Python Data Course- Python for Data Analysis Visualization

Python Data Course: Python for Data Analysis & Visualization, available at $54.99, has an average rating of 4.3, with 68 lectures, based on 104 reviews, and has 20147 subscribers.

You will learn about What is Python libraries or modules & how to use its methods? How to use Numpy + pandas in data Analysis And data Science. How to use Python to manipulate & process data. Data analysis & data visualization using Python. This course is ideal for individuals who are Are you want to learn more about Python data libraries Methods & Functions? or Are you want to learn more about Data Analysis using Python libraries? or Are you want to learn more about Pandas + Numpy? It is particularly useful for Are you want to learn more about Python data libraries Methods & Functions? or Are you want to learn more about Data Analysis using Python libraries? or Are you want to learn more about Pandas + Numpy?.

Enroll now: Python Data Course: Python for Data Analysis & Visualization

Summary

Title: Python Data Course: Python for Data Analysis & Visualization

Price: $54.99

Average Rating: 4.3

Number of Lectures: 68

Number of Published Lectures: 68

Number of Curriculum Items: 68

Number of Published Curriculum Objects: 68

Original Price: $59.99

Quality Status: approved

Status: Live

What You Will Learn

What is Python libraries or modules & how to use its methods?

How to use Numpy + pandas in data Analysis And data Science.

How to use Python to manipulate & process data.

Data analysis & data visualization using Python.

Who Should Attend

Are you want to learn more about Python data libraries Methods & Functions?

Are you want to learn more about Data Analysis using Python libraries?

Are you want to learn more about Pandas + Numpy?

Target Audiences

Are you want to learn more about Python data libraries Methods & Functions?

Are you want to learn more about Data Analysis using Python libraries?

Are you want to learn more about Pandas + Numpy?

The key to success in data science is understanding the data at hand. In this comprehensive course, we’ll teach you everything you need to know about data analysis and data science using Python. You’ll learn how to use Python libraries like Numpy and Pandas to manipulate and process data, and how to visualize your findings for maximum impact.

Whether you’re a beginner or an experienced data scientist, this course will take you from the basics of Python to advanced techniques in data analysis. You’ll learn how to install Python, use Python IDEs, and create Python modules. You’ll also learn how to use Numpy and Pandas to manipulate data, process images, and perform data analysis and visualization.

With step-by-step examples and hands-on exercises, you’ll gain practical knowledge and skills that you can apply to real-world data science problems. By the end of this course, you’ll have a solid understanding of Python and be able to write Python code to analyze, process, and visualize data.

What you will learn in this course:

– Learn Python fundamentals step by step, from installation to syntax to IDEs.

– Use Numpy and Pandas libraries to manipulate and process data.

– Understand different data types and how to work with them in Python.

– Create Python modules and use them to open and manipulate files.

– Perform data analysis and visualization with Numpy and Pandas.

– Process images using Numpy libraries.

– Handle errors and use control flow and loops to optimize your Python programs.

This comprehensive course is perfect for anyone looking to learn data science and Python programming. With these tutorials, you’ll go from beginner to pro under the guidance of an experienced data science instructor.

The hands-on projects and exercises will give you practical experience in:

– Importing, cleaning, and wrangling datasets using Pandas

– Statistical analysis and machine learning with Numpy

– Creating insightful data visualizations with Matplotlib

– Building end-to-end data pipelines and Python scripts

These are the exact skills top companies like Google, Facebook, and Microsoft are looking for in data professionals.

Learning by doing is the best way to master new skills. This course provides you with downloadable datasets, Python code templates, mini-projects and more to actively practice as you learn. With our expert instructor guiding you, you’ll be ready for a career in data in no time!

If you want to future-proof your career and break into the exciting world of data science, Python is a must-have skill. Enroll in this best-selling course and start your journey today!

Course Curriculum

Chapter 1: Python Environment Preparing

Lecture 1: Introduction

Lecture 2: Environment Preparing for Python

Lecture 3: Python2 VS Python3

Lecture 4: Understanding Data Types in Python

Chapter 2: Python Refresher

Lecture 1: Variables, Operators and Data Types in Python

Lecture 2: String Functions in Python.

Lecture 3: Data Structures in Python.

Lecture 4: Control Flow VS Loops.

Lecture 5: Error Handling in Python.

Lecture 6: Functions in Python.

Lecture 7: Files and Modules in Python.

Chapter 3: Object Oriented Programming (OOP) In Python

Lecture 1: Creating Simple Class.

Lecture 2: Overviewing Constructor.

Lecture 3: Learning How to creating Dunder Methods?

Lecture 4: Learning about Inheritance.

Lecture 5: Knowing What is the Encapsulation?

Lecture 6: Learning also about Multiple Inheritance.

Lecture 7: Knowing What is the Overriding?

Lecture 8: Learning about Decorators.

Lecture 9: Learning How to use Build-in Decorators?

Chapter 4: Refresher Project 1

Lecture 1: Project 1 Walk through

Lecture 2: Project 1 Helpful Notes

Lecture 3: Project 1 Solution

Chapter 5: Refresher Project 2

Lecture 1: Project Walk through

Lecture 2: Project Helful Notes

Lecture 3: Project Solution Part 1

Lecture 4: Project Solution Part 2

Chapter 6: Refresher Project 3

Lecture 1: Project Walk Through

Lecture 2: Project Helpful Notes

Lecture 3: Project Solution

Chapter 7: Data Analysis Process.

Lecture 1: Data Analysis Process

Chapter 8: Python Numpy

Lecture 1: 1. Numpy Intro

Lecture 2: 2. Numpy.shape & Numpy.size

Lecture 3: 3. Creating Numpy nd arrays using Numpy functions

Lecture 4: 4. Numpy.unique( ) & Array slicing

Lecture 5: 5. Numpy Calculations and Operators.

Lecture 6: 6. Numpy Aggregations

Lecture 7: 7. Numpy Reshape and Transposing

Lecture 8: 8. Numpy Comparing

Lecture 9: 9. Numpy Images Processing

Chapter 9: Python Pandas Data Analysis & Visualization

Lecture 1: Installing Jupyter Lab & Pandas

Lecture 2: SQL PostgreSQL Down and install

Lecture 3: Database Creation

Lecture 4: Database Restore

Lecture 5: Using Python Pandas Package to load PostgreSQL the Data Output file

Lecture 6: Fetchmany and Fetchall

Lecture 7: Querying Using Python Panadas

Lecture 8: Pandas methods and functions

Lecture 9: Visualizing Data

Lecture 10: Pandas Data Analysis

Lecture 11: Sampling Error

Chapter 10: Web Scraping & Data Analysis Using Python & SQL.

Lecture 1: How to Scrape a website in Python?

Lecture 2: Scrape a Table inside a Webpage using Pandas and LXML Python Modules!

Lecture 3: Data Visualization of the Scraped Data.

Lecture 4: Save The Scraped Data to a Database.

Chapter 11: Project 4: Using Pandas + Automation to Manage a Business Email List.

Lecture 1: Part 1

Lecture 2: Part 2

Lecture 3: Part 3

Chapter 12: Project 5: Google App Data Analysis.

Lecture 1: 1. Visual Exploring of Google App Store Data.

Lecture 2: 2. Data Cleaning and Preprocessing of Google App Store Data.

Lecture 3: 3. Data Visualization Techniques.

Lecture 4: 4. Statistical Analysis and Hypothesis Testing.

Lecture 5: 5. Data Storytelling.

Lecture 6: 6. Conclusion.

Chapter 13: Using ChatGPT and Generative AI Assistance for Data.

Lecture 1: Generative AI for Data Analysis.

Lecture 2: Generative AI for Data Science.

Lecture 3: GEN AI Most Used Prompts for Data Analyst & Data Scientists.

Chapter 14: Thanks

Lecture 1: Bonus

Instructors

Temotec Learning Academy
Professional Developer & Programmer love teaching.

Rating Distribution

1 stars: 7 votes

2 stars: 5 votes

3 stars: 16 votes

4 stars: 42 votes

5 stars: 34 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!