{"id":19053363,"url":"https://github.com/georgiosioannoucoder/2023-fall-data-science-ta","last_synced_at":"2026-05-10T07:34:30.801Z","repository":{"id":207105823,"uuid":"718445986","full_name":"GeorgiosIoannouCoder/2023-fall-data-science-ta","owner":"GeorgiosIoannouCoder","description":"These are my code examples for the 2023-fall-data-science-ta as a Data Science Teaching Assistant at CUNY Tech Prep (CTP) Cohort 9. 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ca name=\"readme-top\"\u003e\u003c/a\u003e\n\n***Class GitHub Repository: [https://github.com/CUNYTechPrep/2023-fall-data-science-fridays](https://github.com/CUNYTechPrep/2023-fall-data-science-fridays)***\n\n[![Contributors][contributors-shield]][contributors-url]\n[![Forks][forks-shield]][forks-url]\n[![Stargazers][stars-shield]][stars-url]\n[![Issues][issues-shield]][issues-url]\n[![MIT License][license-shield]][license-url]\n[![LinkedIn][linkedin-shield]][linkedin-url]\n[![GitHub][github-shield]][github-url]\n\n# [CTP](https://cunytechprep.org/) | CUNY Tech Prep\n\n\u003cbr /\u003e\n\u003cdiv align=\"center\"\u003e\n  \u003ca href=\"https://cunytechprep.org/\"\u003e\n    \u003cimg src=\"ctp.png\" alt=\"Logo\" width=\"200\" height=\"200\"\u003e\n  \u003c/a\u003e\n\n\u003ch3 align=\"center\"\u003eCTP\u003c/h3\u003e\n\n  \u003cp align=\"center\"\u003e\n    CUNY Tech Prep is a year long technical and professional development program for CUNY computer science and related majors to learn in-demand technologies, master professional soft skills, and land great tech jobs in NYC.\n    \u003cbr /\u003e\n    \u003ca href=\"https://github.com/GeorgiosIoannouCoder/movierate-backend\"\u003e\u003cstrong\u003eExplore the docs »\u003c/strong\u003e\u003c/a\u003e\n    \u003cbr /\u003e\n    \u003cbr /\u003e\n    \u003ca href=\"https://github.com/GeorgiosIoannouCoder/movierate-backend/issues\"\u003eReport Bug\u003c/a\u003e\n    ·\n    \u003ca href=\"https://github.com/GeorgiosIoannouCoder/movierate-backend/issues\"\u003eRequest Feature\u003c/a\u003e\n  \u003c/p\u003e\n\u003c/div\u003e\n\n\u003cdetails\u003e\n  \u003csummary\u003eTable of Contents\u003c/summary\u003e\n  \u003col\u003e\n    \u003cli\u003e\n      \u003ca href=\"#about-ctp\"\u003eAbout CTP\u003c/a\u003e\n      \u003cul\u003e\n        \u003cli\u003e\u003ca href=\"#mission\"\u003eMission\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"#general-information\"\u003eGeneral Information\u003c/a\u003e\n        \u003cul\u003e\n        \u003cli\u003e\u003ca href=\"#industry-insight\"\u003eIndustry Insight\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"#project-experience-with-industry-mentorship\"\u003eProject Experience with Industry Mentorship\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"#professional-development\"\u003eProfessional Development\u003c/a\u003e\u003c/li\u003e   \n        \u003c/ul\u003e\n        \u003c/li\u003e\n      \u003c/ul\u003e\n    \u003c/li\u003e\n    \u003cli\u003e\n      \u003ca href=\"#georgios-ioannou-data-science-teaching-assistant-fall-2023\"\u003eGeorgios Ioannou Data Science Teaching Assistant Fall 2023\u003c/a\u003e\n    \u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#contributing\"\u003eContributing\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#license\"\u003eLicense\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#contact\"\u003eContact\u003c/a\u003e\u003c/li\u003e\n  \u003c/ol\u003e\n\u003c/details\u003e\n\n## About CTP\n\n\u003ca href=\"https://cunytechprep.org/\"\u003e\n  \u003cimg src=\"ctp.png\" alt=\"Logo\" width=\"100\" height=\"100\"\u003e\n\u003c/a\u003e\n\n### Mission\n\n- Our mission is to equip CUNY students with the resources they need to jumpstart their careers in tech.\n\n- Developed and delivered with the CUNY Institute for Software Design and Development and industry leaders, CTP is designed to provide students with industry exposure to software development and a connection to tech jobs post-graduation.\n\n- The NYC Tech Talent Pipeline is a multi-million industry partnership designed to support the growth of the City's tech sector and deliver quality jobs for New Yorkers and quality talent for New York’s businesses.\n\n\u003cp align=\"right\"\u003e\u003ca href=\"#readme-top\"\u003eBack to top\u003c/a\u003e\u003c/p\u003e\n\n### General Information\n\n- CUNY Tech Prep was established in 2015 to serve computer science and computing students from the 11 four-year CUNY Colleges that are preparing to enter the workforce. Students accepted into CTP each academic year participate in a program designed to prepare them for the challenges of the job search and technical work in the industry.\n\n- The curriculum is designed around three pillars:\n\n  ## Industry Insight\n\n  - Our technical curriculum offers two tracks: full stack web development using modern JavaScript and data science using Python. The curriculums are developed, evaluated, and taught by industry experts.\n\n  - In both tracks, students work in teams to design, develop, and deploy projects where they learn and apply tools, concepts, and processes — Git, TDD and automated testing, CI/CD, agile, web security, etc. — desired by high-tech employers.\n\n  ## Project Experience with Industry Mentorship\n\n  - Students work in teams on projects they propose, design, and implement. Each team is assigned a mentor that supervises the work, introduces the software development life cycle and best practices, and performs code reviews.\n\n  - CTP instructors, TA's, and mentors all have extensive current and past industry experience as software engineers and data scientists.\n\n  ## Professional Development\n\n  - It takes more than technical skills to land a job in tech! That's why CUNY Tech Prep takes a holistic approach to professional development. Our fellows have access to:\n  \n    - 1:1 Career Coaching, including behavioral interview practice In-class workshops led by our career coaches on topics such as networking, project pitching, job search strategy, resumes, and communication skills\n\n    - Mock technical interviews conducted by industry professionals\n\n    - Workshops led by industry professionals\n\n    - Assistance with crafting technical resumes\n\n\n\n\u003cp align=\"right\"\u003e\u003ca href=\"#readme-top\"\u003eBack to top\u003c/a\u003e\u003c/p\u003e\n\n## Georgios Ioannou Data Science Teaching Assistant Fall 2023\n\n- In this repository you can find all of my code examples as the Teaching Assistant for the Fall 2023 Data Science Track Cohort 9 at CUNY Tech Prep (CTP).\n\n- You can also use [NBViwer](https://nbviewer.org/) to see all of my code example notebooks interactively.\n\n\u003cp align=\"right\"\u003e\u003ca href=\"#readme-top\"\u003eBack to top\u003c/a\u003e\u003c/p\u003e\n\n\n## Contributing\n\nContributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.\n\nIf you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag \"enhancement\".\nDon't forget to give the project a star! Thanks again!\n\n1. Fork the Project\n2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)\n3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)\n4. Push to the Branch (`git push origin feature/AmazingFeature`)\n5. Open a Pull Request\n\n\u003cp align=\"right\"\u003e\u003ca href=\"#readme-top\"\u003eBack to top\u003c/a\u003e\u003c/p\u003e\n\n## License\n\nDistributed under the MIT License. See [LICENSE](https://github.com/GeorgiosIoannouCoder/2023-fall-data-science-ta/blob/master/LICENSE) for more information.\n\nMIT License\n\nCopyright (c) 2023 Georgios Ioannou\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n\n\u003cp align=\"right\"\u003e\u003ca href=\"#readme-top\"\u003eBack to top\u003c/a\u003e\u003c/p\u003e\n\n## Contact\n\nGeorgios Ioannou - [@LinkedIn](https://linkedin.com/in/georgiosioannoucoder)\n\nGeorgios Ioannou - [@georgiosioannoucoder](https://georgiosioannoucoder.github.io/) - Please contact me via the form in my portfolio.\n\nProject Link: [https://github.com/GeorgiosIoannouCoder/2023-fall-data-science-ta](https://github.com/GeorgiosIoannouCoder/2023-fall-data-science-ta)\n\n\u003cp align=\"right\"\u003e\u003ca href=\"#readme-top\"\u003eBack to top\u003c/a\u003e\u003c/p\u003e\n\n[contributors-shield]: https://img.shields.io/github/contributors/GeorgiosIoannouCoder/2023-fall-data-science-ta.svg?style=for-the-badge\n[contributors-url]: https://github.com/GeorgiosIoannouCoder/2023-fall-data-science-ta/graphs/contributors\n\n[forks-shield]: https://img.shields.io/github/forks/GeorgiosIoannouCoder/2023-fall-data-science-ta.svg?style=for-the-badge\n[forks-url]: https://github.com/GeorgiosIoannouCoder/2023-fall-data-science-ta/network/members\n\n[stars-shield]: https://img.shields.io/github/stars/GeorgiosIoannouCoder/2023-fall-data-science-ta.svg?style=for-the-badge\n[stars-url]: https://github.com/GeorgiosIoannouCoder/2023-fall-data-science-ta/stargazers\n\n[issues-shield]: https://img.shields.io/github/issues/GeorgiosIoannouCoder/2023-fall-data-science-ta.svg?style=for-the-badge\n[issues-url]: https://github.com/GeorgiosIoannouCoder/2023-fall-data-science-ta/issues\n\n[license-shield]: https://img.shields.io/github/license/GeorgiosIoannouCoder/movierate-backend.svg?style=for-the-badge\n[license-url]: https://github.com/GeorgiosIoannouCoder/movierate-backend/blob/master/LICENSE\n\n[linkedin-shield]: https://img.shields.io/badge/-LinkedIn-black.svg?style=for-the-badge\u0026logo=linkedin\u0026colorB=0077B5\n[linkedin-url]: https://linkedin.com/in/georgiosioannoucoder\n\n[github-shield]: https://img.shields.io/badge/-GitHub-black.svg?style=for-the-badge\u0026logo=github\u0026colorB=000\n[github-url]: https://github.com/GeorgiosIoannouCoder/\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgeorgiosioannoucoder%2F2023-fall-data-science-ta","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgeorgiosioannoucoder%2F2023-fall-data-science-ta","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgeorgiosioannoucoder%2F2023-fall-data-science-ta/lists"}