The Complete Data Analysis Course 2022 With Python

Learn and how to use python to analyse, visualize and present data with many challenges, projects and one big assignment

What you'll learn
Matplotlib
Bokeh
Numpy
Pandas
Database connection
Slider
Hover
Plotly
Brown
FreqDist
Pos_tag
Spacy
WordCloud
NLTK
Mapper
Requirements
Solid Python Knowledge
Description
This course will give you the resources to learn python and effectively use it to analyze and visualize data! Start your career in Data Analysis!You'll get a full understanding of how to program with Python and how to use it in conjunction with scientific computing modules and libraries to analyse data.You will also get lifetime access to many example python code notebooks, new and updated videos, as well as future additions of various data analysis projects that you can use for a portfolio to show future employers!This course covers a variety of topics, includingGoogle ColabKeras.Pandas.Seaborn.Matplotlib.scikit-learnNLTK.Tokenization.Spacy.PoS tagging.Stemming and lemmatization.Loading data.Analyzing data.Visualizing data.Bokeh.Plotly.Mapper.WordCloud.Hover.Slider.FreqDist.MatplotlibMoreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models. There is an assignment for you to learn and practice all the tools and knowledge that you will learn throughout the course.By the end of this course you will:- Have an understanding of how to program in Python.- Know how to create and manipulate arrays using NumPy and Python.- Know how to use pandas to create and analyze data sets.- Know how to use matplotlib and seaborn libraries to create beautiful data visualization.- Have an amazing portfolio of example python data analysis projects!- Have an understanding of Machine Learning and SciKit Learn!

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 How to make the most out of this course

Lecture 3 Introduction to Data Analyis

Lecture 4 Introduction to Data Science

Section 2: Database Connection Using Python

Lecture 5 Introduction to SQL and Implementation

Section 3: Data Wrangling with Python

Lecture 6 Introduction to Data Wrangling

Lecture 7 Data Wrangling Implementation Part 1

Lecture 8 Data Wrangling Implementation Part 2

Lecture 9 Data Wrangling Implementation Part 3

Lecture 10 Filling missing values and handling outliers Implementation

Lecture 11 Introduction to Data Frame Connection and Implementation

Lecture 12 Introduction and Implementation of Apply function in Pandas Library

Section 4: Data Visualization with Python

Lecture 13 Creating fundamental plots with Pandas and seaborn

Lecture 14 Introduction to bar plot and implemetation

Lecture 15 Advanced bar plot and implementation

Lecture 16 Project 2: Sport

Lecture 17 Advanced Visualization with Python Part 1

Lecture 18 Advanced Visualization with Python Part 2

Lecture 19 Advanced Visualization with Python Part 3

Lecture 20 Advanced Visualization with Python Part 4

Lecture 21 Advanced Visualization with Python Part 5

Lecture 22 Another Practice with Plotly

Section 5: Text Analysis With Python

Lecture 23 Introduction

Lecture 24 Text Analysis Implementation Part 1

Lecture 25 Text Analysis Implementation Part 2

Lecture 26 Text Analysis Implementation Part 3

Lecture 27 Text Analysis Implementation Part 4

Lecture 28 Text Analysis Implementation Part 5

Lecture 29 Text Analysis Implementation Part 6

Lecture 30 Text Analysis Implementation Part 7

Lecture 31 Text Analysis Implementation Final Part

Section 6: Thank you

Lecture 32 Thank you

You should take this course if you want to become a Data Scientist or if you want to learn about the field,This course is for you if you want a great career,The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills

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