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Udemy - Data Science with Plotly, NumPy, Matplotlib, and Pandas
Udemy - Data Science with Plotly, NumPy, Matplotlib, and Pandas

Become a Master in Data Acquisition and Visualization with Python 3 and acquire employers' one of the most requested skills of 21st Century! An expert level Data Science Professional can earn minimum $100000 (that's five zeros after 1) in today's economy.


Description

Become a Master in Data Acquisition and Visualization with Python 3 and acquire employers' one of the most requested skills of 21st Century! An expert level Data Science Professional can earn minimum $100000 (that's five zeros after 1) in today's economy.

This is themost comprehensive, yet straight-forward course for the Data Science with Python 3 on Udemy!Whether you have never worked with Data Science before, already know basics of Python, or want to learn the advanced features of Plotly and Pandas with Python 3, this course is for you! In this course we willteach you Data Science with Python 3, Jupyter, NumPy, Pandas, Matplotlib, and Plotly .

(Note, we also provide you PDFs and Jupyter Notebooks in case you need them)

Withover 120 lecturesand more than 13.5 hours of video this comprehensive course leaves no stone unturned in teaching you Data Science with Python 3, Pandas, and Plotly!

This course will teach you Data Science in a very practical manner, with every lecture comes a programming video and a corresponding Jupyter notebook that has Python 3 code! Learn in whatever manner is the best for you!

We will start by helping you get Python3, NumPy, matplotlib, Jupyter, Pandas, and Plotly installed on your Windows computer and Raspberry Pi.

We cover a wide variety of topics, including:

  • Basics of Scientific Python Ecosystem

  • Basics of Pandas

  • Basics of NumPy and Matplotlib

  • Installation of Python 3 on Windows

  • Setting up Raspberry Pi

  • Tour of Python 3 environment on Raspberry Pi

  • Jupyter installation and basics

  • NumPy Ndarrays

  • Array Creation Routines

  • Basic Visualization with Matplotlib

  • Ndarray Manipulation

  • Random Array Generation

  • Bitwise Operations

  • Statistical Functions

  • Basics of Matplotlib

  • Installation of SciPy and Pandas

  • Linear Algebra with NumPy and SciPy

  • Data Acquisition with Python 3

  • MySQLand Python 3

  • Data Acquisition with Pandas

  • Basics of Plotly

  • Configuring Charts with Plotly

  • NumPy and Plotly

  • Matplotlib and Plotly

  • Pandas and Plotly

  • Transformations with Plotly

  • Advanced visualizations with Pandas and Plotly

You will get lifetime access to over 120 lectures plus corresponding PDFs and the Jupyter notebooks for the lectures!

So what are you waiting for? Learn Data Science with Python 3 in a way that will advance your career and increase your knowledge, all in a fun and practical way!

이 강좌의 대상:
  • Data Science Professionals: Data Scientists and Data Engineers
  • AI and Machine Learning Professionals
  • Scientists, Mathematicians, Physicists, and Engineers
  • Python Developers and Programmers
  • Managers and Business Professionals
  • Anyone who wants to learn

Course content

  • Introduction
    • Audience and Prerequisites
    • Course Contents and Topics Overview
    • Please leave your feedback
    • Scientific Python Ecosystem
    • URLs to the important projects in SciPy ecosystem
  • Install and Verify Python 3 on Windows
    • Python 3 on Windows
    • Verify the installation
  • Python 3 on Raspberry Pi
    • What is Raspberry Pi?
    • Unboxing of Raspberry Pi
    • Web URLs for the download
    • Raspbian OS Installation Part 1
    • Raspbian OS Installation Part 2
    • Remote connection with VNC
    • Linux commands used in the section
    • Install IDLE3 on Raspberry Pi Raspbian
    • Python on Raspberry Pi Raspbian OS
  • Basics of Python 3
    • Hello World! on Windows
    • Hello World! on Raspberry Pi
    • Python: Interpreter mode vs Script Mode
    • IDLE
    • RPi Vs PC vs Mac
  • PyPI and pip
    • Python Package Index and pip
    • pip on Windows
    • pip3 on Raspberry Pi / Linux
  • Install NumPy and Matplotlib
    • Install NumPy and Matplotlib on a Windows Computer
    • Install NumPy and Matplotlib on Raspberry Pi
  • Jupyter Notebook
    • Jupyter and IPython
    • Jupyter on Windows
    • Jupyter on Raspberry Pi
    • Remote connection with PuTTy
    • Connecting to Remote Jupyter Notebook
    • A brief tour of Jupyter
    • Notes of Jupyter Installation and Remote Connection
  • Getting Started with NumPy
    • Introduction to NumPy
    • Ndarrays, Indexing, and Slicing
    • Ndarray Properties
    • NumPy constants
    • NumPy Datatypes
  • Creation of Arrays and Matplotlib
    • Ones and Zeros
    • Matrices
    • What is Matplotlib?
    • Numerical Rages Visualised
  • Random Sampling
    • Random Sampling
  • Array Manipulation Routines
    • Array Manipulation Routines
  • Bitwise Operations
    • Bitwise Operations
  • Statistical Functions
    • Statistical Functions
  • Plotting in detail
    • Single Line Plots
    • Multi Line Plots
    • Grid Axes and Labels
    • Color Line Markers
  • Installing SciPy and Pandas
    • Introduction to SciPy
    • Install SciPy on Windows
    • Install SciPy on Raspberry Pi
    • What is Pandas
    • Install Pandas on Windows
    • Install Pandas on Raspberry Pi
  • Matrices and Linear Algebra
    • Dot Products
    • Vector Dot Products
    • Inner Products
    • QR Decomposition
    • Determinant and Solving Linear Equations Improved
    • Linear Algebra with SciPy
  • Data Acquisition with Python, NumPy, and Matplotlib
    • Plain Text File Handling
    • CSV File Handling
    • Handling Excel File
    • NumPy file format
    • NumPy CSV File
    • Matplotlib CBook
  • Python and MySQL
    • MySQL Windows Installation
    • Getting Started with MySQL and SQL Workbench
    • Install SQL Developer on Windows
    • Connect to MySQL with SQL Developer
    • Exploring SQL Workbench
    • pymysql on Windows
    • Connect MySQL with Python 3
    • Execute DDL
    • INSERT
    • SELECT
    • UPDATE
    • DELETE
    • DROP
  • Series and DataFrame in Pandas
    • Pandas Series
    • Pandas Dataframe
  • Data Acquisition with Pandas
    • Read CSV
    • Read Excel
    • Read JSON
    • Pickles
    • Pandas and Web
    • Read SQL
    • Clipboard
  • Plotly Basics
    • Installation and Version Checking
    • Scatter Plot
    • Bubble Chart
    • Line Plots
    • Area Plots
    • Bar Charts
    • Horizontal Bar Charts
    • Gantt Chart
    • Pie Chart
    • Table Visualization
    • Multiple Visualization
  • Data Transformation
    • Filters
    • Group By
    • Aggregate
  • NumPy and Plotly
    • NumPy arrays
    • Linspace arrange and meshgrid
    • Array modification routines
    • Array Operations
    • Visualizing Random
    • 2-Norm of array
  • Plotly and Pandas
    • Scatter Plots
    • Line Charts
    • Bar Charts
    • Error Bar
    • Box Plot
    • Basic Histogram
    • 2D Histogram
    • Inset Plots
    • Gantt Chart
    • Tables
  • Downloadable Contents
    • Code Bundle - Jupyter Notebooks
    • BONUS LECTURE

Data_Science_with_Plotly__NumPy__Matplotlib__and_Pandas.part1.rar

Data_Science_with_Plotly__NumPy__Matplotlib__and_Pandas.part2.rar

Data_Science_with_Plotly__NumPy__Matplotlib__and_Pandas.part3.rar

Data_Science_with_Plotly__NumPy__Matplotlib__and_Pandas.part4.rar


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