{"id":20011464,"url":"https://github.com/jorgeandrespadilla/data-science-course","last_synced_at":"2025-10-19T02:03:54.143Z","repository":{"id":106965764,"uuid":"515616753","full_name":"jorgeandrespadilla/data-science-course","owner":"jorgeandrespadilla","description":"Data Science Course by Jennifer Widom (UDLA, 2022)","archived":false,"fork":false,"pushed_at":"2022-07-25T08:40:45.000Z","size":48869,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-01-12T14:47:44.858Z","etag":null,"topics":["data-mining","data-science","machine-learning","network-analysis"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":false,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jorgeandrespadilla.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-07-19T14:22:40.000Z","updated_at":"2023-09-28T08:18:58.000Z","dependencies_parsed_at":null,"dependency_job_id":"68f0d156-8819-477f-84bf-b0f7d5cbd89a","html_url":"https://github.com/jorgeandrespadilla/data-science-course","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jorgeandrespadilla%2Fdata-science-course","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jorgeandrespadilla%2Fdata-science-course/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jorgeandrespadilla%2Fdata-science-course/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jorgeandrespadilla%2Fdata-science-course/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jorgeandrespadilla","download_url":"https://codeload.github.com/jorgeandrespadilla/data-science-course/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241447645,"owners_count":19964336,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-mining","data-science","machine-learning","network-analysis"],"created_at":"2024-11-13T07:26:01.883Z","updated_at":"2025-10-19T02:03:54.049Z","avatar_url":"https://github.com/jorgeandrespadilla.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data Science Course\n\n## Introduction\n\nMany of the world's biggest discoveries and decisions in science, technology, business, medicine, politics, and society as a whole, are now being made on the basis of analyzing data. Professor Widom's short-courses provide an introduction to data science, including some history, case studies, and common pitfalls, along with broad, interactive, hands-on coverage of tools \u0026 techniques for data collection, analysis, and visualization.\n\nThis short-courses where dictated by Jennifer Widom, Dean of the School of Engineering at Stanford University, from July 19th to July 21st, 2022, at UDLA's campus.\n\nThis repository is a collection of all the course materials, including the course notes, presentation slides, and hands-on activities.\n\nSee more at [Data Science Fact Sheet](materials/documents/Data%20Science%20Fact%20Sheet.pdf).\n\n## Itinerary\n\n### Day 1 (19th July)\n\n**Introduction to Data Science**:\n\n*Content:*\n\n- The “Instructional Odyssey”\n- Motivation and terminology\n- Applications and services\n- Tools and Techniques overview:\n    - Basic Data Manipulation and Analysis\n    - Data Mining\n    - Machine Learning\n    - Data Visualization\n    - Data Collection and Preparation\n    - Languages, Systems, Platforms\n- Pitfalls:\n    - Correlation and Causation\n    - Underfitting and Overfitting\n    - Privacy considerations\n\nSee more at [Overview of Data Science](materials/slides/OverviewSlides.pdf) or [Overview of Data Science (COVID Edition)](materials/slides/OverviewSlidesCE.pdf).\n\n**Data Analysis and Visualization:**\n\n*Before starting:*\n\n- [Getting Started with Google Sheets](materials/documents/getting-started/Getting%20Started%20with%20Google%20Sheets.pdf)\n- [Getting Started with Tableau Public](materials/documents/getting-started/Getting%20Started%20with%20Tableau%20Public.pdf)\n\n*Content:*\n\n- Data analysis using Spreadsheets (see more [here](materials/slides/day1/SpreadsheetsSlides.pdf))\n- Data visualization using Spreadsheets (see more [here](materials/slides/day1/VisualizationSlides.pdf.pdf))\n- Data visualization using Tableau (see more [here](materials/slides/day1/TableauSlides.pdf))\n\n*Hands-on activities:*\n\n- Data analysis using Spreadsheets (*Spreadsheets Module*)\n- Data visualization using Spreadsheets (*Visualization Module*)\n\n### Day 2 (20th July)\n\n**Relational Databases and SQL**:\n\n*Before starting:*\n\n- [Getting Started with Google Colab](materials/documents/getting-started/Getting%20Started%20with%20Google%20Colab.pdf)\n\n*Content:*\n\n- Introduction and basic concepts\n- Basic SQL:\n    - Basic SELECT statement\n    - Ordering\n    - Joins\n    - Basic aggregation\n    - Limit clause\n\nSee more at [Relational Databases and SQL](materials/slides/day2/RelationalDBandSQLSlides.pdf).\n\n*Hands-on activities:*\n\n- Basic SQL (*SQL Modules (only Basic SQL)*)\n\n**Python for Data Analysis and Visualization**:\n\n*Before starting:*\n\n- [Getting Started with Google Colab](materials/documents/getting-started/Getting%20Started%20with%20Google%20Colab.pdf)\n\n*Content:*\n\n- Python basics\n- Data manipulation\n- Pandas and data analysis\n- Plotting and data visualization\n\nSee more at [Python for Data Analysis and Visualization](materials/slides/day2/PythonSlides.pdf).\n\n*Hands-on activities:*\n\n- Python for Data Analysis and Visualization (*Python Modules*)\n\n### Day 3 (21th July)\n\n**Python for Machine Learning**:\n\n*Content:*\n\n- Regression (see more [here](materials/slides/day3/RegressionSlides.pdf)):\n    - Simple linear regression\n    - Regression and Correlation (measuring correlation)\n    - Polynomial regression\n    - Anscombe’s quartet\n- Classification (see more [here](materials/slides/day3/ClassificationSlides.pdf)):\n    - Terminology\n    - K-Nearest Neighbors (KNN)\n    - Decision Trees\n    - Naïve Bayes\n    - Deep Neural Networks\n    - Training and testing\n- Clustering (see more [here](materials/slides/day3/ClusteringSlides.pdf)):\n    - K-Means Clustering\n    - Applications\n\nSee more at [Python for Machine Learning](materials/slides/day3/PythonMLslides.pdf).\n\n*Hands-on activities:*\n\n- Python for Machine Learning (*Machine Learning Modules*)\n\n**Data Mining**:\n\n*Content:*\n\n- Basic concepts\n- Data mining algorithms:\n    - Frequent item-sets\n    - Association rules\n\nSee more at [Data Mining Algorithms](materials/slides/day3/MiningSlides.pdf).\n\n*Hands-on activities:*\n\n- Data Mining using Python (*Data Mining Modules (only Python)*)\n\n**Network Analysis**:\n\n*Content:*\n- Basic concepts\n- Examples\n- Network analysis:\n    - Undirected graphs\n    - Directed graphs\n    - Labeled graphs\n    - Other analyses\n\nSee more at [Network Analysis](materials/slides/day3/NetworksSlides.pdf).\n\n*Hands-on activities:*\n\n- Network Analysis (*Network Analysis (module)*)\n\n## Materials\n\nhttp://www.professorwidom.org/\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjorgeandrespadilla%2Fdata-science-course","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjorgeandrespadilla%2Fdata-science-course","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjorgeandrespadilla%2Fdata-science-course/lists"}