Course Materials

Here, is our content used in our BIOL/CHEM 806 - Exploratory Data Science for Scientists class for your learning.

This course is a part of the Graduate Opportunities to Learn Data Science (GOLD) series intended for SFSU Masters students specializing in Biology and Biochemistry & Chemistry. We will emphasize data science concepts, investigative skills, collaboration skills, and coding skills integral to data science. An overarching goal of the course is for us to gain insight into the nature of scientific inquiry, the process by which data science knowledge is created, and of the strengths and limitations of the process and the evidence obtained using data science techniques. To this end, we will consider experiments and data stemming from research in biology and biochemistry. From ocean acidification to telomere length, and from cancer biomarkers to frog embryos, we'll be covering a range of biological and biochemical topics using data science!

Course Content

• Designed to deepen our understanding of:

  • What data science is

  • How it is used in natural science research

  • The types of people that do data science

  • The philosophy of data science that informs ethical, reproducible, and collaborative practices

  • Applications of data science and its influence on society

Learning Outcomes

At the completion of this course, students will be able to understand the working principles and apply good practices for:

• Coding for data science in R and python. Learn to use Rstudio, Jupyter hub, and Google Colab.
• Managing data science projects. Map out and reflectively work within the data science cycle (preparation, analysis, reporting), organize elements of a data analysis project from the file-structure perspective, and document its contents.
• Data Visualization. Basic principles and how to display data graphically; create plots and design graphs to communicate information simply, clearly, and accurately.
• Data Exploration and Modeling. Statistical methods to explore, describe, and summarize data including statistical tests, visualizations of data and results, simulations, principal components analysis, and machine learning.
• Fostering community with scientists at SFSU and beyond. Learning about the people who use data science and their diverse backgrounds – and where you and your own research fits in.

Overall, this course aspires to support each and every one of us in developing the interests, basic content knowledge, and skills necessary to evaluate and make new discoveries in data science. Through this course, we will engage with data science as it is relevant to the life 2 sciences. With the tools we learn, we will continue to deepen our knowledge of data science throughout our lives, whether it's using data science in our theses or in our future careers and advocacy.