Level 7 Diploma in Machine Learning and Deep Learning
The Level 7 Diploma in Machine Learning and Deep Learning offered by OXQUAL develops advanced competence in mathematical foundations, machine-learning algorithms, deep-learning architectures, optimisation, cloud-based training, responsible AI and applied AI project development.
About this qualification
The Level 7 Diploma in Machine Learning and Deep Learning offered by OXQUAL develops advanced competence in mathematical foundations, machine-learning algorithms, deep-learning architectures, optimisation, cloud-based training, responsible AI and applied AI project development.
Career-focused
Develop relevant skills and knowledge that can support your next professional step.
What you'll cover
Key topics covered in this OXQUAL programme include:
- Advanced Machine Learning
- Deep Learning
- Linear Algebra
- Calculus for Machine Learning
- Probability
- Statistics
- Optimisation Methods
- Regression
- Classification
- Ensemble Methods
- Clustering
- Dimensionality Reduction
- Anomaly Detection
- Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- LSTM Networks
- GANs
- Transformers
- Hyperparameter Tuning
- Gradient Descent
- Regularisation
- Cloud ML Platforms
- Scalable Training
- Responsible AI
- Bias and Fairness
- NLP Applications
- Computer Vision
- Recommendation Systems
- ML/DL Capstone Project
Who it's designed for
This OXQUAL programme is suitable for:
- Machine-Learning Professionals
- AI Engineers
- Data Scientists
- Postgraduate Computing or Mathematics Learners
- Professionals developing advanced AI expertise
What you'll gain
Successful completion of this OXQUAL programme can help learners to:
- Develop advanced ML and deep-learning competence.
- Strengthen mathematical foundations.
- Improve neural-network design knowledge.
- Develop model-optimisation capability.
- Strengthen cloud-based training awareness.
- Improve responsible-AI practices.
How this qualification is assessed
The assessment pattern for this OXQUAL programme is outlined below.
- Assessment Type: Capstone project, written examination and portfolio review.
- Format: Applied case studies, multiple-choice questions, project defence and oral presentation.
- Total Questions: 100 theory questions plus project submission and portfolio defence.
- Passing Score: 70%.
- Duration: 9–12 months (1,200–1,400 hours total).
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