Hello and welcome to the video course Master Pandas and Python for Data Handling! 2
This video course is a two video courses in one 3
video course aimed at learning you data handling, 4
the Python programming language, and to use 5
the Pandas library which is the world's most 6
powerful software for data handling and built on the Python programming language. 7
In this video course you will learn to master 8
the Python programming language with its native 9
building blocks and powerful object oriented 10
programming and to use it for data science and machine learning data handling tasks. 11
You will learn to master the powerful Pandas library, 12
and to use super effective data science and machine learning data handling techniques. 13
My name is Henrik Johansson and I am the 14
instructor for this course. In the next minutes 15
you will be informed about what you will learn, 16
the intended target audience for this course, 17
your expected workload, the course requirements, 18
I will give you a short instructor introduction, 19
and you will receive some information about Udemy's grading system. 20
This course has two sections and the first section will teach you to master the Python 21
programming language with the perspective of data handling. 22
The short story about technical data handling is that data handling is about 23
moving and transforming data to usable forms and structures. 24
Data scientists and machine learning engineers spends about 80 percent 25
of their working effort and time on data handling tasks. 26
Python is the top choice for data handling 27
and being good at data handling and Python programming are extremely useful and time 28
saving skills. The second section of this video 29
course will teach you to master the Pandas 30
library with the perspective of data handling. 31
The pandas library is the currently best and most 32
efficient, useful and powerful data handling 33
software in the world. But the pandas library 34
is more than just data handling, it is the world's 35
most powerful data storage, spreadsheet and data 36
handling software. With the pandas library you 37
get a fast, powerful, flexible and easy to use, 38
open source data analysis and data manipulation 39
tool which is directly usable with the Python 40
programming language and you will be able to use 41
any data source with incredibly powerful Pandas 42
DataFrame object. In the first section of this video course you will learn to master 43
Python's native building blocks and Python's advanced object-oriented parts. 44
You will learn to use Python's native data structures, 45
data transformers, functions, object orientation, 46
and logic, and you will learn to move data between file formats and data structures. 47
You will learn to use and design your own 48
advanced constructions of these building blocks 49
and to execute detailed data handling tasks with 50
limited assistance from file handling libraries and 51
the matplotlib library. You will learn to make 52
your own custom functions, your own custom objects 53
and to use Python's advanced object-oriented 54
programming, plus learn how to generalize 55
functions and you will learn to manipulate data 56
and to use advanced multi-dimensional uneven data structures. 57
Compared to university courses in computer engineering or system sciences, 58
this section of the course will propel you to 59
about the general one years of studies level with 60
respect to programming and the general master or 61
researcher level with respect to data handling. 62
In the second section of this course you will learn 63
to master the Pandas library for data handling. 64
You will learn the language and fundamental 65
concepts of the Pandas library and to handle 66
all aspects of the Pandas dataframe object plus 67
file handling to and from a DataFrame object. 68
You will learn to execute operations and 69
techniques such as combining DataFrames with 70
functions and methods such as the concat function, and the join and merge methods. 71
You will learn advanced data preparation including 72
advanced model-based imputation of missing data 73
and you will learn to scale and standardize your data. 74
You will learn to make data description with Pandas from ranking and sorting to 75
cross tabulations, groupings and descriptive statistics. 76
As a bonus, the course includes a large set of bonus videos which will teach 77
you how to make advanced data visualizations 78
with the Pandas, matplotlib, cand seaborn libraries. 79
Compared to university courses in computer 80
engineering or system sciences, this section 81
of the course will propel you to the general 82
master or researcher level with respect to data handling. 83
In practice this means that after you have 84
completed this course you will be as knowledgeable 85
in data handling as any doctor or master student leaving their university. 86
This will make you very attractive for employment in particular within research, 87
science, academies, government and business. 88
If you are an academic student or want to 89
become an academic student, this course is the ultimate course to give you 90
attractive, useful and time-saving skills to enhance and augment your career. 91
This course is an excellent entrance to learn the python programming language 92
and the pandas library and in practice this 93
course is the course we ourselves would want 94
to be able to enroll in if we could time travel 95
and re-enter the university as new students. 96
In our opinion, this course is the best course 97
to learn the python programming language, 98
the Pandas library and to learn effective data handling. 99
For this course, Henrik Johansson will be your instructor. Henrik has a broad 100
instructor and leadership experience with more 101
than 20 years in roles ranging from university 102
teacher within the most mathematically advanced 103
courses in data mining and statistics to 104
sports coach and leadership roles in the private 105
and public sectors. Henrik has experience 106
teaching students from all walks of life, from 107
the poor to the royalty, and has taught students 108
from nearly all educational backgrounds from high school students to doctors. 109
This course is an excellent choice for anyone who 110
wants to learn the Python programming language. 111
This course's first section provides an 112
excellent package about Python's fundamental part 113
and propels you to the intermediate level of 114
Python programming even if you start from scratch. 115
Reaching this intermediate level is important 116
as many courses and jobs require intermediate or 117
master knowledge of Python programming. 118
This course is also an excellent choice for anyone 119
who wants to master Pandas for data handling. 120
You get to learn everything from A to Z 121
in an updated package without any depreciated videos. 122
This course is also excellent for anyone who 123
knows data science or machine learning and 124
want to learn data handling skills that work as a 125
force multiplier with the skills you already know. 126
The stuff you learn in this course is seldom 127
taught at universities except in several highly 128
specialized and separate courses, often divided 129
into many different disciplines and seldom even 130
being available in a single university, if at all. Knowing the content of this course 131
will make you so much better and so much faster at your work. 132
This course is also beneficial for anyone who wants to study at the university 133
level and want to learn data handling skills 134
that they will have use for in their entire careers. 135
Demonstrating effective and impressive 136
data handling skills will make most academics very 137
interested in having you on the research team. 138
This course is simply the best course to learn 139
Python, Pandas, and effective data handling and in 140
practice this course is the course we ourselves 141
would want to be able to enroll in if we could 142
restart our studies. Now we'll talk about the 143
expected time consumption and workload of this course. 144
I will begin to say that while listening to all of the course materials is an exciting 145
18 to 30 hours endeavor and the main exercise 146
for the course is to replicate the code, 147
and this may take about twice or three times the time to listen to the course. 148
To sum it up: the total workload for the course 149
is less than 18 to 80 hours depending on your 150
decision to replicate the code, to listen to the 151
entire course, or to cherry-pick from the contents useful and interesting to you. 152
The more you already know the faster all parts of this course 153
will be completed, and we can say that if you have 154
some knowledge about Python, this video course 155
will be very easy for you. If you have no 156
programming experience, this course will require 157
some effort from you. If you already have some 158
data handling skills, this video course will be easy for you. 159
If you have some experience with tabular software, you will find that the 160
knowledge gained from this video course functions 161
as a force multiplier and increases your ability 162
to work with data. Learning the contents of this course will propel you to the master 163
or intermediate data science level, and you will 164
fulfill any requirements for most advanced 165
Python data science and machine learning courses. And now we'll talk some about the 166
course requirements, and this course assumes that you have everyday user experience with 167
operating systems such as Windows, Mac, iOS, 168
Android or Linux. And we can be certain to 169
say that, if you are able to join the course 170
on Udemy you likely fulfill this requirement. 171
And the course students may opt to use the new Anaconda Cloud Notebook 172
which is advertised by Anaconda to make Android 173
and iOS operating system users able to use the web browsers. 174
And this means that Android, Chrome and iOS users also should be able to follow the 175
course through Anaconda Cloud Notebook and the internet. 176
And this course is given globally and the requirement for the four ways of counting 177
simply establishes simple basic schooling as required. 178
Now we'll talk about the Udemy grading 179
system and a short time after enrolling in this 180
video course you will receive a message from Udemy asking you to grade the course. 181
Our intention with this course is that it shall 182
be the best Python, Pandas, and data handling course on Udemy. 183
We aim for high quality, mass dissemination and perhaps 100 000 to 2 million 184
or more students within five to ten years. 185
If you rate this course with five stars it will 186
motivate us to update this course for your benefit 187
and this increases the course's merit value 188
without any other effort than rating the course five stars. 189
Rating this course with five stars will signal 190
the high quality of the course and increase 191
the curriculum data value for your CV, when 192
you complete this course and acquire the Udemy 193
course certificate. Feel free to ask questions before grading this course. 194
All right, now it is time to continue to the 195
installation and setup procedures for Anaconda 196
Cloud Notebook and or optionality to download 197
and install the Anaconda distribution or any other python capable system of your choice, 198
And we look forward to see you in the next video!