Complete Python 3 and Pandas Data Science Masterclass

Complete Python 3 and Pandas Data Science Masterclass

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 15 Hours | 6.54 GB

Learn Data Acquisition, Analysis, and Visualization with Python 3, NumPy, Pandas, and Matplotlib in a single course

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

This is the most 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 Pandas with Python 3, this course is for you! In this course we will teach you Pandas with Python 3, Jupyter, NumPy, and Matplotlib.

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

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, and Pandas 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
  • MySQL and Python 3
  • Data Acquisition with Pandas
  • Data Cleaning with Pandas
  • Working with Data using Pandas
  • Plotting with Pandas
  • Pandas visualization with Seaborn, bokeh, and ggplot

What you’ll learn

  • Understand the Scientific Python Ecosystem
  • Understand Data Science and Pandas
  • Learn basics of NumPy Fundamentals
  • Learn Basic Visualization
  • Learn Data Acquisition Techniques
  • Linear Algebra and Matrices
Table of Contents

Introduction
1 Course Objective, Prerequisite, and Audience
2 Course Contents and Overview
3 Please leave your feedback for this course
4 Introduction to the Scientific Python Ecosystem
5 URLs to the important projects in the Scientific Python Ecosystem

Python 3 Setup on Windows Computer
6 Python 3 Installation on Windows Computer
7 Verify Python 3 Setup on Windows Computer

Python 3 on Raspberry Pi
8 What is Raspberry Pi?
9 Unboxing of Raspberry Pi
10 Web URLs for Downloads
11 Raspberry Pi Raspbian OS Setup Part 1
12 Raspberry Pi Raspbian OS Setup Part 2
13 Remotely Connect to the Raspberry Pi from Windows Computer with VNC
14 Linux Commands used in this section
15 A brief tour of Python Environment on Raspberry Pi Raspbian OS

Basics of Python 3
16 Hello World! Program on Windows
17 Hello World! on Raspberry Pi
18 Interpreter vs Script Mode
19 IDLE for Python
20 Raspberry Pi vs a Custom built PC

Python Package Index and pip
21 PyPI and pip
22 pip on Windows Computer
23 pip3 on Raspberry Pi Raspbian OS

Installing NumPy and Matplotlib
24 Installing NumPy and Matplotlib on Windows
25 Installing NumPy and Matplotlib on Raspberry Pi

Jupyter Notebook
26 Jupyter and IPython
27 Jupyter Installation on Windows
28 Jupyter Installation on Raspberry Pi
29 Connect to Raspberry Pi from Windows Computer using PuTTY
30 Remote connection to Jupyter Notebook
31 A brief tour of Jupyter Notebook
32 Downloadable Notes

Getting Started with NumPy
33 Introduction to NumPy
34 Ndarrays, Indexing, and Slicing
35 Ndarray Properties
36 NumPy Constants
37 NumPy Datatypes

Creation of Arrays and Matplotlib
38 Ones and Zeroes Improved
39 Matrices Improved
40 Introduction to Matplotlib
41 Numerical Ranges and Visualizations

Random Value Generation
42 Random Value Generation

Ndarray manipulation
43 Ndarray manipulation

Bitwise Operations
44 Bitwise Operations

Statistical Functions
45 Statistical Functions

Matplotlib Plotting in Detail
46 Single Line Plots
47 Multiline Plots
48 Grid, Axes, and Labels
49 Color Line Markers

Installing SciPy and Pandas
50 What is SciPy
51 Install SciPy on Windows
52 Install SciPy on Raspberry Pi
53 Introduction to Pandas
54 Install Pandas on Windows Computers
55 Install Pandas on Windows Raspberry Pi

Matrices and Linear Algebra
56 Dot Products
57 Vector Dot Product
58 Inner Product
59 QR Decomposition
60 Determinant and Solving Linear Equations
61 Linear Algebra with SciPy

Data Acquisition with Python, NumPy, and Matplotlib
62 Read a plaintext file with Python 3
63 Reading a CSV file
64 Read Spreadsheets with Python 3
65 Saving NumPy data into a file
66 Read a CSV file with NumPy
67 Matplotlib CBook

Python and MySQL
68 MySQL Installation
69 Getting Started with MySQL and SQL Workbench
70 MySQL and SQL Developer
71 Explore MySQL Workbench
72 Install pymysql on windows
73 Connect to MySQL with Python 3
74 Execute DDLs
75 INSERT with Python
76 SELECT with Python
77 UPDATE with Python
78 DELETE with Python
79 DROP tables with Python

Pandas Series and DataFrame
80 Series
81 DataFrame

Data Acquisition with Pandas
82 CSV
83 Excel
84 Read JSON
85 Pickles
86 Web and HTML
87 SQL
88 Clipboard Data

Data Cleansing
89 Data Cleansing

Data Analysis and Wrangling with Pandas
90 Hierarchical Indexing
91 More Data Science with pandas
92 Relational Database Style Joins with Dataframes
93 Merge on Index
94 Group By and Aggregation

Data Visualization with Pandas
95 Visualization Part 1
96 Visualization Part 2
97 Visualization Part 3

Data visualization with Seaborn
98 Datasets in Seaborn
99 Visualizations in Seaborn
100 Visualizing Regression in seaborn

A complete data Science example
101 A complete data Science example

A bit of machine learning
102 K Means Clustering

Advanced Pandas
103 Concat Along Axis
104 Combine with Overlap
105 Work with Strings and Text Data
106 Panels Data Structure in Pandas

Times Series in Pandas
107 Introduction
108 Shifting and Timezone

Downloadable Code Bundle
109 Downloadable Code Bundle
110 BONUS LECTURE