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Copy file name to clipboardExpand all lines: README.md
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# Learn Python for Data Analysis for Beginners to Advanced.
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## Motivation
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# Learn Python for Data Analysis
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I am building this repository for study purposes. I am on the journey to become a Data Analyst, and I want to share what I have learned along the way.
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## Prerequisites
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1. Python 3.x
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1. Python 3.x version
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2. Git is installed and you know basics of [git commands.](git/git-basic-commands.md)
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3. Have access to terminal/command line.
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3. Have access and know [how to use terminal/command line.](cms/cms-basic-commands.md)
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## List of Content
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## About the Content
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The content of this repository is organized by levels. First, we start with basic programming concepts using Python. Next, we delve into the world of data analysis and its theories. Finally, we bring everything together and start exploring Python for data analysis. For each section, we will complete at least one project.
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7. Loops, Condititionals, Methods and Functions.
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8. Modules, Packages, Built-in Functions and File handling.
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### Intro Project
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1.
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### Python Basic Level
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1. Oriented Object Programming.
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2. Math and Numpy.
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3. Data handling with Pandas.
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4. Data Visualization with Matplotlib and Seaborn.
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### Basic Project
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1.
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### Python Intermediary Level
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1. Data Analysis with Statsmodel.
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4. Deep Learning with TensorFlow.
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5. Reinforcement Learning.
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### Intermediary Project
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1.
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### Data Analysis
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1. What are Data? Why should we care about it?
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Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides.
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