{"id":29061737,"url":"https://github.com/waqasm78/ai-90days","last_synced_at":"2026-04-29T04:35:54.243Z","repository":{"id":301427430,"uuid":"1008689899","full_name":"waqasm78/AI-90Days","owner":"waqasm78","description":"Learn AI in 90 Days – A Complete Beginner-to-Project Guide with Python, Jupyter \u0026 Visual Studio 2022","archived":false,"fork":false,"pushed_at":"2025-06-26T20:00:04.000Z","size":15,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-26T20:38:40.574Z","etag":null,"topics":["ai","beginner-friendly","beginner-friendly-project","jupyter-notebook","learning-path","machine-learning","python","visual-studio"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"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/waqasm78.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,"zenodo":null}},"created_at":"2025-06-26T00:20:11.000Z","updated_at":"2025-06-26T20:00:08.000Z","dependencies_parsed_at":"2025-06-26T20:38:46.120Z","dependency_job_id":"f8228fe2-907d-4c0e-88e6-195fe0a81b1d","html_url":"https://github.com/waqasm78/AI-90Days","commit_stats":null,"previous_names":["waqasm78/ai-90days"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/waqasm78/AI-90Days","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/waqasm78%2FAI-90Days","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/waqasm78%2FAI-90Days/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/waqasm78%2FAI-90Days/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/waqasm78%2FAI-90Days/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/waqasm78","download_url":"https://codeload.github.com/waqasm78/AI-90Days/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/waqasm78%2FAI-90Days/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":262219795,"owners_count":23276888,"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":["ai","beginner-friendly","beginner-friendly-project","jupyter-notebook","learning-path","machine-learning","python","visual-studio"],"created_at":"2025-06-27T08:07:05.519Z","updated_at":"2026-04-29T04:35:54.231Z","avatar_url":"https://github.com/waqasm78.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 90-Day AI Learning Journey 🚀\n\nWelcome to the **90-Day AI Upskilling Program** — a structured, hands-on path designed for professionals coming from traditional languages like .NET (C#), C++ MFC, and FORTRAN who now want to enter the AI field using **Python** and real-world projects.\n\nThis repository will guide you through all the necessary tools, programming concepts, and AI/ML practices over 90 days, one day at a time. Each day comes with:\n\n* 📚 Theory (with beginner-friendly explanations)\n* 💻 Practical coding exercises\n* 📓 Jupyter notebooks\n* ✅ Real-world mini projects\n* ☁️ Deployment, GitHub versioning, and portfolio building\n\n\u003e 💡 All daily lessons are kept in the [`docs/`](docs/README.md) folder for easy access.\n\n---\n\n## 🗂 Folder Structure\n\n```\nAI-90Days/\n│\n├── Day1_Setup/             # Your code, notebooks, and files for Day 1\n├── Day2_PythonBasics/      # Folder for Day 2 exercises and code\n├── ...\n├── docs/                   # Contains markdown files for each day\n│   ├── Day1.md             # Full guide for Day 1\n│   ├── Day2.md             # Full guide for Day 2\n│   └── ...\n│\n└── README.md               # This overview file\n```\n\n---\n\n## 🔗 Daily Learning Modules\n\nEach link below takes you to the detailed tutorial and instructions for that day.\n\n| Day | Topic                                           | Link                                          |\n| --- | ----------------------------------------------- | --------------------------------------------- |\n| 1   | Tools Setup + Git + Jupyter Intro               | [Day 1](docs/Day1_Setup.md)                   |\n| 2   | Python Basics                                   | [Day 2](docs/Day2_PythonBasics.md)            |\n| 3   | Collections: Lists, Tuples, Sets \u0026 Dictionaries | [Day 3](docs/Day3_Collections.md)             |\n| 4   | Control Flow: If, For, While, and Logic         | [Day 4](docs/Day4_ControlFlow.md)             |\n| 5   | Functions                                       | [Day 5](docs/Day5_Functions.md)               |\n| 6   | Modules and Packages                            | [Day 6](docs/Day6_Modules.md)                 |\n| 7   | Exception Handling                              | [Day 7](docs/Day7_Exceptions.md)              |\n| 8   | File Handling                                   | [Day 8](docs/Day8_FileHandling.md)            |\n| 9   | Working with CSV and JSON Files                 | [Day 9](docs/Day9_DataFiles.md)               |\n| 10  | NumPy for AI                                    | [Day 10](docs/Day10_NumPyBasics.md)           |\n| 11  | Pandas for Data Analysis                        | [Day 11](docs/Day11_PandasBasics.md)          |\n| 12  | Data Cleaning and Feature Engineering           | [Day 12](docs/Day12_Data_Cleaning.md)         |\n| 13  | Data Visualization with Matplotlib \u0026 Seaborn    | [Day 13](docs/Day13_Data_Visualization.md)    |\n| 14  | Exploratory Data Analysis (EDA)                 | [Day 14](docs/Day14_EDA.md)                   |\n| 15  | Machine Learning with Scikit-learn              | [Day 15](docs/Day15_Machine_Learning.md)      |\n| 16  | Data Preprocessing and Pipelines                | [Day 16](docs/Day16_DataPipeline.md)          |\n| 17  | Linear Regression                               | [Day 17](docs/Day17_LinearRegression.md)      |\n| 18  | Logistic Regression \u0026 Classification Metrics    | [Day 18](docs/Day18_LogisticRegression.md)    |\n| 19  | Decision Trees \u0026 Entropy                        | [Day 19](docs/Day19_DecisionTrees.md)    |\n| ... | ...                                             | ...                                           |\n| 90  | Final Project \u0026 Portfolio Deployment            | Coming Soon                                   |\n\n\u003e ✅ Links will be updated here each day as you progress.\n\n---\n\n## 🧠 Why This Journey?\n\nBy the end of 90 days, you'll:\n\n* Be proficient in Python\n* Understand core AI/ML concepts\n* Build deployable real-world projects\n* Gain Git/GitHub portfolio management skills\n* Be ready to apply for AI-related roles confidently\n\n---\n\n## 🛠 Tools Used\n\n* Python 3.11+\n* Visual Studio 2022 (with Python workload)\n* Jupyter Notebooks\n* Git \u0026 GitHub Desktop\n* ML Libraries: scikit-learn, pandas, matplotlib, TensorFlow (later)\n\n---\n\n## 📬 Questions / Contributions\n\nThis journey is open-source. If you're following along or want to contribute fixes or translations, feel free to fork the repo and send pull requests!\n\nHappy Learning! 🚀\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwaqasm78%2Fai-90days","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwaqasm78%2Fai-90days","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwaqasm78%2Fai-90days/lists"}