Learning Outcomes:

Topics:

• Appreciate the difference between AI and its subfields, e.g. Machine Learning, 4-bit deep learning and related interdisciplinary research areas such as robotics.

• How AI leverages other disciplines, e.g. computer science, mathematics, psychology, software engineering and linguistics. Recognising traditional problems (goals) of AI, Such as reasoning, planning, learning, natural language processing and perception.

• Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), Artificial Superintelligence (ASI).

• Business and e-commerce, e.g., chatbots, visual searches, intelligent virtual assistants.

• Engineering, e.g., Computer Aided Design (CAD) and automation in factories.

• Healthcare, e.g., care of the elderly, heartbeat analysis, computer-aided interpretation of medical images, and drug discovery.

• Understanding Machine Learning algorithms and processes, including dataset preparation.

• Linear regression, logistic regression, decision tree, Support Vector Machine (SVM), Naïve Bayes, K-Nearest Neighbor(s) (KNN), k-means, gradient boosting.

• Options include but are not limited to TensorFlow, Torch, Theano, Azure Machine Learning, 4-bit deep learning, MathWorks, MATLAB (plus Simulink), CNTK (Computational Network Toolkit), Deeplearning4j, Scikit-Learn, Swift AI IBM for Watson, Keras, PyBrain, Google ML kit, Caffe, H20: open-source AI platform.

• Tools and required relationships for testing, e.g., accurate and clear documentation, the role of static testing and review in early defect detection, the need to follow specific industry standards (e.g. GDPR, health informatics, safety-critical) and the psychological mindset of the tester-developer relationship.

• Statistical methods, computational intelligence, and traditional symbolic AI. Data collection, data sources, and assessment of data reliability to modify AI-based system.

• Criteria for AI-based application selection, e.g., any application software, system or agent that exhibits intelligence as part of its problem-solving approach, e.g. open-source projects from Google and GitHub.

• The environmental footprint of AI, e.g., the carbon impact of AI. AI bias and the ethical dilemma, e.g., the potential to widen socio-economic inequality, AI-powered hiring processes (employment opportunities), access to skilling, health/life extension, and algorithmic quantitative trading.

Indicative reading list 

• Deisenroth, M. P., Faisal, A. A., & Ong, C. S. (2020). Mathematics for Machine Learning. Cambridge University Press.

• Russell, S. J., & Norvig, P. (2022). Artificial Intelligence: A modern approach. Pearson.

Entry requirements

To enroll The Master Award, the learner must possess:

• Graduated with a Bachelor’s degree from an accredited university or achieved a Level 6 Diploma according to the European Qualifications;
• For a degree from non-recognized universities; The learner should have followed Accreditation of Prior Experiential Learning for Qualifications (APEL.Q) policy of MI Swiss and/or University Partners;
• Learners must be over 21 years old.

English requirements

If a learner is not from a predominantly English-speaking country, proof of English language proficiency must be provided.

• Common European Framework of Reference (CEFR) level B2 or equivalent;
• Or A minimum TOEFL score of 101 or IELTS 5.5; Reading and Writing must be at 5.5 or equivalent.

The UKeU reserves the highest decision-making authority regarding admissions and may accept or reject applicants following a thorough review of each applicant’s profile, ensuring that only those capable of benefiting from the course are admitted. Qualifications from diploma mills or fake universities/institutions will not be accepted by UKeU and/or Partner University.

After graduating with Master Award, learners receive all certified documents from the UKeU.

Certified Documents:

• e-Certificate from the UK eUni Worldwide (UKeU);
• Hard copy certificate from UK eUni Worldwide (UKeU) (Optional);
• Accreditation of Prior Experiential Learning for Qualifications (APEL.Q) certified from UKeU for credit and tuition fee transfer.

Because the course is accredited and recognized, learners can easily use their qualifications in the workplace and enjoy many opportunities for career advancement. In addition, if you wish to pursue a degree from UKeU and/or a Partner University, all credits and 50% paid tuition fees can be transferred.

The UKeU’ Master Award means:

UKeU Master Award is the award at the master level and is equivalent to:

• Level 7 certificate of Regulated Qualifications Framework (RQF) of UK
• Level 10 certificate of Scottish Credit and Qualifications Framework (SCQF)
• Level 7 certificate of Credit and Qualifications Framework (CQFW)
• Level 7 certificate of European Qualifications Framework (EQF)
• Level 9 certificates of the Australian Qualifications Framework (AQF)
• Level 7 certificate of ASEAN Qualifications Reference Framework (AQRF)
• Level 9 certificate of the African Continental Qualifications Framework (ACQF)

Learners can transfer all credits and 50% of their tuition fees when enrolling in UKeU and/or Partner University academic programs if they wish to pursue an academic degree.

Credits transfer:

Learners can transfer 20 credits from the Master Award course when participating in the Master program. Please see the credit transfer policy HERE.

Tuition fee transfer:

When enrolling in the Master program, graduates from the Master Award will receive a fee reduction equal to 50% of the tuition fees paid for the Master Award. Please refer to the tuition fee transfer policy HERE.

The UKeU Micro Degree course allows learners to transfer credits and 50% of their tuition fees toward full degree programs offered by UKeU and/or Partner University. UKeU reserves the right to limit admissions once enrollment exceeds the set quotas.

Apply Policy:

• To participate in the UKeU Micro Degree course, learners need to meet the entry criteria corresponding to each level. Please see the “Entry” tab for more details.
• UKeU will not accept applicants whose entry qualifications are from fake universities or institutions that are not accredited.
• For Master Award courses, if an entry bachelor is unavailable, learners must demonstrate a minimum of 5 years of work experience in the relevant field. Please note that a bachelor’s degree is required for the Master’s program at UKeU and Partner University so that you could study Master Award but could not move to the Master’s program of UKeU and/or Partner University.
• English is not a mandatory entry requirement for Micro Degree course, but candidates need to ensure that English is used in reading documents, listening to lectures, and doing assignments. Applicants should note that English is a mandatory requirement when switching to an academic program at UKeU and Partner University.

Apply Process:

• Step 1: To request a consultation for a course that best suits your needs, please email support@ukeu.uk. Our admissions department will contact you to guide you through the required documentation and the next steps in the application process.
• Step 2: Once your application documents are approved and the application fee is paid, UKeU will issue a Letter of Acceptance (LOA). You will then follow the provided instructions, including payment of the tuition fee.
• Step 3: After the tuition fee is paid, UKeU will issue a confirmation letter, provide your login details for the e-learning system, and send you all relevant documents.
• At this point, you have officially become a UKeU student. Welcome, and enjoy your learning journey!

The UKeU Micro Degree course is fully online, allowing you to study anytime and anywhere. You also have the option to attend live classes with UKeU. Final exams will be uploaded to the system and assessed by the UKeU academic board. Learners are required to submit assignments on time; failure to do so will require payment of a resit fee (with up to two attempts allowed). Continued non-compliance on a third occasion will result in being considered as having discontinued the course, and tuition fees will not be refunded.