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  • Excellent written and verbal communication skills
  • Strong interpersonal skills
  • Customer service and inquiry response
  • Collaboration with staff and external stakeholders

My future

I want to work for a company that appreciates dedication and commitment, encourages fun, creativity, and initiative, rewards smart work, and encourages the development of skills to allow positive contributions.

    Job stuff

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    R (R Studio)

    • To learn more about vectors and lists, check out R for Data Science, Chapter 20: Vectors. It’s a classic resource for learning how to use R for data science and data analysis. It covers everything from cleaning to visualizing to communicating your data.
    • For R documentation: files. It’s a useful reference guide for functions in R code.
    • For the technical aspects of debugging R code, check out Debugging with RStudio on the RStudio Support website. Find answers to questions about RStudio. This article will take you through the R debugging tools built into RStudio, and show you how to use them to help debug R code.
    • For problem-solving strategies for debugging R code, check out the chapter on Debugging in AdvancedR. Advanced R is a great resource if you want to explore the finer details of an R topic and take your knowledge to the next level.

    Python

    Helpful content.

    • The Tableau Public Discover page includes ‘Viz of the Day’ and other beautiful vizzes designed on the platform.
    • Tableau Public resources page: This links to the resources page, including some how-to videos and sample data.
    • Tableau Accessibility FAQ: Access resources about accessibility in Tableau visualizations using the FAQ, which includes links to blog posts, community forums, and tips for new users.
    • Tableau community forum: Search for answers and connect with other users in the community on the forum page.
    • Google Career Certificates page on Tableau Public: This gallery contains all the visualizations created in the video lessons so you can explore these examples more in-depth.
    • Build Your Data Literacy course: Build your data literacy skills in order to interpret, explore, and communicate effectively with data.
    • Introduction: Thinking Clearly in Confusing Times:
      • Barbara Oakley, PhD, PE, – focuses on the complex relationship between neuroscience and social behavior – Ted Talk
      • Terry Sejnowski – Francis Crick Professor at the Salk Institute for Biological Studies
      • Adam Trybus – spatial reasoning using techniques from formal logic and computer science

    Consider a few rules about what makes a helpful data visualization:

    • Five-second rule: A data visualization should be clear, effective, and convincing enough to be absorbed in five seconds or less.
    • Color contrast: Graphs and charts should use a diverging color palette to show contrast between elements.
    • Conventions and expectations: Visuals and their organization should align with audience expectations and cultural conventions. For example, if the majority of your audience associates green with a positive concept and red with a negative one, your visualization should reflect this.
    • Minimal labels: Titles, axes, and annotations should use as few labels as it takes to make sense. Having too many labels makes your graph or chart too busy. It takes up too much space and prevents the labels from being shown clearly.

    Searching case studies

    Public datasets

    • The Google Cloud Public Datasets allow data analysts access to high-demand public datasets, and make it easy to uncover insights in the cloud. 
    • The Dataset Search can help you find available datasets online with keyword searches. 
    • Kaggle has an Open Data search function that can help you find datasets to practice with.
    • Finally, BigQuery hosts 150+ public datasets you can access and use. 

    Public health datasets

    • Global Health Observatory data: You can search for datasets from this page or explore featured data collections from the World Health Organization.  
    • The Cancer Imaging Archive (TCIA) dataset: Just like the earlier dataset, this data is hosted by the Google Cloud Public Datasets and can be uploaded to BigQuery.
    • 1000 Genomes: This is another dataset from the Google Cloud Public resources that can be uploaded to BigQuery. 

    Public climate datasets

    Public social-political datasets

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