{"id":5802,"date":"2026-03-20T08:24:39","date_gmt":"2026-03-20T13:24:39","guid":{"rendered":"https:\/\/info.hsls.pitt.edu\/molbio\/?p=5802"},"modified":"2026-04-02T08:49:20","modified_gmt":"2026-04-02T13:49:20","slug":"learn-hsls-python-bootcamp-week-1-introduction-to-python-jupyterlab-and-jupyter-notebook-april-6","status":"publish","type":"post","link":"https:\/\/info.hsls.pitt.edu\/molbio\/2026\/03\/20\/learn-hsls-python-bootcamp-week-1-introduction-to-python-jupyterlab-and-jupyter-notebook-april-6\/","title":{"rendered":"Learn @ HSLS: Python Bootcamp Week 1: Introduction to Python, JupyterLab, and Jupyter Notebook &#8211; April 6"},"content":{"rendered":"<p>Monday, April 6, 2026, noon-1:30 p.m., Online<br \/>\nTaught by Alexis Cenname<br \/>\n<a href=\"https:\/\/www.hsls.pitt.edu\/instruction\/data-science\/python-bootcamp-week-1-introduction-python-jupyterlab-and-jupyter-notebook\">Register for Python Bootcamp Week 1<\/a><\/p>\n<div class=\"field field--name-body field--type-text-with-summary field--label-hidden field__item\">\n<p>Join us for our Python Bootcamp Week, offering a comprehensive dive into Python programming. Mirroring the approach of its R counterpart, the bootcamp unfolds through a sequence of dedicated sessions that encompass the data analysis workflow. This includes importing and cleaning data, moving on to data manipulation, and employing advanced visualization techniques with the pandas and seaborn libraries. Each day&#8217;s workshop builds on the last, ensuring a comprehensive understanding and practical application of Python for data analysis.<\/p>\n<p>This is part one of a three-part Python Bootcamp. We look forward to seeing you for all three sessions, as they build on each other; however, we understand if you are not able to make it to all of them \u2013 please still register and attend what you can!<\/p>\n<p>In Week 1, &#8220;Introduction to Python, JupyterLab, and Jupyter Notebook,&#8221; you&#8217;ll familiarize yourself with the JupyterLab interface and learn to create integrated Jupyter notebooks.<\/p>\n<\/div>\n<p><!--more--><\/p>\n<div class=\"field field--name-field-learning-objective field--type-string field--label-above\">\n<div><strong>Target Audience:<\/strong> The target audience for this workshop series is beginners and intermediates in data science, particularly those interested in learning Python programming for data importation, exploration, cleaning, and visualization.<\/div>\n<div><\/div>\n<div class=\"field__label\"><strong>Upon completing this class, you should be able to:<\/strong><\/div>\n<ul class=\"field field--name-field-learning-objective field--type-string field--label-above field__items\">\n<li class=\"field__item\">Utilize the Anaconda Navigater and JupyterLab interface<\/li>\n<li class=\"field__item\">Describe basic components of Python code<\/li>\n<li class=\"field__item\">Describe the basic functionality of Jupyter notebook<\/li>\n<li class=\"field__item\">Use JupyterLab to create a Jupyter notebook<\/li>\n<\/ul>\n<\/div>\n<div class=\"field field--name-field-class-level field--type-list-string field--label-inline\">\n<div class=\"field__label\"><strong>Level:<\/strong> Novice<\/div>\n<\/div>\n<div><\/div>\n<div>\n<div class=\"field field--name-field-class-prerequisites field--type-text-long field--label-inline\">\n<div class=\"field__label\"><strong>Prerequisites:<\/strong> Installation of Anaconda Navigator\/JupyterLab<\/div>\n<\/div>\n<div><\/div>\n<div class=\"field field--name-field-class-prerequisites field--type-text-long field--label-inline\">\n<div class=\"field__label\"><strong>What should you do before attending this class:<\/strong> If you do not have any previous knowledge of Anaconda\/JupyterLab, or do not have it downloaded on your computer, please follow the instructions given in the <a href=\"https:\/\/pitt-my.sharepoint.com\/:u:\/g\/personal\/alc244_pitt_edu\/IQDOn_OUp_RBRb-nc0SKW71_ASM58feWKxW9dD9u7EprUng?e=iEsnGw\"><strong>Overview file<\/strong><\/a>. It is important you complete this\u00a0<strong>before<\/strong>\u00a0the first day. The document will also provide links to additional help and resources for Python\u00a0programming.<\/div>\n<\/div>\n<div class=\"field field--name-field-pre-work-description field--type-text-long field--label-inline\">\n<div><\/div>\n<div class=\"field__label\"><strong>Recording status:<\/strong> This class will be recorded and shared with attendees.<\/div>\n<\/div>\n<\/div>\n<div class=\"field field--name-field-class-materials field--type-list-string field--label-inline\">\n<div><\/div>\n<div class=\"field__label\"><strong>Class Materials:<\/strong> Class materials will be shared with attendees.<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Monday, April 6, 2026, noon-1:30 p.m., Online<br \/>\nTaught by Alexis Cenname<br \/>\n<a href=\"https:\/\/www.hsls.pitt.edu\/instruction\/data-science\/python-bootcamp-week-1-introduction-python-jupyterlab-and-jupyter-notebook\">Register for Python Bootcamp Week 1<\/a><\/p>\n<p>Join us for our Python Bootcamp Week, offering a comprehensive dive into Python programming. Mirroring the approach of its R counterpart, the bootcamp unfolds through a sequence of dedicated sessions that encompass the data analysis workflow.<\/p>\n<p><a class=\"read-more\" alt= \"Learn @ HSLS: Python Bootcamp Week 1: Introduction to Python, JupyterLab, and Jupyter Notebook &#8211; April 6\" href=\"https:\/\/info.hsls.pitt.edu\/molbio\/2026\/03\/20\/learn-hsls-python-bootcamp-week-1-introduction-to-python-jupyterlab-and-jupyter-notebook-april-6\/\">Read more&hellip;<\/a><\/p>\n","protected":false},"author":46,"featured_media":5334,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[65],"tags":[],"class_list":["post-5802","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-march-2026"],"_links":{"self":[{"href":"https:\/\/info.hsls.pitt.edu\/molbio\/wp-json\/wp\/v2\/posts\/5802","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/info.hsls.pitt.edu\/molbio\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/info.hsls.pitt.edu\/molbio\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/info.hsls.pitt.edu\/molbio\/wp-json\/wp\/v2\/users\/46"}],"replies":[{"embeddable":true,"href":"https:\/\/info.hsls.pitt.edu\/molbio\/wp-json\/wp\/v2\/comments?post=5802"}],"version-history":[{"count":2,"href":"https:\/\/info.hsls.pitt.edu\/molbio\/wp-json\/wp\/v2\/posts\/5802\/revisions"}],"predecessor-version":[{"id":5816,"href":"https:\/\/info.hsls.pitt.edu\/molbio\/wp-json\/wp\/v2\/posts\/5802\/revisions\/5816"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/info.hsls.pitt.edu\/molbio\/wp-json\/wp\/v2\/media\/5334"}],"wp:attachment":[{"href":"https:\/\/info.hsls.pitt.edu\/molbio\/wp-json\/wp\/v2\/media?parent=5802"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/info.hsls.pitt.edu\/molbio\/wp-json\/wp\/v2\/categories?post=5802"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/info.hsls.pitt.edu\/molbio\/wp-json\/wp\/v2\/tags?post=5802"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}