2024 Data Visualization in Python Masterclass for Beginners

2024 Data Visualization in Python Masterclass for Beginners, available at $74.99, has an average rating of 4.47, with 224 lectures, 8 quizzes, based on 879 reviews, and has 36847 subscribers.

You will learn about Learn Complete Exploratory Data Analysis on the Latest Covid-19 Dataset Learn EDA on Kaggles Boston Housing and Titanic Datasets Learn IPL Cricket Matches and FIFA World Cup Matches Analysis and Visualization Learn Data Visualization by Plotly and Cufflinks, Seaborn, matplotlib, and Pandas Learn Interactive plots and visualization Installation of python and related libraries. Covid-19 Data Visualization Covid-19 Dataset Analysis and Visualization in Python Data Science Visualization with Covid-19 Use the Numpy and Pandas in data manipulation Learn Complete Text Data EDA Create a variety of charts, Bar Charts, Line Charts, Stacked Charts, Pie Charts, Histograms, KDE plots, Violinplots, Boxplots, Auto Correlation plots Learn Data Analysis by Pandas. Use the Pandas module with Python to create and structure data. Customize graphs, modifying colors, lines, fonts, and more Basic concepts of data visualization and its importance in data analysis How to use Python libraries such as Matplotlib, Seaborn, and Plotly to create various types of charts and plots This course is ideal for individuals who are Beginners python programmers. or Beginners Data Science programmers. or Students of Data Science and Machine Learning. or Anyone interested in learning more about python, data science, or data visualizations. or Anyone interested about the rapidly expanding world of data science! or Developers who want to work in analytics and visualization project. or Anyone who wants to explore and understand data before applying machine learning. It is particularly useful for Beginners python programmers. or Beginners Data Science programmers. or Students of Data Science and Machine Learning. or Anyone interested in learning more about python, data science, or data visualizations. or Anyone interested about the rapidly expanding world of data science! or Developers who want to work in analytics and visualization project. or Anyone who wants to explore and understand data before applying machine learning.

Enroll now: 2024 Data Visualization in Python Masterclass for Beginners

Summary

Title: 2024 Data Visualization in Python Masterclass for Beginners

Price: $74.99

Average Rating: 4.47

Number of Lectures: 224

Number of Quizzes: 8

Number of Published Lectures: 224

Number of Published Quizzes: 8

Number of Curriculum Items: 232

Number of Published Curriculum Objects: 232

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Learn Complete Exploratory Data Analysis on the Latest Covid-19 Dataset

Learn EDA on Kaggles Boston Housing and Titanic Datasets

Learn IPL Cricket Matches and FIFA World Cup Matches Analysis and Visualization

Learn Data Visualization by Plotly and Cufflinks, Seaborn, matplotlib, and Pandas

Learn Interactive plots and visualization

Installation of python and related libraries.

Covid-19 Data Visualization

Covid-19 Dataset Analysis and Visualization in Python

Data Science Visualization with Covid-19

Use the Numpy and Pandas in data manipulation

Learn Complete Text Data EDA

Create a variety of charts, Bar Charts, Line Charts, Stacked Charts, Pie Charts, Histograms, KDE plots, Violinplots, Boxplots, Auto Correlation plots

Learn Data Analysis by Pandas.

Use the Pandas module with Python to create and structure data.

Customize graphs, modifying colors, lines, fonts, and more

Basic concepts of data visualization and its importance in data analysis

How to use Python libraries such as Matplotlib, Seaborn, and Plotly to create various types of charts and plots

Who Should Attend

Beginners python programmers.

Beginners Data Science programmers.

Students of Data Science and Machine Learning.

Anyone interested in learning more about python, data science, or data visualizations.

Anyone interested about the rapidly expanding world of data science!

Developers who want to work in analytics and visualization project.

Anyone who wants to explore and understand data before applying machine learning.

Target Audiences

Beginners python programmers.

Beginners Data Science programmers.

Students of Data Science and Machine Learning.

Anyone interested in learning more about python, data science, or data visualizations.

Anyone interested about the rapidly expanding world of data science!

Developers who want to work in analytics and visualization project.

Anyone who wants to explore and understand data before applying machine learning.

Are you ready to start your path to becoming a Data Scientist!

KGP Talkie brings you all in one course. Learn all kinds of Data Visualization with practical datasets.

This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations!

This is a very unique course where you will learn EDA on Kaggle’s Boston Housing, Titanic and Latest Covid-19 Datasets, Text Dataset, IPL Cricket Matches of all seasons, and FIFA world cup matches with real and practical examples.

Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $110,000 in the United States and all over the World according to Indeed! Data Science is a rewarding career that allows you to solve some of the world’s most interesting problems!

This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!

This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 200+ Full HD video lectures and detailed code notebooks for every lecturethis is one of the most comprehensive courses on Complete Data Visualization in Python.

We’ll teach you how to program with Python, how to analyze and create amazing data visualizations with Python! You can use this course as your ready-to-go reference for your own project.

Here just a few of the topics we will be learning:

Programming with Python

NumPy with Python

Using Pandas Data Frames to solve complex tasks

Use Pandas to Files

Use matplotlib and Seaborn for data visualizations

Use Plotly and Cufflinks for interactive visualizations

Exploratory Data Analysis (EDA) of Boston Housing Dataset

Exploratory Data Analysis (EDA) of Titanic Dataset

Exploratory Data Analysis (EDA) of the Latest Covid-19 Dataset

and much, much more!

This Data Visualization in Python Masterclass can help data scientists in several ways:

It can help them gain a deeper understanding of how to effectively communicate data insights using visualizations.

It can teach them how to use Python libraries specifically designed for data visualization, making it easier for them to create visualizations in their own data analysis projects.

It can also provide them with hands-on experience working with real-world data sets, allowing them to practice creating visualizations and improve their skills.

It can also teach them to create interactive visualizations which can be used to create dashboards and reports, which can be shared with stakeholders.

It can also help them to create visualizations that can convey more information in less space, making it more effective and efficient.

Overall, this course can help data scientists to become more proficient in creating effective and engaging data visualizations, which can be used to communicate their data insights more effectively.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Welcome

Lecture 2: DO NOT SKIP IT | Introduction

Lecture 3: Q&A Support

Lecture 4: Course Overview

Lecture 5: Anaconda Installation for Windows OS

Lecture 6: Anaconda Installation for Mac OS

Lecture 7: Anaconda Installation on Ubuntu OS

Lecture 8: Jupyter Notebook Keyboard Shortcuts

Lecture 9: Jupyter Notebook Shortcuts Article

Chapter 2: Python Crash Course

Lecture 1: Introduction

Lecture 2: Data Types: Numbers

Lecture 3: Variable Assignment

Lecture 4: String

Lecture 5: List

Lecture 6: Set

Lecture 7: Tuple

Lecture 8: Dictionary

Lecture 9: Boolean and Comparison Operator

Lecture 10: Logical Operator

Lecture 11: Conditional Statements: If Else and Elif

Lecture 12: For and While Loops in Python

Lecture 13: Methods and Lambda Functions

Chapter 3: NumPy Crash Course

Lecture 1: Introduction

Lecture 2: Array

Lecture 3: NaN and INF

Lecture 4: Statistical Operations

Lecture 5: Shape, Reshape, Ravel, Flatten

Lecture 6: Sequence, Repetitions, and Random Numbers

Lecture 7: Where

Lecture 8: File Read and Write

Lecture 9: Concatenate and Sorting

Lecture 10: Working with Dates

Chapter 4: Pandas Crash Course

Lecture 1: Introduction

Lecture 2: DataFrame and Series

Lecture 3: File Reading and Writing

Lecture 4: Info, Shape, Duplicated, and Drop

Lecture 5: Columns

Lecture 6: NaN and Null Values

Lecture 7: Imputation

Lecture 8: Lambda Function

Chapter 5: Data Visualization with Pandas

Lecture 1: Introduction

Lecture 2: Data Generation

Lecture 3: Line Plot

Lecture 4: More on Line Plot

Lecture 5: Bar Plot

Lecture 6: Stacked Plot

Lecture 7: Histogram

Lecture 8: Box Plot

Lecture 9: Area and Scatter Plot

Lecture 10: Hex and Pie Plot

Lecture 11: Scatter Matrix and Subplots

Chapter 6: Matplotlib

Lecture 1: Introduction

Lecture 2: Line Plot

Lecture 3: Label

Lecture 4: Scatter, Bar, and Hist Plots

Lecture 5: Box Plot

Lecture 6: Subplot

Lecture 7: xlim, ylim, xticks, and yticks

Lecture 8: Pie Plot

Lecture 9: Pie Plot Text Color

Lecture 10: Nested Pie Plot

Lecture 11: Labeling a Pie Plot

Lecture 12: Bar Chart on Polar Axis

Lecture 13: Line Plot on a Polar Axis

Lecture 14: Scatter Plot on a Polar Axis

Lecture 15: Integral in Calculus Plot as Area Under the Curve

Lecture 16: Animation Plot Part 1

Lecture 17: Animation Plot Part 2

Chapter 7: Time Series Plots

Lecture 1: Dataset Loading

Lecture 2: Line and Scatter Plots

Lecture 3: Subplots

Lecture 4: Heatmap

Lecture 5: Histogram and KDE Plots

Chapter 8: Seaborn

Lecture 1: Introduction

Lecture 2: Scatter Plot

Lecture 3: Hue, Style and Size Part 1

Lecture 4: Hue, Style and Size Part 2

Lecture 5: Line Plot Part 1

Lecture 6: Line Plot Part 2

Lecture 7: Line Plot Part 3

Lecture 8: Subplot

Lecture 9: sns.lineplot(), sns.scatterplot()

Lecture 10: Cat Plot

Lecture 11: Box Plot

Instructors

Laxmi Kant | KGP Talkie
AVP, Data Science Join Ventures | IIT Kharagpur | KGPTalkie

Rating Distribution

1 stars: 13 votes

2 stars: 13 votes

3 stars: 68 votes

4 stars: 265 votes

5 stars: 520 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!