DataWiz

Designed for students within the age group 12-15, the Wizkateers program provides the blend of technical analytics capabilities right from advancing in excel, to training in database systems, to introduction to AI and machine learning. This module is a step closer to becoming a professional data wiz.
Excel250

Excel+

In this course, the student will get hands on instruction of advanced Excel. They will learn to use pivot tables, designing charts and simulation analysis. Later in the course, we will cover complex data interpretation and dashboarding using excel.

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Visualization

This part of the course is about implementing the knowledge from advanced excel. Students will practice how to visualise complex datasets, how to tell a more advanced story with deep insights in a simple context, and explore core principles of data visualisation.

Python250

Python

Python is the highly essential programming language for data science. Keeping this in mind, we will introduce fundamental programming concepts including data structures and database design using Python. Students will work in teams for a project to apply their knowledge and to create their own applications for data processing and visualisation.

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SQL & Database

In order to be a strong data scientist or analyst, it is necessary to be able to retrieve and work with data. For that, one needs to be well efficient in SQL, the most common and standard language to communicate with the database management systems. This course is designed to help students learn about the fundamentals of SQL, building queries to a database and working with data in SQL platforms such as MySQL and Microsoft SQL Server.

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Data Clensing

It is believed that data scientists spend 70% of their time doing data cleaning and mining. For this reason, it is very important to be familiar with the processes of data cleaning and mining. In this course we will introduce cleaning data in Excel, R and Python using key concepts and tricks to quickly mine and tidy raw data.

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Outlier Analysis

Quickly detecting outliers and analyzing them at the right time can help to increase revenue or avoid organisations losses. This course will bring both theoretical and practical knowledge about the types of outliers and how to deal with them using certain techniques/algorithms.