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December 2024
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Data Analysis, Simulation, Visualization And Exploration

Posted By: ELK1nG
Data Analysis, Simulation, Visualization And Exploration

Data Analysis, Simulation, Visualization And Exploration
Published 12/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 6.21 GB | Duration: 16h 22m

A deep dive in data analysis, simulation and visualization for Data Science, Machine Learning and Business Students

What you'll learn

Masters Python Data Types and Numpy

A deep dive in Pandas library for learning Data Analysis techniques

Masters Matplotlib, most powerful Python library for data plotting and visualization

Learn advanced customization like subplots, styling, and object oriented programming with Matplotlib

A deep dive in Seaborn, a library for Data Visualization and Inference.

Learn Scatterplots, Categorical Plot, Distribution Plots, Comparison plots, Seaborn Grids, Pie plots Matrix plots,

Learn Data and Visual Analytics by completing a project

Monte Carlo Simulations and Visualization with lots of Experiments and Exercises

Learn to Create and Visualize different time series data such as impulse , square, triangular , sinusoidal , and synthetic time series to mimic real world data.

Learn to create images and draw different shapes on images such as lines, edges, corners, rings, circles

Learn how to create your own custom image dataset

Requirements

High school mathematics is recommended but not necessary

Description

DescriptionThis is a complete and comprehensive course on Data Analysis, Simulation, Visualization and Exploration. It is hands-on course design to make you expert by solving projects and exercises by using Python’s most important packages and libraries such NumPy, Pandas, Matplotlib and Seaborn.Course OutlineNumPy and Python RefresherIn this section of the course, we learn basic and fundamentals of python. If you don’t know anything about the python, even then you do not need to worry about, this section will provide you all the fundamentals.Pandas ( Data Analysis )In this section we deep dive into Pandas to learn Pandas Series, Pandas Data Frames, groupby method, pivot table, conditional filtering with Pandas, Combining Data Frames and Other advanced data analysis techniquesMatplotlib ( Data Plotting and Visualization )We learn everything of Matplotlib from fundamental to advanced. We learn how to customize the figures and plots from 1D to 3D.Seaborn ( Data Visualization and Inference )In this section, we dive deep into Seaborn. It is the most important Visualization package for data visualization Inference. It provides the plots, charts and visualization in such manners that other than visualizing we can also infer the statistical information from the data such as the data distribution, mean, median, Interquartile range etc.Project ( Data and Visual Analytics )After learning Pandas, Matplotlib and Seaborn, now its time to do a project that require the knowledge from above three sections. In this section you will have to solve the project to get expertise in Data Analysis and Visualization.Montecarlo Simulations and VisualizationWe Perform Monte Carlo Simulation when we are not sure about the outcome of some process. In this section we perform several experiments of Montecarlo Simulations and then at the end you will solve exercise to solidify your conceptsTime Series Generation and VisualizationTime Series is a very important type of data with numerous practical applications. In this section you will learn how to create different types of time series data. At the end of this section, you will solve an exercise to get command on time series generation and visualizationImage Creation and VisualizationImage is another very import data type. This section is dedicated to make you understand how to create your own color and gray scale images. We will also learn how to draw lines, edges, corners, rings and circles on the images. We will also learn how to create our own custom image dataset. At the end of this section, you will solve an exercise to get the full understanding of image creation and visualization

Overview

Section 1: Introduction of the Course

Lecture 1 Introduction

Lecture 2 Course Material

Lecture 3 How to succeed in this course

Section 2: Introduction to Google Colab

Lecture 4 Introduction of the section

Lecture 5 Mounting the drive and reading dataset

Lecture 6 Mounting the drive and reading, displaying an image

Lecture 7 Reading More datasets

Lecture 8 Uploading Course Material to Google Drive

Section 3: NumPy and Python Refresher

Lecture 9 Introduction of the section

Lecture 10 Arithmetic Operations With Python

Lecture 11 Comparison and Logical Operators

Lecture 12 Conditional Staements

Lecture 13 NumPy Part01 : Creating Arrays

Lecture 14 NumPy Part02 : Methods and Attributes

Lecture 15 NumPy Part03 : Indexing and Slicing

Lecture 16 NumPy Part04 : Broad Casting With NumPy Arrays

Lecture 17 Lists in Python

Lecture 18 For Loop Part01

Lecture 19 For Loop Part02

Lecture 20 While Loop

Lecture 21 Strings in Python

Lecture 22 Print Formatting With Strings

Lecture 23 Dictionaries Part01

Lecture 24 Dictionaries Part02

Lecture 25 Functions in Python Part01

Lecture 26 Functions in Python Part02

Lecture 27 Tuples

Lecture 28 Lambda function

Lecture 29 Map function

Lecture 30 Reduce function

Lecture 31 Filter function

Lecture 32 Zip function

Lecture 33 Join function

Section 4: Pandas ( Data Analysis )

Lecture 34 Introduction of the section

Lecture 35 Creating Pandas Series

Lecture 36 Operations on Pandas Series

Lecture 37 Creating Pandas Data Frame

Lecture 38 Working with rows and columns of Data Frames

Lecture 39 Dealing with missing values

Lecture 40 Pandas Filtering

Lecture 41 Pandas Methods Part01

Lecture 42 Pandas Methods Part02

Lecture 43 Combining Data Frames

Lecture 44 Pandas groupby method

Lecture 45 Pandas Multilevel Indexing

Lecture 46 Pandas date time method part01

Lecture 47 Pandas date time method part02

Lecture 48 Pandas Pivot table

Section 5: Matplotlib ( Data Plotting and Visualization )

Lecture 49 Introduction of the section

Lecture 50 First plot with Matplotlib

Lecture 51 Two plots on same figure

Lecture 52 Changing the color of the line of plot

Lecture 53 Changing the size of the figure

Lecture 54 Changing the width of the line of plot

Lecture 55 Label the axes of the plot

Lecture 56 Adding legend and title to the plot

Lecture 57 Setting limits for X-axis and Y-axis of the plot

Lecture 58 Adding ticks on X-axis and Y-axis

Lecture 59 Changing line style and adding more customizations

Lecture 60 Setting styles with Matplotlib

Lecture 61 Subplotting in Matplotlib

Lecture 62 rc Parameters of Matplotlib

Lecture 63 Creating Figure Object - OOP in Matplotlib

Lecture 64 Subplotting with figure object

Lecture 65 Advanced Matplotlib Plots Part01

Lecture 66 Advanced Matplotlib Plots Part02

Section 6: Seaborn ( Data Visualization and Inference )

Lecture 67 Introduction of the section

Lecture 68 Scatter plots

Lecture 69 Scatter plots in Seaborn

Lecture 70 Distribution Plots

Lecture 71 Distribution plots in Seaborn Part01

Lecture 72 Distribution plots in Seaborn Part02

Lecture 73 Categorical Plots

Lecture 74 Categorical plots ( countplot and barplot in Seaborn )

Lecture 75 Categorical plots ( boxplot and violin plot in Seaborn )

Lecture 76 Categorical plots ( swarmplot and boxenplot in Seaborn )

Lecture 77 Comparison plots ( jointplot and pairplot in Seaborn )

Lecture 78 Seaborn Grids

Lecture 79 Matrix Plots ( heatmap and cluster map in Seaborn )

Lecture 80 Linear Model ( lm ) plots in Seaborn

Lecture 81 Pieplot

Section 7: Project ( Data and Visual Analytics )

Lecture 82 Project Exercise Overview

Lecture 83 Project Exercise Solution Part01

Lecture 84 Project Exercise Solution Part02

Section 8: Monte Carlo Simulations and Visualization

Lecture 85 Introduction of the section

Lecture 86 Flipping a coin and pair of coins

Lecture 87 Monte Carlo Simulations - Flipping a single coin

Lecture 88 Monte Carlo Simulations : Flipping a pair of coins

Lecture 89 Rolling a die and pair of dice

Lecture 90 Monte Carlo Simulations - Rolling a single die

Lecture 91 Montecarlo Simulations-Rolling a Pair of die and getting two sixes

Lecture 92 Montecarlo Simulations-Rolling a Pair of die and getting two after six

Lecture 93 Exercise 01-Overview

Lecture 94 Exercise 01-Solution

Lecture 95 Exercise 02-Overview

Lecture 96 Exercise 02-Solution

Section 9: Time Series Generation and Visualization

Lecture 97 Introduction of the section

Lecture 98 Impulse series

Lecture 99 Generating and Visualizing Impulse Series

Lecture 100 Generating and Visualizing Square Wave Series

Lecture 101 Generating and Visualizing Triangular Series

Lecture 102 Sinusoidal Time Series

Lecture 103 Generating and Visualizing Sinusoidal Time Series

Lecture 104 Exponential Time Series

Lecture 105 Generating and Visualizing Exponential Time Series

Lecture 106 Generating and Visualizing Chirp Time Series

Lecture 107 Generating and Visualizing Synthetic Time Series

Lecture 108 Exercise Overview

Lecture 109 Exercise Solution

Section 10: Image Creation and Visualization

Lecture 110 Introduction of the section

Lecture 111 Image Fundamentals with NumPy and Matplotlib

Lecture 112 Line, Edge and Corner of an image

Lecture 113 Drawing and Visualizing line on an image

Lecture 114 Creating and Visualizing Edge and Corner on an image

Lecture 115 Creating and Visualizing Ring and Circle on the image

Lecture 116 Creating our own custom image dataset containing 4000 images

Lecture 117 Exercise Overview

Lecture 118 Exercise Solution

Section 11: Bonus Lecture

Lecture 119 Introduction

Data Scientists who want to learn data analysis and visualization tools,Any one who wants to learn how to simulate and visualize data,Anyone who wants to improve Python Programming skills,Engineers,Statisticians,Computer Scientists,Business Analysts