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Jordan
- Rate R654
- Response 1h

R654/h
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- Computer Science
- Software
- Machine learning
Offering Elite Python, Data Science and Machine Learning tuition. Chilled Teaching approach
- Computer Science
- Software
- Machine learning
Lesson location
About Jordan
I’m Jordan Clive, Lead Deep Learning Scientist / Engineer at Chattermill AI in London. Day-to-day I design, fine-tune and deploy large-language-model systems used by global brands like Uber and Amazon.
I’m also passionate about open-source and the frontier, as a core contributor to LAION’s OpenAssistant—the original open-source alternative to ChatGPT—and have peer-reviewed papers at EMNLP, ICLR, NAACL and COLING. Academically, I earned a Distinction MSc in Computing (Machine Learning & AI) from Imperial College London with an average of 92% and won a prize for first-author work with Google DeepMind. I also review for top NLP conferences, including ACL 2025 and EMNLP 2023.
My open-source footprint spans Hugging Face Transformers, MMTEB, and numerous public LLM checkpoints downloaded thousands of times. Alongside frontier research, I still enjoy the “classics”: scikit-learn, XGBoost, time-series modelling and solid software engineering. That mix of bleeding-edge and traditional data science lets me meet students exactly where they are—whether they’re writing a first Python loop or scaling a 100B-parameter model on H100s.
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
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Kids
- English
Languages in which the lesson is available :
English
Bring your problem—homework, project, or study topic—and we’ll solve it together. I combine front-line industry experience (shipping RAG and custom LLMs for clients like Uber & Amazon) with the empathy of someone who started in a data-science boot camp. I understand both steep learning curves and real-world constraints.
⸻ How sessions run
• Tailored start – I gauge your current knowledge and learning style, then sketch a mini-curriculum that balances motivation and challenge.
• Project-based – We build something tangible each session (e.g. an image generator or a Streamlit dashboard), so you leave with runnable code and next-step notes.
• Intuition first – Clear explanations and sketches come before equations or APIs.
⸻ Topics covered
• Core data science – Pandas, NumPy, visualisation, XGBoost / LightGBM, supervised & unsupervised learning (PCA, K-Means), Bayesian inference, Streamlit / Gradio.
• Advanced ML & AI – Neural networks, Transformers, Hugging Face, RAG pipelines, agentic AI, LoRA fine-tuning, PyTorch, vLLM, GPU workflows, production tips (Docker, “push-to-prod”).
• Maths support – Linear algebra, optimisation, probabilistic inference.
⸻ Who it suits
From beginners or young students to working professionals. Message me for more details about me or your first project or question—then let’s get building.
Recommendations
Recommendations are written by the tutor's friends, family, and acquaintances.
Thanks to Jordan’s clear explanations and project-based approach, I landed my first Data Scientist role—and later pivoted into Machine Learning! He makes complex topics feel approachable and gave me the confidence to build real-world projects.
See more recommendations
Rates
Rate
- R654
Package rates
- 5h: R3270
- 10h: R6540
online
- R654/h
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