Learning
Topics and skills from coursework, research, and hands-on builds — newest first. Certificate scans live on Certificates & Awards.
AWS AI Practitioner
Mar–Apr 2026 · Udacity
- AWS AI/ML services and cloud-native patterns for applied AI workloads
- Hands-on implementations connecting ML theory to production-style pipelines on AWS
Credential URL: https://www.udacity.com/certificate/e/d318d16e-3196-11f1-a9c4-4b2f4c389ac0
Deep Learning Specialization
Mar–Apr 2026 · DeepLearning.AI (Coursera)
- Neural Networks and Deep Learning
- Improving Deep Neural Networks: hyperparameter tuning, regularization, and optimization
- Structuring Machine Learning Projects
- Convolutional Neural Networks
- Sequence Models
- Architectures: CNNs, RNNs, LSTMs, and Transformers
- Training strategies: dropout, BatchNorm, Xavier/He initialization
- Built models in Python and TensorFlow for speech recognition, music synthesis, chatbots, machine translation, and NLP
Credential URL: https://www.coursera.org/account/accomplishments/specialization/certificate/JL3S1X3P207U
Research & user-centered AI
2026 · KDU Global
- Quantitative study of how users perceive AI recommendations (ResQue framework on Netflix and YouTube)
- Survey design, Likert scaling, and connecting perceived quality to trust and transparency
- Why explainable recommendation UX matters as much as offline accuracy
MGM Assist — GenAI hackathon build
Mar 2026 · GenAI Academy World Wide Vibes
- Bright Data for scheduled scraping and keeping civic/economic feeds fresh
- Firebase (Realtime Database & Firestore) for live dashboard data
- Vibe coding — rapid AI-assisted iteration, sharpened under hackathon pressure
- Claude API integration for the city assistant and natural-language Q&A on civic data
- Full-stack delivery: React, Node/Express, Mapbox, and Vercel deployment in a two-week sprint
Machine Learning Specialization
Dec 2025–Mar 2026 · Stanford Online / Coursera
- Supervised Machine Learning: Regression and Classification
- Advanced Learning Algorithms
- Unsupervised Learning, Recommenders, Reinforcement Learning
- Supervised learning: linear regression, logistic regression, neural networks, and decision trees
- Unsupervised learning: clustering and anomaly detection
- Recommender systems and reinforcement learning
- Best practices for building machine learning models and applying techniques to real-world problems
Credential URL: https://www.coursera.org/account/accomplishments/specialization/certificate/AGC3UP0QYQH0