https://github.com/ackwolver335/pydatascience

It is a general repository that is used in order to learn Data Science with the use of Python Programming language, and here it is a course from Scratch.
https://github.com/ackwolver335/pydatascience

data-science datascientist programmer programming-language python python-script python3 pythonprogramming pythonprogramminglanguage pythonprojects

Last synced: 8 months ago
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It is a general repository that is used in order to learn Data Science with the use of Python Programming language, and here it is a course from Scratch.

• Host: GitHub
• URL: https://github.com/ackwolver335/pydatascience
• Owner: ackwolver335
• Created: 2024-10-05T12:45:58.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2024-10-24T17:30:22.000Z (11 months ago)
• Last Synced: 2024-10-24T20:18:22.202Z (11 months ago)
• Topics: data-science, datascientist, programmer, programming-language, python, python-script, python3, pythonprogramming, pythonprogramminglanguage, pythonprojects
• Language: Jupyter Notebook
• Homepage:
• Size: 68.4 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# 🏔️ Data Science with Python 🐍

**Intro** ➤ Data science is an interconnected field that involves the use of statistical and computational methods to extract insightful information and knowledge from data. Python is a popular and versatile programming language, now has become a popular choice among data scientists for its ease of use, extensive libraries, and flexibility.

⦿ This course offers expert-led instruction and hands-on projects that will help you master the tools and techniques used by data professionals. Gain practical experience and build a strong foundation to excel in your data science career

## 🖥️ Features of Data Science 🏗️

➤ **Interdisciplinary** 🖱️ Data science is an interdisciplinary field that involves using data to solve problems and gain insights.

➤ **Statistical Methods** 🖱️ Data scientists use statistical methods to analyze data.

➤ **Machine Learning** 🖱️ Machine learning is a key component of data science.

➤ **Data Visualization** 🖱️ Data visualization is an essential part of data science, as it helps to make sense of large amounts of data.

➤ **Data Cleansing** 🖱️ Data cleansing is the process of cleaning data and making it usable.

➤ **Feature Extraction** 🖱️ Feature extraction is a type of data reduction that helps to improve the accuracy of predictions.

➤ **Data Analysis** 🖱️ Data analysis is a key principle of data science.

✐ Note : Data science programs often include courses in statistics, machine learning, programming, and data visualization. Students also work on practical projects and gain hands-on experience through internships and final projects.

## 🔌 Components of Data Science 💻

- 🕹️ **Data Collection**

- 🕹️ **Data Cleansing**

- 🕹️ **Data Exploration & Visualization**

- 🕹️ **Data Modeling**

- 🕹️ **Model Evaluation and Deployment**

## 🔌 What you'll find here ❓

✇ Here, in this Repository you'll be able to learn the Basics of Data Science, together by learning them in few Days with the help of Days **Folders** from which you need to follow the pattern that will be soon available in the Wikies.

| 🤔 **Day's Schedule** | 🎁 **Data and Methods Flow** | 💻 **Go Through** |

| --------------------- | ---------------------------- | ------------------ |

| **Day1** | ➱ It contains **Basics** of Python Variables,..etc. and Installation for **PyCharm** and **Python Installation** | **[Python Basics](https://github.com/ackwolver335/pyDataScience/tree/main/Day1)** |

| **Day2** | ➱ On Day2, we'll learn **OOPs**, **Exception Handling** and other necessary concept like **JSON**,..etc. | **[Advance Concept](https://github.com/ackwolver335/pyDataScience/tree/main/Day2)** |

| **Day3** | ➱ At Day3, we'll start about **Jupyter Notebook Installation** , **Numpy** and **Pandas** Concept. | **[DataSets](https://github.com/ackwolver335/pyDataScience/tree/main/Day3)** |

| **Day4** | ➱ On the last Day, we have the concept **Matplotlib Plotting** Concept and **Visualization** Concept. | **[Visualization](https://github.com/ackwolver335/pyDataScience/tree/main/Day4)** |

## 🪄 How to Learn Data Science ❓

- **Industrial Knowledge** 🎯 : Domain knowledge in which you are going to work is necessary like If you want to be a data scientist in Blogging domain so you have much information about blogging sector like SEOs, Keywords and serializing 💻

- **Models and Logics Knowledge** 🎯 : All machine learning systems are built on Models or algorithms, its important prerequisites to have a basic knowledge about models that are used in data science ⌨️

- **Computer and Programming Knowledge** 🎯 : Not master level programming knowledge is required in data science but some basic like variables, constants, loops, conditional statements, input/output, functions 💻

- **Mathematics Used** 🎯 : It is an important part in data science. There is no such tutorial presents but you should have knowledge about the topics : mean, median, mode, variance, percentiles, distribution, probability, bayes theorem and statistical tests like hypothesis testing, Anova, chi squre, p-value ⌨️

## 🖥️ Applications of Data Science 🛅

✩ **HeathCare** ➵ Healthcare industries uses the data science to make instruments to detect and cure disease.

✩ **Image Recognition** ➵ The popular application is identifying pattern in images and finds objects in image.

✩ **Internet Search** ➵ To show best results for our searched query search engine use data science algorithms. Google deals with more than 20 petabytes of data per day. The reason google is a successful engine because it uses data science.

✩ **Advertising** ➵ Data science algorithms are used in digital marketing which includes banners on various websites, billboard, posts etc. those marketing are done by data science. Data science helps to find correct user to show a particular banner or advertisement.

✩ **Logistics** ➵ Logistics companies ensure faster delivery of your order so, these companies use the data science to find best route to deliver the order.

## 🤝🏻 Support Me 🗿

**If you likes what I do and wants to support me** 🫣

- Give a ✴️ to my Repo.

- Share 🔊 my work with your network 🌐

➱ Everyone, visiting these helpful notes or information, its owner's humble request to please provide the feedback in the Discussion Page of our Repo for making more better improvement in our learning Resources.

➱ [Click](https://github.com/ackwolver335/pyDataScience/discussions) here to visiting discussion center.

Thanks for visiting my Repository, hope you find it useful. Let's [connect](https://github.com/ackwolver335) and collaborate for building 🏗️ something amazing 🗿