{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[],"dockerImageVersionId":30587,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# 1. Dive into Data Science  \n\nWelcome to **[\"Dive Into Data Science\"](https://dayche.com/courses/what-is-data-science/)**!   \n\nThis course designed to provide you with a comprehensive understanding of the fundamental concepts,basic terminology, applications, and pivotal roles within the field of data science. We'll walk you through the data science process using the **CRISP-DM methology** and show you how it works in action through our real experiments.\n\nReady for hands-on data science? We'll introduce you to **ChatGPT** as your smart assistant and use **Kaggle** for running code and chatting with experts. Together, we tackle **two interactive data science problems**, gaining insights into basic statistical concepts and addressing significant challenges in data-driven problem-solving.\n\nNext up, we'll help you dive into Python quickly. This part is all about making **Python programming** easy and practical, especially for data science. With a focus on **hands-on learning**, we utilize essential data science libraries to empower you with the tools necessary for effective data analysis and problem-solving.   \n\n**[Join us](http://dayche.com/courses/what-is-data-science/)** for a fun and straightforward journey into the world of data science to get ready for an advanced courses in **statistics** and **data mining** in data science!\n> All videos in this course are **Farsi/Persian** language!","metadata":{}},{"cell_type":"markdown","source":"## Content Of Notebooks:  \n\n1. Project 1: [Prediction of drug prescription](https://www.kaggle.com/code/rouzbeh/prediction-of-drug-prescription)  \n2. Project 2: [Loan Credit Prediction](https://www.kaggle.com/code/rouzbeh/loan-credit-prediction)  \n3. Basic Programming in Python: [Dive into Python-Section 1](https://www.kaggle.com/code/rouzbeh/dive-into-python-section-1)  \nExercise: [Python-01](https://www.kaggle.com/code/rouzbeh/dids-exercise-python-01)  \n4. Data Science Libraries in Python: [Dive into Python-Section 2](https://www.kaggle.com/code/rouzbeh/dive-into-python-section-2)  \nExercise: [Python-02](https://www.kaggle.com/code/rouzbeh/dids-exercise-python-02)  \n  \n  \n\n**Final Project:** [Final Challenge-DiDS](https://www.kaggle.com/code/rouzbeh/final-challenge-dids)","metadata":{}},{"cell_type":"markdown","source":"### Guideline Map:  \n\n\n#### Next Notebook:   \n###### [Project 1: Prediction of drug prescription](https://www.kaggle.com/code/rouzbeh/prediction-of-drug-prescription)  \n\n#### Next Courses:   \n###### [2. Statistics for Data Science -->](https://www.kaggle.com/code/rouzbeh/2-statistics-for-ds-content)  \n###### [3. Data Mining and Applied Machine Learning -->](https://www.kaggle.com/code/rouzbeh/3-data-mining-applied-machine-learning-content)","metadata":{}}]}