Maths for AI
6 Credits (ECTS)
Maths for AI
Get 70% back via Tax Credit
€683 refund on this module
Module Description
The module is divided into two parts:
The first part of the module will equip learners with a basic understanding of
- Set Theory
- Functions and Relations
- Permutations and Combinations
- Probability Theory
- Differentiation, and Integration, etc.
The second part of the module will equip learners with the basics of Linear Algebra and Matrices, and Linear Transformations etc.
It includes basics operations to be performed on matrices such as addition, subtraction, and multiplication, etc.;
Linear Independence and Dependence of Vectors; and Linear Transformations.
Entry Requirements
Candidates who apply for this course must possess one of the following:
- a Level 6 degree related to AI/Computer-Science/Mathematics/Electronics;
OR
- a Level 6 degree not related to AI/Computer Science/Mathematics/Electronics and a minimum of two years’ relevant experience;
OR
- a Level 5 diploma or higher diploma and five years’ of relevant work experience.
Target Audience
This course is targeted at:
- Industry professionals working in different domains, including Technology, Engineering, Science, IT, Finance, Accountancy, Management, Marketing, Insurance, Banking, Gaming, Healthcare, Medicine, Pharmaceutical, Human Resources, Psychology, Blockchain, Legal, Administration, Policy Making, Digital Art, Archaeology, Architecture, Education and other related areas.
- Recent graduates with degrees in Computer Science, Technology, Marketing, Finance, Economics, Accountancy, Management, HR, Law, Engineering, Science, Medicine, Psychology, Digital Art, Game Development, Archaeology, Architecture or Business.
- Mid-career-break professionals looking for opportunities to return to or change their career.
The target group may also be extended to positions such as that of wedding manager, transport manager, maintenance manager, operations manager, marketing manager, conference manager and even that of general manager.
Career Paths
The programme prepares for positions such as and not limited to:
- Compliance Supervisor/Manager/Officers
- Anti-Money Laundering Managers
- Money Laundering Reporting Officer and their deputies
- Law enforcement agencies and supervisory and regulatory authorities
- Managers with responsibilities for internal AML controls
- Risk Managers
- Director of Compliance
How you’ll be assessed
The course comprises:
- Evening classes for part-time courses.
- Classes held throughout the day for full-time courses.
- Guided learning, presentations, comprising synchronous online discussions, tutorials and/or videos.
- Self-study hours comprising research, reading and assignment work.
Assessment
Assessment is carried out via two mandatory components:
- Modular Assessment
- Summative Assessment
The programme includes different forms of assessment which allow for and promote students’ critical engagement. The formative and summative assessment tasks may include an in-class assignment and/or a home-based written assignment using diverse assessment tools which may take the form of online and in-class discussions, examinations, case studies, reports, proposals, essays, and presentations, etc., as applicable to the diverse modules.
Additional Info
Upon successful completion of this course, students will be eligible for a 70% refund of the cost through the ‘Get Qualified’ scheme.**
Due to the modular structure of the course, you may also opt to take individual modules as stand-alone. The entry requirements still apply.***
*Prices are applicable to students who reside in Malta at the time of applying.
**Terms and conditions apply.
Learning Outcomes
Competences:
At the end of the module/unit the learner will have acquired the responsibility and autonomy to:
- Rigorously assess the need for applications of Set Theory, Functions and Relations for Artificial Intelligence.
- Understand Permutations & Combinations and Probability Theory.
- Thoroughly evaluate the requirements of Differentiation and Integration.
- Proficiently use the matrices algebra such as matrix addition, subtraction, and multiplication, etc.
- Analyse the problems and challenges in Cayleg Hamilton Theorem.
Knowledge:
At the end of the module/unit the learner will have been exposed to the following:
- Discuss Set Theory, Relations, and Functions · Identify and discuss theory related to Discrete Mathematics.
- Compute and contrast implications/elements for Matrix Algebra and Linear Algebra · Explain Linear Transformation and Singular and Non- Regular Linear Mapping.
Key indicative topic areas cover:
- Set Theory, Relations, and Functions
- Discrete Mathematics
- Differentiation, Integration, and Introduction to Vectors
- Matrices & Determinants
- Matrix Algebra and Linear Algebra
- Linear Transformation
Skills :
At the end of the module/unit the learner will have acquired the following skills:
- Appropriately apply matrices determinants such as Eigen Values & Eigen Vectors, Diagonalization of a Matrix, etc.
- Understand and apply the fundamentals of Matrix Algebra and Linear Algebra such as groups, rings, and Vector Spaces.
- Apply the fundamentals of Linear Transformation.
- Apply Cayleg Hamilton Theorem to analyse the problems and challenges critically.
Judgment Skills and Critical Abilities:
The learner will be able to: ·
Master problem- solving skills by analysing case studies and working out the issues presented in real-life situations.
Module-Specific Communication Skills:
The learner will be able to:
- Communicates ideas, problems, and solutions to both specialist and non-specialist audiences using a range of techniques involving qualitative and quantitative information to sustain arguments.
Module-Specific Learner Skills:
The learner will be able to:
- Undertake independent and self-directed study through primary and secondary research.
Module-Specific Digital Skills and Competences:
The learner will be able to:
- Navigate through the online learning platform to find assignments, discussion boards, literature, tutorials etc.