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Unveiling Health: Data Discovery Expedition
Coaine Richards
Coaine Richards
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Unveiling Health: Data Discovery Expedition

Explore public health data to uncover hidden trends, emerging disease patterns, and critical insights that shape the future of healthcare.

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Tuesdays
 at
3:00
P.M.
 ET /
12:00
P.M.
PT
8 weeks, 2-3 hours per week
Intermediate
No experience required
No experience required
Some experience required
Degree and experience required

Description

Embark on an exhilarating journey into healthcare data analysis. From identifying trends in disease outbreaks to forecasting future healthcare needs, this project will challenge you to navigate real-world data complexities while sharpening your analytical skills.

You will produce a comprehensive project report that details the entire data analysis process, from initial data collection and cleaning to advanced predictive modeling and result interpretation. Additionally, you will create a visually compelling presentation that highlights key insights, methodologies used, and implications for public health research and practice. These deliverables will not only demonstrate your mastery of data science techniques in the healthcare industry but also showcase your ability to effectively communicate complex findings—an essential skill for future roles in data-driven positions within healthcare and beyond.

By mastering techniques in data cleaning, exploratory analysis, and predictive modeling, you'll not only unlock valuable insights crucial for public health decision-making but also equip yourself with the indispensable skills sought after in entry-level roles across various sectors of the U.S. society, where data-driven decision-making is paramount for addressing pressing healthcare challenges and improving population well-being.

Session timeline

  • Applications open
    August 1, 2024
  • Application deadline
    August 25, 2024
  • Project start date
    Week of July 8, 2024
    Week of
    September 9, 2024
  • Project end date
    Week of

What you will learn

  • Conduct comprehensive data cleaning and preparation for healthcare datasets using tools like Excel and ​​SPSS, ensuring data integrity and suitability for analysis.
  • Perform exploratory data analysis (EDA) on public health datasets, utilizing descriptive statistics, data visualization techniques, and domain knowledge to uncover underlying patterns and trends.
  • Apply advanced feature selection and engineering techniques in the context of healthcare data analysis, integrating domain knowledge and insights gained from EDA to inform predictive modeling.
Build Projects are 8-week experiences that operate on a rolling basis. Selected participants engage in weekly live workshops with a Build Fellow and 2-15 other students.

Project workshops

1
Meet and Setup
2
Collect and Clean Data
3
Explore the Data
4
Select and Engineer Features
5
Train Models
6
Interpret and Validate Models
7
Prepare Report
8
Present Findings

Prerequisites

  • Access to ​​​​SPSS and Microsoft Excel.
  • Basic knowledge of data manipulation and cleaning techniques using tools like Excel and SPSS, including handling missing values, outliers, and inconsistencies to ensure data integrity for analysis.
  • Basic understanding of statistical analysis concepts such as descriptive statistics, hypothesis testing, and regression analysis, enabling you to derive meaningful insights from healthcare datasets and make informed decisions throughout the analysis process.

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About the expert
Coaine Richards
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Coaine
's Linkedin

Coaine Richards is a seasoned mathematics educator with 16 years of experience teaching at both high school and college levels. With a strong foundation in data science, stemming from his Bachelor of Science in Actuarial Science, Coaine seamlessly integrates real-world applications into his lessons, making complex mathematical concepts accessible and engaging for his students.

As a Data Science Fellow, Coaine will collaborate with students on innovative data science projects, guiding them through the intricacies of data analysis and interpretation. His extensive teaching background and practical knowledge ensure that students gain valuable insights and hands-on experience in this rapidly evolving field.

In his free time, Coaine enjoys relaxing at the beach and is always up for a long road trip, often volunteering to be the designated driver for the journey.