learning_goals

# Learning Goals

## Collective

**Our shared goals for these exercises are**:

Strengthen our collaboration and communication skills in a technical context by
working through coding challenges together and exchanging ideas openly.

Develop a consistent and professional workflow for writing, structuring, reviewing,
 and improving code using shared standards and GitHub best practices.

Write clear, readable, and well-documented solutions, including modular functions,
meaningful commit messages, polished notebooks, and accessible READMEs.

Support each other’s learning through constructive feedback, code reviews,
 and active knowledge sharing—so everyone learns from everyone.

Build confidence and creativity in how we approach problems as a team, experimenting
with new techniques and tackling challenges with curiosity.

Deepen our data-science foundations through weekly practice with EDA, visualization,
 and fundamental statistics applied to real datasets.

Create an inclusive, supportive learning environment where all voices are welcomed,
questions are encouraged, and leadership is shared.

Communicate insights clearly by translating technical results into simple explanations,
 one-pagers, and concise presentations.

Promote reproducible, future-friendly work through automation, versioning,
structured pipelines, and documentation that helps future collaborators.

## Individual Learning goal

### Kervens Louis

Build consistency and personal discipline by dedicating regular time to research,
review, and independent practice.

Apply personal agency tools to set clear intentions, monitor progress,
and stay accountable throughout the project.

Strengthen collaborative coding skills by mastering GitHub workflows
(branching, pull requests, conflict resolution) and writing meaningful commit messages.

Develop clear technical communication by maintaining well-commented scripts,
structured notebooks, and visual explanations of decisions.

Create reproducible workflows for data loading, cleaning, and modeling through
modularized code and versioned notebooks.

Apply data science to real-world questions—especially related to education, policy,
or social outcomes, and document insights for both technical and non-technical audiences.

### Pierre Kenley MERVIL

• Improve my collaboration skills by working remotely in a team
and communicating on a daily or biweekly basis.
• Using my programming,python, AI and ML skills to tackle real
world problems that my country are currently facing.
• Improve my communication skills by developing storytelling and communication strategy
• Master PowerBI by creating Dashboard to sustain story and enhance comprehension
• Make progress in my career as a backend developer and python developer.
• Apply my Data science knowledge in the sustainable tourism sector.

### Cliforde EXAEL    "Cliforde"

🌍 General Learning Goals

Understand how data-driven technology can preserve cultural heritage and influence
global narratives.

Apply interdisciplinary methods combining data science, geography, history, and
UX design.

Learn to collect, clean, structure, and visualize real-world datasets.

Develop accessible, bilingual digital tools that promote sustainable tourism and
education.

Explore how digital storytelling enhances cultural appreciation.

💡 Personal Learning Goals

Strengthen full-cycle project management skills (data → visualization → prototype).

Gain hands-on experience with APIs (OpenStreetMap, Google Maps, Wikidata).

Develop user-centered web design and multimedia integration skills.

Learn to communicate insights clearly using data and visualization.

Build confidence designing meaningful, socially impactful digital experiences.