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Liza
- Rate R218
- Response 1h
R218/h
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- Basic computer skills
- Computer Science
- Computer networks
- IT security
- Machine learning
Currently a third year PhD student in Computing at University of Lancashire.
- Basic computer skills
- Computer Science
- Computer networks
- IT security
- Machine learning
Lesson location
About Liza
I'm a third-year PhD researcher in Cybersecurity and Machine Learning at the University of Lancashire, focused on adaptive phishing detection using deep reinforcement learning and generative adversarial networks. My research bridges academic theory with real-world security challenges, and I'm passionate about sharing this knowledge through practical, mentorship-driven tutoring.
My background combines advanced expertise in deep learning architectures (transformers, CNNs, GANs, reinforcement learning agents), cybersecurity threat modelling, and production-level Python development. I regularly work with modern ML frameworks including PyTorch, TensorFlow, Hugging Face, and scikit-learn, and I'm experienced in GPU-accelerated model training, experimental design, and rigorous evaluation methodologies.
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About the lesson
- Primary
- Secondary
- Matric/GCSE
- +14
levels :
Primary
Secondary
Matric/GCSE
AS Level
A Level
BTech
Adult education
Undergraduate
Masters
Diploma
Doctorate
MBA
Beginner
Intermediate
Advanced
Professional
Kids
- English
Languages in which the lesson is available :
English
I am a PhD researcher in Cybersecurity and Machine Learning at the University of Lancashire, specialising in adaptive phishing detection using deep learning and reinforcement learning. My teaching combines academic rigour with practical, hands-on experience building real production-level ML models for security applications.
My Teaching Approach:
I teach through iterative project-based learning, we build working systems together, not just study theory. Lessons blend conceptual foundations (neural networks, deep learning architectures, adversarial training) with applied Python development using industry-standard frameworks: PyTorch, TensorFlow, Hugging Face transformers, and scikit-learn.
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Rates
Rate
- R218
Package rates
- 5h: R1090
- 10h: R2180
online
- R218/h
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