FLi Data Science Fellowship
In an era characterized by the abundance of data available at our fingertips, there’s never been a better time for young, inquisitive minds to dive into the world of data science. Our Data Science Fellowship Program for high school students not only offers an exciting opportunity to explore data analysis using the R programming language but also emphasizes that the digital age has made the vast world of data an open book for everyone to explore. We recognize that access to resources can be a challenge, especially for low-income students, which is why we’re committed to breaking down barriers and offering a level playing field.
With the wealth of data available online, there’s no reason why any student, regardless of their background, shouldn’t start asking their own questions, seeking answers, and making a real impact. Through this program, we aim to empower these students to harness the power of data to address pressing questions, opening doors to exciting educational and career opportunities while fostering a sense of agency and curiosity that will serve them well in the data-driven future. Join us in equipping the next generation with the tools and confidence to shape their own data-driven narratives, as we believe that every young mind has the potential to be a data scientist and a changemaker.
Objective
The FLi Sci Data Science Fellowship is to empower low-income high school students with the skills and experiences foundational to become researchers. Throughout the program, participants will undergo comprehensive training in coding, with a focus on the R programming language, equipping them to analyze complex datasets effectively. Beyond technical proficiency, our goal is to nurture your research acumen and critical thinking abilities.
Over the course of the program, students will design and execute their own research projects, utilizing secondary data sources to explore topics of interest and relevance. By guiding these young minds through the complete research cycle, from hypothesis formulation to data analysis and presentation, we aim to instill in them a deep understanding of the data science field and the confidence to contribute meaningful insights to various domains, thereby preparing them for a future filled with opportunities and the potential to make a significant impact.
Program Highlights
- Mentoring by a graduate-level researcher.
- Hands-on experience in all aspects of data science research.
- Research independence
- Exposure to the ethical principles of research.
- Opportunities for collaboration with peers.
- Presentation of findings to the wider community.
Mentorship
Graduate-level Mentorship
Exposure
Exposure to real research
YEAR 1 – Introduction to R and Statistics
Introduction to Data Science
Spring Semester (Year 1): Introduction to Data Science
Fundamentals
Fundamentals of data science concepts and terminology.
Visualization
Basic data manipulation and visualization techniques.
Introduction
Introduction to the R programming language.
Data Explorer
Exploring data sources and datasets available online.
YEAR 1 – Introduction to R and Statistics
Summer Semester (Year 1): Introduction to Statistics
R
Advanced R programming and data manipulation.
Storytelling
Data visualization and storytelling.
Data Sources
Exploring data sources and datasets available online.
Analysis
Statistical analysis and hypothesis testing.
Ethics
Introduction to data ethics and responsible data handling.
YEAR 2 – Research, Analysis, and Presentation
Research, Analysis, and Presentation
Fall Semester (Year 2): Data Collection and Analysis
Data Collection
Begin data collection following the approved research proposal.
Mentorship
Regular data analysis sessions with the mentor.
Ethics
Ethical considerations in research.
YEAR 2 – Research, Analysis, and Presentation
Spring Semester (Year 2): Presentation and Conclusion
Conclusion
Analyze data and draw conclusions.
Dissemination
Showcase findings at a school-wide or community event.
Presentation
Prepare a research presentation.