{"id":20392750,"url":"https://github.com/baptvit/artificial_intelligence","last_synced_at":"2025-07-22T18:36:01.921Z","repository":{"id":130240874,"uuid":"163898675","full_name":"baptvit/Artificial_Intelligence","owner":"baptvit","description":"My courses and activities in Artificial Intelligence","archived":false,"fork":false,"pushed_at":"2020-01-31T00:45:52.000Z","size":55891,"stargazers_count":4,"open_issues_count":3,"forks_count":1,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-04-07T15:52:32.316Z","etag":null,"topics":["data-science","deep-learning","excel","machine-learning","python","r"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/baptvit.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2019-01-02T23:05:50.000Z","updated_at":"2024-12-02T19:15:23.000Z","dependencies_parsed_at":"2024-03-12T10:32:20.318Z","dependency_job_id":null,"html_url":"https://github.com/baptvit/Artificial_Intelligence","commit_stats":null,"previous_names":["baptvit/artificial_intelligence"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/baptvit/Artificial_Intelligence","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/baptvit%2FArtificial_Intelligence","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/baptvit%2FArtificial_Intelligence/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/baptvit%2FArtificial_Intelligence/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/baptvit%2FArtificial_Intelligence/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/baptvit","download_url":"https://codeload.github.com/baptvit/Artificial_Intelligence/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/baptvit%2FArtificial_Intelligence/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266552761,"owners_count":23947184,"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","status":"online","status_checked_at":"2025-07-22T02:00:09.085Z","response_time":66,"last_error":null,"robots_txt_status":null,"robots_txt_updated_at":null,"robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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-science","deep-learning","excel","machine-learning","python","r"],"created_at":"2024-11-15T03:45:24.961Z","updated_at":"2025-07-22T18:35:56.887Z","avatar_url":"https://github.com/baptvit.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n\n# Learning Data Science\n\n#### Course base\n\nThis is the Curriculum for [Learn Data in 3 Science Months](https://youtu.be/9rDhY1P3YLA) by Siraj,[Dreams in the CodingTrain](https://github.com/CodingTrain/Machine-Learning)  Raval and [Roadmap: How to Learn Machine Learning in 6 Months](https://www.youtube.com/watch?v=MOdlp1d0PNA) by Zach Miller. \n\n# Resource attributes\n\nSince resources across the internet vary in terms of their pre-requisites and general accessibility, it is useful to\ngive attributes to them so that it is easy to understand where a resource fits into the wider machine learning scope. Below is a few suggested attributes (please extend):\n \n - :blue_book: = Doing\n - :heavy_check_mark: = Completed\n - :rainbow: = creative\n - :bowtie: = beginner\n - :sweat_smile: = intermediate, some pre-requisites\n - :godmode: = advanced, many pre-requisites\n\n\n#### Tools Used\n- Python, SQL, R, Tensorflow,Spark, Excel\n\n### Accelerated Learning Techniques\n- Watch videos at 2x or 3x speed using a browser extension\n- Handwrite notes as you watch for memory retention\n- Immerse yourself in the [community](https://medium.com/@exastax/top-20-data-science-blogs-and-websites-for-data-scientists-d88b7d99740)\n\n# Data Analysis\n\n## Learn basics data analysis with Excel -\n-   [Microsoft: DAT206x - Analyzing and Visualizing Data with Excel](https://courses.edx.org/courses/course-v1:Microsoft+DAT206x+1T2018a/course/) [RESULTS](https://github.com/helpthx/Data_Science/tree/master/EdX/Microsoft%20Courses/Microsoft:%20Professional%20Certificate%20in%20Excel%20Fundamentals/Microsoft:%20DAT206x%20-%20Analyzing%20and%20Visualizing%20Data%20with%20Excel) :heavy_check_mark:\n- [Microsoft: DAT101x - Introduction to Data Science](https://courses.edx.org/courses/course-v1:Microsoft+DAT101x+1T2018a/course/) [RESULTS](https://github.com/helpthx/Data_Science/tree/master/EdX/Microsoft%20Courses/Microsoft:%20DAT101x%20-%20Introduction%20to%20Data%20Science):heavy_check_mark:\n\n## Learn Python - \n-  [GTx: CSE6040x - FA18: Computing for Data Analysis](https://courses.edx.org/courses/course-v1:GTx+CSE6040x+2T2019/course/) [RESULTS](https://github.com/helpthx/Data_Science/tree/master/EdX/GTx:%20CSE6040x:%20FA18%20-%20Computing%20for%20Data%20Analysis) :heavy_check_mark:\n- [Siraj Raval](https://www.youtube.com/watch?v=T5pRlIbr6gg\u0026list=PL2-dafEMk2A6QKz1mrk1uIGfHkC1zZ6UU) :heavy_check_mark:\n\n## Learn R - \n-  [Harvard University: Professional Certificate in Data Science](https://www.edx.org/professional-certificate/harvardx-data-science) [RESULTS](https://github.com/helpthx/Data_Science/tree/master/EdX/Harvard%20University:%20Professional%20Certificate%20in%20Data%20Science) :blue_book:\n\n## Statistics \u0026 Probability\n-  [KhanAcademy](https://www.khanacademy.org/math/statistics-probability) :blue_book:\n\n## Data Pre-processing, Data Visualization, Exploratory Data Analysis\n-  [GTx: CSE6040x - FA18: Computing for Data Analysis](https://courses.edx.org/courses/course-v1:GTx+CSE6040x+2T2019/course/) [RESULTS](https://github.com/helpthx/Data_Science/tree/master/EdX/GTx:%20CSE6040x:%20FA18%20-%20Computing%20for%20Data%20Analysis) :heavy_check_mark:\n\n\n# Machine Learning\n\n#### Math of Machine Learning Cheat Sheets\n-  [Statistics](http://web.mit.edu/~csvoss/Public/usabo/stats_handout.pdf)\n-  [Probability](https://static1.squarespace.com/static/54bf3241e4b0f0d81bf7ff36/t/55e9494fe4b011aed10e48e5/1441352015658/probability_cheatsheet.pdf)\n-  [Calculus](http://tutorial.math.lamar.edu/pdf/Calculus_Cheat_Sheet_All.pdf)\n-  [Linear Algebra](https://www.souravsengupta.com/cds2016/lectures/Savov_Notes.pdf)\n\n## Algorithms \u0026 Machine Learning\n- #### [Applied Data Science with Python](https://cognitiveclass.ai/learn/data-science-with-python/)  \n\t- [Python for Data Science](https://cognitiveclass.ai/courses/python-for-data-science/) [RESULTS](https://github.com/helpthx/Data_Science/blob/master/Cognitive_Class_IBM/Applied_Data_Science_with_Python/Cognitiveclass%20PY0101EN%20Certificate%20_%20Cognitive%20Class.pdf) :heavy_check_mark:\n\t- [Data Analysis with Python](https://cognitiveclass.ai/courses/data-analysis-python/) [RESULTS](https://github.com/helpthx/Data_Science/blob/master/Cognitive_Class_IBM/Applied_Data_Science_with_Python/CognitiveClass%20DA0101EN%20Certificate%20_%20Cognitive%20Class.pdf) :heavy_check_mark:\n\t- [Data Visualization with Python](https://cognitiveclass.ai/courses/data-visualization-with-python/) [RESULTS](https://github.com/helpthx/Data_Science/blob/master/Cognitive_Class_IBM/Applied_Data_Science_with_Python/Cognitive%20Class%20DV0101EN%20Certificate%20_%20Cognitive%20Class.pdf) :heavy_check_mark:\n\t- [Machine Learning with Python](https://cognitiveclass.ai/courses/machine-learning-with-python/) [RESULTS](https://github.com/helpthx/Data_Science/blob/master/Cognitive_Class_IBM/Applied_Data_Science_with_Python/Cognitive%20Class%20ML0101ENv3%20Certificate%20_%20Cognitive%20Class.pdf) :heavy_check_mark:\n\t \n- [Columbia](https://courses.edx.org/courses/course-v1:ColumbiaX+DS102X+2T2018/course/)\n\n## Deep Learning\n- #### Deep Learning path from cognitive.ia IBM\n\t-  [Deep Learning Fundamentals](https://cognitiveclass.ai/courses/introduction-deep-learning/) [RESULTS](https://github.com/helpthx/Data_Science/blob/master/Cognitive_Class_IBM/Deep_Learning/DeepLearning.TV%20ML0115EN%20Certificate%20_%20Cognitive%20Class.pdf):heavy_check_mark:\n\t- [Deep Learning with TensorFlow](https://cognitiveclass.ai/courses/deep-learning-tensorflow/) [RESULTS](https://github.com/helpthx/Data_Science/blob/master/Cognitive_Class_IBM/Deep_Learning/CognitiveClass%20ML0120ENv2%20Certificate%20_%20Cognitive%20Class.pdf):heavy_check_mark:\n\t-  [Accelerating Deep Learning with GPU](https://cognitiveclass.ai/courses/accelerating-deep-learning-gpu/) [RESULTS](https://github.com/helpthx/Data_Science/blob/master/Cognitive_Class_IBM/Deep_Learning/CognitiveClass%20ML0122ENv1%20Certificate%20_%20Cognitive%20Class.pdf) :heavy_check_mark:\n-  [IBM DL0101EN - Deep Learning Fundamentals with Keras](https://www.edx.org/course/deep-learning-fundamentals-with-keras)  [RESULTS](https://github.com/helpthx/Data_Science/blob/master/EdX/IBM%20DL0101EN%20-%20Deep%20Learning%20Fundamentals%20with%20Keras/final_progress.png) :heavy_check_mark:\n-  [IBM DL0110EN - Deep Learning with Python and PyTorch](https://www.edx.org/course/deep-learning-with-python-and-pytorch)  :blue_book:\n-  [Part 1 and 2 of DL Book](https://www.deeplearningbook.org/) \n-  [Siraj Raval](https://www.youtube.com/watch?v=vOppzHpvTiQ\u0026list=PL2-dafEMk2A7YdKv4XfKpfbTH5z6rEEj3)\n\n# Real-World Tools\n\n## Databases (SQL + NoSQL) \n-  [KhanAcademy](https://www.khanacademy.org/computing/computer-programming/sql) :blue_book:\n-  [M001: MongoDB Basics](https://university.mongodb.com/mercury/M001/2019_January_2/overview) [RESULTS](https://github.com/helpthx/MongoDB_University/tree/master/M001:%20MongoDB%20Basics) :heavy_check_mark:\n-  [Microsoft:  DAT240x Using Non-Relational Data in SQL Server](https://courses.edx.org/courses/course-v1:Microsoft+DAT240x+2T2018) :blue_book:\n-  [Microsoft:  DAT221x Introduction to NoSQL Data Solutions](https://courses.edx.org/courses/course-v1:Microsoft+DAT221x+1T2019) [RESULTS](https://github.com/helpthx/Data_Science/tree/master/EdX/Microsoft:%20DAT221x%20-%20Introduction%20to%20NoSQL%20Data%20Solutions) :heavy_check_mark:\n- [Modelagem de dados](https://www.ev.org.br/Cursos?fbclid=IwAR1ctGjJbtF_q_mI7aMcW7Yee0ym7v7Yo9XP31Dhse4KgfOc89IKpD2Eo10) [RESULTS](https://github.com/helpthx/Data_Science/tree/master/Escola_Virtual_Funda%C3%A7%C3%A3o_Bradesco/Modelagem%20de%20dados) :heavy_check_mark:\n- [Implementando Banco de dados](https://www.ev.org.br/Cursos?fbclid=IwAR1ctGjJbtF_q_mI7aMcW7Yee0ym7v7Yo9XP31Dhse4KgfOc89IKpD2Eo10) [RESULTS](https://github.com/helpthx/Data_Science/tree/master/Escola_Virtual_Funda%C3%A7%C3%A3o_Bradesco/Implementando%20banco%20de%20dados) :heavy_check_mark:\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbaptvit%2Fartificial_intelligence","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbaptvit%2Fartificial_intelligence","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbaptvit%2Fartificial_intelligence/lists"}