This project is no longer accepting applications. Subscribe to our newsletter to be notified of new projects!
Analyze and visualize real-world climate data using Python to uncover trends in global temperature and CO₂ levels, creating a professional climate data report.
Data science plays a crucial role in understanding climate change, allowing scientists and policymakers to analyze trends, make predictions, and develop solutions. This project introduces you to the fundamentals of climate data analysis using Python, focusing on real-world datasets from NASA and NOAA.
In this Build Project, you will step into the role of a Data Scientist working in the environmental sector. You will learn how to access, clean, and analyze climate data, create compelling visualizations, and interpret key indicators such as global temperature rise and CO₂ levels. The project is designed to be accessible to students with basic Python knowledge, focusing on step-by-step learning and practical implementation. By the end, you will have a structured portfolio piece, showcasing your ability to analyze and communicate climate data effectively.
This workshop will introduce you to climate data sources and their significance in understanding environmental changes. You will explore datasets from NASA and NOAA, learning how scientists use data to track climate trends, predict future changes, and inform policy decisions. The workshop will also provide guidance on selecting an appropriate dataset for analysis, which will serve as the foundation for the entire project.
This workshop focuses on the fundamentals of data handling using Python. You will learn how to load, inspect, and explore your chosen climate dataset using Pandas and NumPy. The workshop will emphasize data structures, basic operations, and exploratory data analysis techniques that help uncover patterns in climate data.
This workshop focuses on the importance of data cleaning and preprocessing before analysis. You will learn how to handle missing values, remove inconsistencies, and standardize data for visualization and trend analysis. You will gain hands-on experience in refining raw climate datasets for meaningful insights.
You will learn how to visualize climate trends using Python libraries like Matplotlib and Seaborn. This workshop will focus on creating line charts, bar graphs, and heatmaps to represent temperature and CO₂ level changes over time. Emphasis will be placed on customizing graphs for better storytelling and clarity.
This workshop will introduce you to trend analysis techniques for climate data. You will learn how to calculate trendlines, compare historical temperature and CO₂ levels, and interpret key climate indicators. The discussion will also cover the real-world implications of climate trends on policy and decision-making.
In this workshop, you will learn how to present your climate data findings in an engaging and effective way. You will explore techniques for structuring your insights, writing clear explanations, and designing compelling data narratives. The goal is to ensure your analysis is accessible to both technical and non-technical audiences.
This workshop focuses on refining your project deliverables, including the final report, visualizations, and presentation slides. You will receive feedback on your work and improve the clarity and professionalism of your findings. The session will also cover how to present your work effectively in a professional setting.
In the final workshop, you will present your projects to your peers and the Project Leader. You will practice articulating your analysis, answering questions, and discussing the broader significance of your findings. The workshop will also include reflections on key learnings and future applications of skills.
Get access to all of our Build projects, including this one, by creating your Build account!
Get started by submitting your application.
We'll notify you of new projects via email. In the meantime, you can explore our resources and learn more about our Fellows.
Denis Slabakov is a Mathematics Build Fellow at DREAM Venture Labs, where he works with students leading projects in mathematics and applied problem-solving.
Denis is a co-founder and managing director at New Mining, a cryptocurrency mining company engaged in developing and managing high-performance data centers. He focuses on expanding the business internationally, specifically in the U.S. market, and exploring new technologies to optimize mining operations.
Denis has over 15 years of experience in IT, business development, and entrepreneurship. Over his career, he has co-founded and managed ventures in cryptocurrency, real estate, and media. He specializes in leading teams, solving complex business challenges, and scaling operations globally.
He holds a degree in Applied Mathematics from Moscow Institute of Physics and Technology and has completed business administration studies at The Open University.
A fun fact about Denis is that he has visited over 50 countries and has a passion for mountain skiing and exploring new cultures.