Artificial Intelligence

Artificial intelligence is part of the fourth industrial revolution with major advances for quality of life, work and decisions making for most industry areas including health, logistics, smart cities and travel, retail, manufacturing, energy, smart grid, environmental impacts, and much more.

Introduction

Artificial intelligence is part of the fourth industrial revolution with major advances for quality of life, work and decisions making for most industry areas including health, logistics, smart cities and travel, retail, manufacturing, energy, smart grid, environmental impacts, and much more. It is now major growth area within computing and artificial intelligence is estimated to grow considerably with autonomous vehicles, machine learning, and big data driving massive change. This exciting new area works across all areas of industry including robotics, linking of sensor driven technologies, visualising mass data from numerous sensors and large scale data sources in real time and ability to adapt and change outcomes using live data to direct logistical issues such as traffic for example. Machine to machine learning is here to stay and advancing the mass communications revolution which has taken shape during the last decade to new levels of precision, connectivity, community input and instant knowledge from source to end user or need.

Course Modules

Semester 1 - Compulsory
• Foundations in AI
• Machine Learning
• Evaluation of AI Sytsems
• Engineering of AI Systems

Semester 2 - Compulsory
• Data Mining and Visualisation
• Natural Language Generation
• Software Agents and Multi Agent Systems
• Knowledge Representations and Reasoning

Semester 3
• Individual projects

Duration

1 year, Full Time

Module 1

Foundations of AI
This module presents the fundamental techniques of Artificial Intelligence, used in system such as Google Maps, Siri, as well as industrial automation systems, and which are core to emerging products such as self-driving vehicles. This course will equip the student to understand how such AI technologies operate, their implementation details, and how to use them effectively. This course therefore provides the building blocks necessary for understanding and using AI techniques and methodologies.

Module 2

Machine Learning
This module presents the fundamental as well as the most popular Machine Learning theories and algorithms, used in a wide range of applications such as face detection, anomaly detection etc. This course provides the building blocks for understanding and using Machine Learning techniques and methodologies and prepares students to work in data science and general AI systems.

Module 3

Evaluation of AI Systems
This course will provide students AI with knowledge of core evaluation concepts, approaches, tools, techniques and technologies.

Module 4

Engineering AI Systems
This course will provide students AI with skills to help them engineer AI systems, equipping them with solid programming skills, and using state-of-the-practice languages, tools and technologies.

Module 5

Data Mining and Visualization
This course will provide students with knowledge of core data mining and visualization approaches, tools, techniques and technologies.

Module 6

Natural Language Generation
Artificial intelligence has helped solve complex practical problems such as driving a car, translating text from/to different languages, understanding and answering questions, and playing games such as chess and Go. This course will provide students with knowledge of core natural language generation concepts, approaches, tools, techniques and technologies.

Module 7

Software Agents and Multi - Agent Systems
The global systems market is expected to be valued at over 13 billion by 2025, involving both software systems and robots. Such autonomous systems act to achieve goals with no human intervention, and are already found in self-driving cars, space probes and systems such as Amazon's Echo. This course provides the student with a solid grounding in the theory and tools which underpin such systems, teaching them both how to develop such systems, and use them effectively as part of a larger product.

Module 8

Knowledge Representations and Reasoning
Recent advances in AI have changed the perception of what machines can do, from on-line search to answering questions. An underlying feature of many AI systems concern how knowledge is acquired, represented, and reasoned with. Companies such as Google, IBM, and Facebook have been developing sophisticated tools for knowledge representation and reasoning. This module provides the theory and practice of knowledge representation and reasoning, also presenting cutting-edge technologies, libraries and tools. At the end of the course students will be able to design, implement and evaluate knowledge-intensive AI systems.

Module 9

Project in Artificial Intelligence
This course will provide students AI programme with the opportunity to develop their own AI project. Typical projects include extending, improving or adapting existing AI theories or techniques to solve different problems, comparing competing techniques or tools to solve a particular problem, and so on. Students will improve their problem-solving and communication skills, as well as broaden, deepen and consolidate knowledge obtained in other components of the degree.

Fees: 1750 Euros

ALUMNI SPOTLIGHT

"We choose to study at TIMI because first of all, the environment is very conducive and suitable for both teaching and learning. Secondly, they have very good teachers who are very accommodating. They take their time to explain courses and also answer all our necessary questions. Lastly, the small number of students in each class allow us to be able to interact and understand more".