Skills.
- Analysing Data with Microsoft Power BI and Power Pivot for Excel.
Digital Data Mining With Application in R
This Course introduces a learner to
- Web and Data Technologies using R
- Automated Text Mining for Business Analytics.
- Automated Text Classification and Prediction using Machine Learning.
- Interactive Web-Based Data Visualization.
Data Mining and Big Data Mining for Business Analytics
This course covers
- Business Intelligence
- Data Management,
- Big Data Science Analytics with applications in R.
Project Management
This course covers
- Framework, Project Organisation.
- Project Leadership and People Management.
- Project Scope and Quality Management.
- Project Scheduling.
- Project Cost Planning.
- Monitoring and Tracking.
- Issues and Risk Management.
- The Business Case.
- Procurement Management.
- Introduction to Microsoft Projects.
- Project Libre
F
Data Visualisation.
The Course covers
- Data visualisation with Microsoft Power BI.
- Introduction to Data Visualisation using Tableau.
- Advanced Data Visualisation with Microsoft Excel.
- Interactive Web-Based Data Visualization with R.
Analysing Data with Microsoft Power BI and Power Pivot for Excel
This course cover the following topics:
- Data Modelling and presentation.
- The use of Header/Detail Tables.
- The use of Multiple Fact Tables.
- Working with Date and Time
- The use of Snapshots
- Analysing Data and Time Intervals.
- Segmentation Data Models.
Digital Survey Tools
In this course, you will learn
- Data Collection using Survey Monkey.
- Data Collection using Microsoft Forms.
- Data Collection using Google Forms.
Presentations
This course training on presentations using
- Microsoft PowerPoint.
- Google Slides.
- Powtoons. Inforgrapia
- RStudio Presentation
- Latex Beamer.
Katleho Makatjane is a well trained and experienced quantitative business; data miner/big data consultant with more than six years of research experience; community engagement programs and data analysis and data management. His research interest is in data mining and big data methods with applications. In particular, he specializes in Statistical methods used for Text mining and Text analysis, quantitative business and risk analysis, social media and digital tools with social network analysis using R. He also specializes in the area of causal inference in business and finance.