MSc Artificial Intelligence (First Class Honours)
Builder of AI systems, educational technologies, and exploratory computational tools.
Driven by curiosity, I enjoy creating systems that help people learn, explore, visualize, and understand complex ideas.
Currently open to selected collaborations, consulting, mentoring, and applied AI education opportunities.
I work at the intersection of:
- AI systems
- applied computational research
- education
- visualization and exploratory analysis
- human-centered technology
My projects combine technical implementation, design, and learning experiences, often taking the form of AI systems, educational tools, scientific prototypes, interactive visualizations, and research-oriented computational frameworks.
Areas of interest include scientific exploration, anomaly analysis, decision-support systems, bioacoustics, AI-assisted learning, and exploratory AI architectures operating under uncertainty.
Projects are typically developed as reproducible notebooks, modular pipelines, technical reports, educational artifacts, and research prototypes.
Curiosity
↓
Learning ↔ AI Systems ↔ Research
↓
Visualization & Understanding
Languages & Development
Python • SQL • Jupyter • Git • GitHub
AI & Machine Learning
LLM Systems • Deep Learning • Computer Vision
Agentic Workflows • Human-in-the-Loop AI
Data & Analytics
Tableau • Power BI • Data Visualization
Exploratory Analysis • KPI Design • Decision Support
Research & Exploration
Signal Analysis • Computational Research
Scientific Computing • Anomaly Detection
Education & Communication
Mentoring • Curriculum Design
Educational Technology • Technical Writing
My work currently spans four complementary areas:
Agentic workflows, decision-support systems, orchestration pipelines, LLM applications, and human-in-the-loop architectures.
Exploratory computational frameworks, scientific investigation, anomaly analysis, and research-oriented prototype development.
AI and data science mentoring, educational technologies, curriculum design, and project-based learning systems.
Data storytelling, dashboard development, technology watch (veille), exploratory analysis, KPI design, and decision-support visualization.
In addition to AI systems and computational research, I develop analytical dashboards and visualization systems designed to support exploration, prioritization, communication, and decision-making.
Recent projects include technology watch dashboards, exploratory scientific visualizations, and business-oriented decision-support tools built with Tableau and related analytics platforms.
Interactive Dashboard: View on Tableau Public
This project demonstrates the end-to-end workflow behind analytical dashboard development:
- data preparation and structuring
- KPI design and business metrics
- exploratory and comparative visualization
- dashboard composition and storytelling
- executive-oriented decision support
The objective is not merely to display data, but to transform information into actionable insight through clear visual communication.
| Project | Focus |
|---|---|
| industry-integrated-ai-systems-synthesis | integrated AI decision-support architectures |
| opsflow.ai | modular operational routing and orchestration |
| leadflow-ai | AI-assisted qualification and activation pipelines |
| bioacoustic-topology | birdsong manifold dynamics and acoustic representation |
| latent-physiological-topology | exploratory physiological signal systems |
| design-of-agentic-workflows | governed multi-agent workflow architectures |
Alongside technical development, I mentor learners in AI, data, and software projects.
As an OpenClassrooms mentor, I help students develop technical skills, build portfolio projects, and communicate their work effectively.
My teaching approach emphasizes systems thinking, practical problem-solving, and real-world project construction.
Additional specialization includes deep learning, reinforcement learning, computer vision, data science, and AI for healthcare.
Ongoing projects are progressively documented through:
- technical reports
- GitHub repositories
- Zenodo publications
- educational write-ups
- exploratory computational notebooks
One of the most formative stages of my AI journey was the completion of the Self-Driving Car Engineer Nanodegree.
The recovered project portfolio covers the complete autonomous driving stack:
- computer vision
- deep learning
- sensor fusion
- localization
- path planning
- vehicle control
🚗 Portfolio Hub:
https://github.com/MinervaRose/Self-Driving-Car-Engineer-Nanodegree-Projects
Representative projects include:
- Advanced Lane Finding
- Traffic Sign Classification
- Behavioral Cloning
- Extended Kalman Filter Sensor Fusion
- Kidnapped Vehicle Localization
- Highway Path Planning
- PID Vehicle Control
Current projects build upon a longer learning journey spanning education, research, applied AI, and systems design.
Selected milestones include:
| Milestone | Year |
|---|---|
| Deep Reinforcement Learning Nanodegree (Facebook AI Scholarship) | 2019 |
| Deep Learning & PyTorch Scholarship Programs | 2018–2019 |
| Android Basics Nanodegree (Google Scholarship) | 2018 |
| MSc Artificial Intelligence (First Class Honours) | 2026 |
A three-project reinforcement learning portfolio covering:
- Deep Q-Networks (DQN)
- Continuous Control with DDPG
- Multi-Agent Reinforcement Learning (MADDPG)
🔗 Repository: https://github.com/MinervaRose/Deep-Reinforcement-Learning-Nanodegree-Projects
This work marked an early transition from traditional programming toward autonomous agents, decision systems, and AI architectures.
More recent projects build upon many of the concepts first explored there.
Following selection for the Facebook AI & PyTorch Scholarship Challenge, I was awarded a full scholarship to the Udacity Deep Learning Nanodegree and graduated in 2019.
The resulting project portfolio explores several major deep learning paradigms, including neural networks, computer vision, natural language processing, generative adversarial networks (GANs), and model deployment with Amazon SageMaker.
🔗 Repository: https://github.com/MinervaRose/Deep-Learning-Nanodegree-Projects
This work represents an early milestone in my transition from traditional programming and data analysis toward modern AI systems and machine learning engineering.
On November 6, 2017, I received a life-changing email. I was offered a seat in the Google Developer Scholarship Challenge hosted through Udacity.
At the time, I had no background in computer science and no experience developing software professionally. What began as curiosity quickly became a passion for building technology and solving problems through code.
🔗 Repository: https://github.com/MinervaRose/Deep-Learning-Nanodegree-Projects