Short Courses
Short Course in Cyber Security
Overview
The Short Course in Cyber Security will provide participants with knowledge of the fundamental principles, underlying theory and practical skills employed in securing information and networks.
It will allow learners to assess the security risks inherent in computer networks and the technologies that can be employed to counter such risks. It covers cryptographic algorithms, including practical examples of breaking codes. As a practical course that teaches the principles of network security and cryptography, our Short Course in Cyber Security allows learners to acquire and demonstrate their practical, work ready skills in this field.
Topic Covers:
- Public Key Infrastructure (PKI), Cryptographic Algorithm
- Web Security and Email Security
- Data Protection
- Vulnerability Assessment
- Authentication and Access Control
- Firewall
- VPN
- Remote Access
- Wireless Security
- Suggested Hours: 40
Entry Requirements
As a minimum, participants should have:
- Good IT knowledge
- Good understanding of English
Short Course in Data Science
Overview
Data science is the study of extracting meaningful insights from data. It is a forward-looking approach with the focus on analyzing the past or current data and predicting the future outcomes with the aim of making informed decisions. Regardless of industry or size, organisations that wish to remain competitive in the age of big data need to efficiently develop and implement data science capabilities.
The Short Courses in Data Science have four levels:
- Short Course in Data Science: An Introduction
- Short Course in Data Science: Intermediate
- Short Course in Data Science: Advanced
- Short Course in Data Science: Expert
Short Course in Data Science: An Introduction
Who should attend?
- Individuals who are just embarking on the data science journey either as a “STEM” fresh graduate or those looking to upskill into data science.
- Knowledge of either computer science, programming or strong mathematics background is essential.
Total Hours: 80 Hours
Topics Covered:
- Computer Instructions and Data
- Collecting and Analysing Data
- Solve problems with Algorithms
- Structure, Manipulate and Represent Data
- Developing and Testing Program Code
- Database with SQL
- Inferential Statistics
- Data Visualisation
- Data Science project lifecycle
Short Course in Data Science : Intermediate
Who should attend?
- The intermediate course is designed to provide individuals who have 2-3 years working experience in data analytics or analysis discipline such as finance, business planning, marketing or sales who are looking to develop an understanding of data science.
- Basic practical knowledge of computer science, programming or strong mathematics background is a must.
- The individual must have attended the Short Course in Data Science : An Introduction or other associated data science course.
Total Hours: 80 Hours
Topics Covered:
- Data Scientist Skillsets
- Statistical Methods
- Python
- Database Essential
- Text Mining
Short Course in Data Science : Advanced
Who should attend?
- Analytics practitioners who have more than 3 years experience operating in a data analytics or analysis team looking to increase their knowledge in data science.
- They must have attended the Short Course in Data Science : Intermediate or other associated data science course.
Total Hours: 120 Hours
Topics Covered:
- Extract, Transform and Load Data
- Linear Transformation
- Matrix Multiplication
- Data Analysis with R
- Visualisation using R
- Machine Learning
- Data Visualisation and Storytelling
Short Course in Data Science : Expert
Who should attend?
- Data Science team leaders looking to step into senior management role
- Must have attended the Short Course in Data Science : Advanced or other associated data science course.
Total Hours: 120 Hours
Topics Covered:
- Optimisation
- Linear programming
- Integer programming
- Big Data Analytics
- Predictive Analytics
- Regression Models
- Data Mining
- Decision Trees