FTI6001 Managing and Leading Enterprise Artificial Intelligence Projects
About This Course
This module trains the student on project management and the background knowhow to lead corporate AI projects, which are fundamentally different from standard IT projects, as AI systems tend to be both highly diverse and complex.
Having completed this module, the student will be able to demonstrate knowledge and understanding of the following, and be able to manage and guide AI projects in a project management or enterprise innovation role:
1. The architecture, applications and operations of popular AI Deep Learning systems and how they would benefit enterprises via enhanced productivity in corporate decision making, process automation and problem solving. Overview of software development using AI frameworks.
2. Overview of Natural Language Processing (NLP) AI systems and key applications.
3. Overview of AI vision processing systems for object recognition, segmentation, pose, biometrics and action recognition.
4. Overview of AI Ethics, governance, AI cyber security vulnerabilities such as Adversarial Attacks, data security, privacy and common implementation weaknesses. Understand privacy and cyber security best practices for AIOps and the need for ethics, transparency and fairness for Trustworthy AI.
5. Overview of AI Project Management and leadership roles.
6. State-of-the-art in AI, future trends and developments; new pending problems that can be solved with better algorithms and the cost reduction expected as the technology advances.
Additionally, students will have mastered the skills to be able to:
7. Analyse the feasibility of user requirements, data input requirements, AI project life cycle and deployment suitability.
What You'll Learn
Having completed this module, the student will be able to demonstrate knowledge and understanding of the following, and be able to manage and guide AI projects in a project management or enterprise innovation role:
1. The architecture, applications and operations of popular AI Deep Learning systems and how they would benefit enterprises via enhanced productivity in corporate decision making, process automation and problem solving. Overview of software development using AI frameworks.
2. Overview of Natural Language Processing (NLP) AI systems and key applications.
3. Overview of AI vision processing systems for object recognition, segmentation, pose, biometrics and action recognition.
4. Overview of AI Ethics, governance, AI cyber security vulnerabilities such as Adversarial Attacks, data security, privacy and common implementation weaknesses. Understand privacy and cyber security best practices for AIOps and the need for ethics, transparency and fairness for Trustworthy AI.
5. Overview of AI Project Management and leadership roles.
6. State-of-the-art in AI, future trends and developments; new pending problems that can be solved with better algorithms and the cost reduction expected as the technology advances.
Additionally, students will have mastered the skills to be able to:
7. Analyse the feasibility of user requirements, data input requirements, AI project life cycle and deployment suitability.
Entry Requirements
Bachelor degree in Science and Engineering, and preferably have done IT projects and have two years of project management background.