The objectives of this course are:
To equip students with techniques necessary to mine different types of data.
To use different models of computation to mine data, i.e., MapReduce, streams and online algorithms, single machine in-memory.
To learn and use different data mining tools to analyze big data.
The objectives of this course are:
How to use various data structures while developing in a particular programming language as well as how to implement some of the most common algorithms used with such data structures.
Define and explain advanced data types such as stacks, queues, lists, trees, and graphs; write programs using them.
Define, discuss, and explain the main algorithms and techniques (such as sorting, searching, hashing, traversal, and recursion) and write programs using these algorithms.
The objectives of this course are:
Generate probabilities of events or sequences of real-life events under given conditions
Solve probabilistic and statistical problems related to probability distributions.
Generate representations of distributions in real-life scenarios and compute related probabilities.
Solve compounded distributions’ problems.
Analyse data using descriptive statistics.
Apply statistical Inference and regression methods to real-world examples.
This is a project-driven course that aims to give students practical skills in a selected Computer Science area including:
Mobile application development.
Embedded system development.
The course aims to introduce students to:
The need for computer security.
Threats faced by computers in the connected digital world.
Techniques that are used to protect computers against various threats.