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sanchezemily_LATE_3776213_69754480_Final Presentation_ Data Science.pdfEmily Sanchez
Emily Sanchez
Faculty Collaborator: Marissa Gray
About:
Emily has been collaborating with Dr. Marissa Gray, a professor of Biomedical Engineering, to develop a series of instructional videos on using the pandas package in Python. Dr. Gray teaches a year-long capstone class where clinicians present real-world problems, and students work throughout the semester to understand and solve these issues. Given that most projects involve a data science component and many students lack a background in data science or coding, understanding data has been a significant challenge.
The instructional videos, along with pre-populated Google Colab notebooks, are designed to serve as a crash course for students with no Python experience and for those who have experience but have not used Python for data science. This resource aims to bridge the knowledge gap and equip students with the necessary skills to handle data effectively in their projects.
transcript
transcript
Why was there a need for a fellow?
Course Context:
Year-long capstone course in the engineering department.
Clinicians present problems, and students find solutions throughout the semester.
Data Science Element:
Example: Sensor data such as heart rate and blood pressure.
Student Experience:
Varied levels of coding and data handling experience among students.
Main Project Goals
Create a Series of Video Tutorials:
Increasing in depth.
Crash course in Python and Pandas for beginners.
Refresher for those with prior experience.
Video Topics:
Introduction to Data Analysis and Python
Python Fundamentals
Introduction to Pandas
Data Cleaning
Exploratory Data Analysis (EDA)
Troubleshooting and Debugging
Statistical Analysis
Data Visualization
Advanced Pandas Techniques (Grouping and Aggregating, Merging and Joining, Pivot Tables)
Tools & Resources
Google Colab Notebooks
Zoom:
Screen share and recording function
Overcoming Obstacles
Recording: Takes practice.
Timeline and Scheduling
Rhythm: Managing weekly deliverables
Achievements
Populated Google Colab Notebooks for the First 5 Videos:
Introduction to Data Analysis and Python
Python Fundamentals
Introduction to Pandas
Data Cleaning
Exploratory Data Analysis (EDA)
Outlining: First 5 videos
Recording: Completed 2 videos
Consultant & Teaching Skills
Communication: Balancing the needs of students
Learner-Centered Approach: As opposed to a teacher-centered approach
Creating, Connecting, and Computing:
Creating: Providing a populated Colab notebook to discourage passivity
Connecting: Using real sensor data sets
Computing: Teaching computing techniques
Constructivist Approach: Creating an active learning environment that builds knowledge
Scaffolding: Providing temporary support to help students become progressively more independent
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