Welcome to Python in three hours. 1
Hello, everyone, this is lecture one, an introduction to the course. 2
By the end of this lecture, you will be able to see if the course is appropriate for you or not, see 3
how you should approach such a fast-paced course and also see an overview of the course. 4
My name is Mohammad Rafiei. 5
I'm a researcher and instructor at Johns Hopkins University College of Engineering and Georgia State 6
University Department of Computer Science. 7
I am also the founder of MHR Group LLC in Georgia, a data analytics company where we work with 8
various domestic and global researchers at different institutions to address persistent challenges in 9
computer science, engineering, and medicine using state of the art machine learning and optimization 10
techniques. 11
It is my great pleasure to serve as a Udemy instructor, helping thousands of students and researchers 12
across the globe to learn python and machine learning. 13
You can find more information about me at ep.jhu/faculty/mohammad-rafiei. 14
The main question for you guys is that does this course suit you or not? 15
This course suits you, 16
If you want to learn, python, learn and apply machine learning artificial intelligence in Python, 17
run Python on free CPU, GPU, and TPU 18
cloud computers, do not want to install any bulky software on your computer, 19
want to do all these in less than three hours, and want this course to be 100 percent money-back guaranteed. 20
If that is the case, then you are in the right place. In less than three hours. 21
this course will teach you Python 3 from scratch, 22
(No installation is required all on free cloud computers at Google), General Machine Learning Concepts, 23
and neural networks, 24
How to develop machine learning models using tensor flow in Python 3, and how to investigate your 25
problems in Python. This course helps you 26
if you are a Python beginner who is interested in learning Python and using Python to develop machine 27
learning models in less than three hours. You are interested in using free and powerful cloud CPU 28
and GPU computers to develop and run your python code. almost wherever you are in the world 29
Google will give you free remote access to its computers. Free CPU, GPU, and TPU processors to develop 30
and run your Python codes for free. 31
You only need to have Gmail, which is free, and Google Chrome, the Google Web browser, also free, 32
installed on your operating system. 33
It does not matter what your operating system is. 34
No bulky software is required. 35
Just Google Chrome Web browser. 36
Almost all the cheapest computers in the market can handle Google Chrome, so no significant computer 37
system is required. 38
Isn't that amazing? 39
This course helps you if you have no or little knowledge of Python and are interested in learning Python 40
and want to practice machine learning problems in Python, all in a matter of fewer than three hours, 41
you might have no or little knowledge of Python. 42
So you will be taught, you might have no or little knowledge of machine learning or neural networks. 43
You will be taught and you will practice them in Python. 44
You might be someone so busy and might not have the time to go over a twenty five hour course that teaches 45
you many rudimentary programming basics. 46
You need optimum materials in a minimum amount of time to help you drive Python by yourself. 47
This course helps you if you prefer, not even install any additional complicated software, editors, or programs 48
on your computer to run Python. 49
You might have an old rusty computer, but it is able to run the latest version of Google Chrome. 50
I mean the Google Free Web browser. 51
Your computer has limited memory to run programming scripts or has a limited hard drive to install 52
bulky and complicated software. 53
You will benefit the most if you're familiar with at least one computation based programming language 54
such as Matlab, R, C, C++, C, Sharp, etc. and want to switch to or learn Python. 55
We are not going to explain, say, what a for-loop is 56
But we will see how to create, say, for loops in Python. 57
We are not explaining what an array or matrix. 58
OK, let's talk about the core space order and needs. 59
This is a fast-pace python 3 course, less than 180 minutes only, from zero python experience to 60
machine learning in Python. In every lecture 61
You can download the corresponding python notebooks and upload them in your Google Kulab environment 62
and you can practice them either at the end of each lecture or after watching all the lectures. 63
Remember all the lectures together are less than one hundred and eighty minutes. you can use these Python 64
notebooks as your future cheat sheets. 65
It should be noted that we are not going to see everything in Python but enough or essentials for you 66
to start and accelerate on your own. 67
I believe that by the end of this course you will be able to drive on your own and expand your python 68
knowledge based on your needs. 69
You will be a pythonist equipped with enough knowledge to explore your journey in Python. 70
If you are not familiar with Gmail and or Chrome, there will be links to YouTube videos to show you 71
how to set them up. If the videos are too fast or too slow 72
You can always change the speed of them. 73
You can also turn on the video caption. 74
It is best to watch the videos of this course using HD quality with a caption on. the course overview. 75
It is about one hundred and eighty minutes in 12 lectures. 76
Lecture one, an introduction to the course, which is less than 18 minutes. lecture 2 Gmail, Chrome 77
and Google Colab about eleven minutes, lecture three operations, building functions and data types about 78
twenty minutes, lecture for loops, conditional scripts and functions about sixteen minutes. 79
Lecture five numpty and pandas for data processing about twenty eight minutes. 80
Lecture six Matplot Library and Seaborn for data visualizations about ten minutes. 81
Lecture seven data repositories and data split in machine learning about fifteen minutes. Lecture 82
Eight Data processing and calibrations in machine learning about thirteen minutes. 83
Lecture nine brief introduction to neural networks about eleven minutes. 84
Lecture ten TensorFlow Keras for regression neural networks, about sixteen minutes. 85
Lecture eleven TensorFlow Keras for classification neural networks, about thirteen minutes. 86
Lecture twelve. 87
Hit the road on your own about nine minutes. 88
You guys can contribute to this course. 89
Please write a review about this course, then we can modify it and make it better for you guys. 90
If you find this course interesting, please refer it to your friends and colleagues. 91
I want to thank my amazing wife Fatemeh for all her support in developing this course. 92
I want to also thank my friend and brother Ahmad 93
Mohammadshirazi, a computer science student at the Ohio State University, for helping me in the video 94
editing of this course. 95
In this lecture, you'll learn about why this course would be appropriate for you, how you should approach 96
such a fast paced course, and what are the course contents? 97
In the next lecture, we will talk about how to set up Gmail and Chrome and how to initiate a Google 98
Colab Python 3 notebook 99
Thank you for your attention. 100
See you all in the next lecture.