Fong Jian Zhong · Johor, Malaysia
Diploma in Computer Science student at TAR UMT, certified in AI by IBM, Cisco, and Google Cloud. Available for internship 4 Jan – 23 May 2027 (university-confirmed Industrial Training). The Sudoku solver on the right is my coursework algorithm, running live — hit Solve.
From my Fundamentals of AI group assignment — A* with an MRV heuristic.
Verified on Credly
Skills verified across these badges include machine learning, deep learning, neural networks, NLP, computer vision, chatbots, AI ethics, prompt engineering, and Gemini APIs.
See all my credentials:
Credly ·
Google Skills ·
Google for Education ·
Cisco Learning Network
Selected work
An AI-guided learning project: end-to-end reinforcement-learning fine-tuning of Llama 3.2 3B Instruct with TRL's GRPOTrainer. I applied 4-bit NF4 quantization with LoRA adapters (r=16) to fit training in 16 GB VRAM, designed a rule-based reward function over a 60-prompt custom dataset, tracked runs with W&B, and published the adapter to Hugging Face with an honest model card.
View on Hugging Face →Group leader for my Fundamentals of AI assignment: designed the project structure, split the work into algorithm components, and built the Informed Search (A*) solver myself — heap-based best-first search with an MRV heuristic — while guiding teammates on DFS and Simulated Annealing.
Try the live demo above ↑A vibe-coding side project: an Android floating chat assistant that detects the current YouTube video's context and streams answers from the Gemini API.
View on GitHub →Toolbox
Study
Best grades: Calculus & Algebra (A+), Probability & Statistics (A), Discrete Mathematics (A), Software Development Fundamentals (A). Currently studying Fundamentals of AI, Data Structures & Algorithms, C++, and Mobile App Development.
Industrial Training: 4 Jan – 23 May 2027