English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 12 Hours | 5.31 GB
Learn to acquire Data with NumPy and Pandas and visualize it with Matplotlib and Altair
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 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 Altair with Python 3, this course is for you! In this course we will teach you Data Science with Python 3, Jupyter, NumPy, Pandas, Matplotlib, and Altair.
(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, Pandas, and Altair 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
- Basics of Altair and Vega Datasets
- Data Visualization with Altair
What you’ll learn
- Understand the Scientific Python Ecosystem
- Understand Data Science, Pandas, and xarray
- Learn basics of NumPy Fundamentals
- Learn Basic Visualization
- Learn Data Acquisition Techniques
- Linear Algebra and Matrices
Table of Contents
Introduction
1 Please leave your feedback
2 Scientific Python Ecosystem
3 Projects in Scientific Python Ecosystem
Python 3 on Windows
4 Python 3 Installation on Windows
5 Verify Python 3 on Windows
Python 3 on Raspberry Pi
6 What is Raspberry Pi
7 Unboxing of RPi 3B+
8 URLs for Downloads of Software
9 Raspberry Pi Raspbian OS Setup Part 1
10 Raspberry Pi Raspbian OS Setup Part 2
11 Remote Connection with VNC
12 Linux commands used in the section
13 Python 3 on Raspberry Pi
Python 3 Basics
14 Hello World on Windows
15 Hello World on Raspberry Pi
16 Interpreter vs Script
17 IDLE
18 RPi vs PC
Python Package Index and pip
19 Python Package Index and pip
20 pip on Windows
21 pip on Raspberry Pi
Install Matplotlib and NumPy on Raspberry Pi
22 Install Matplotlib and NumPy on Windows
23 Install Matplotlib and NumPy on Raspberry Pi
Jupyter Notebook
24 Jupyter and IPython
25 Jupyter Installation on Windows
26 Jupyter Installation on Raspberry Pi
27 Remote Connection with PuTTY
28 Connecting to a remote Jupyter Notebook
29 A brief tour of Jupyter
30 Jupyter Notebook Notes
Getting Started with NumPy
31 Introduction to NumPy
32 Ndarrays Indexing and Slicing
33 Ndarray Properties
34 NumPy Constants
35 NumPy Data Types
Creation of Arrays and Matplotlib
36 Ones and Zeros
37 Matrices
38 Matplotlib
39 Numerical Ranges and Visualization
Random Sampling
40 Random Sampling
Array Manipulation
41 Array Manipulation
Bitwise Operations
42 Bitwise Operations
Statistical Functions
43 Statistical Functions
Plotting in Detail
44 Single Line Plots
45 Multiline Plot
46 Grid Axes and Labels
47 Color Line Markers
Installing SciPy and Pandas
48 Introduction to SciPy
49 Install SciPy on Windows
50 Install SciPy on Raspberry Pi
51 Introduction to Pandas
52 Install Pandas on Windows
53 Install Pandas on Raspberry Pi
Matrices and Linear Algebra
54 Dot Products
55 Vector Dot Products
56 Inner Dot Products
57 QR Decomposition
58 Determinant Solving and Linear Equations
59 Linear Algebra with SciPy
Data Acquisition with Python, NumPy, and Matplotlib
60 Plain Text File Handling
61 CSV
62 Excel Files
63 NumPy File Format
64 Reading CSV File with NumPy
65 Matplotlib CBook Format
Python and MySQL
66 MySQL Installation on Windows
67 UPDATE
68 DELETE
69 DROP
70 Getting Started with MySQL and SQL Workbench
71 Connect MySQL with SQL Developer
72 Explore MySQL Workbench
73 Installing Pymysql on Windows
74 Connect to MySQL with Python 3
75 Execute DDL
76 INSERT
77 SELECT
Series and DataFrames in Pandas
78 Series
79 DataFrames
Data Acquisition with Pandas
80 Read CSV file
81 Read Excel
82 Read JSON
83 Pickles
84 Pandas and Web
85 Read SQL
86 Work with the Clipboard Data
Basic Altair Visualization
87 Installation and Basics
88 Basic Statistical Visulization
89 Encodings in Altair
A bit of Machine Learning
90 K-Means Clustering
Downloadable Code Files
91 BONUS LECTURE
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