Hi, my name is Andrew, and I want to introduce you
to our advanced machine learning specialization.
This is an advanced specialization for three groups of people, first,
data scientists who are willing to stay up-to-date with ever evolving field.
Second, programmers who are willing to pass an interview for machine learning engineer.
Third, students who want to get
a hands-on experience with our complex programming assignments.
You should be familiar with the basics of machine learning, probability theory,
linear algebra, and calculus, and of course,
Python programming to possible programming assignments.
Our first course is Introduction to Deep Learning,
because deep learning is so hot today and it is applied everywhere,
and we want you to know more than these guy on the picture who just text more layers.
We introduce the basic building blocks that you will need throughout our specialization.
Our specialization contains courses,
who are devoted to popular machine learning fields,
and also we have courses that are devoted to filling the gap between theory and practice.
The first course is Bayesian methods,
what is so cool about it?
They give superpowers to many machine learning algorithms,
like estimating uncertainty and predictions.
In this course, you will build
a variational autoencoder that we'll be able to generate the faces of new people.
Another course is natural language processing,
it covers traditional and deep learning techniques
for everything that you do with text, like sentiment analysis.
In this course, you will build a chat bot that
can answer stack overflow questions, isn't that cool?
The third course computer vision,
it starts with basics and turns to deep learning models,
like classification and annotation of images and videos.
In this course, you will learn how to build
a face recognition system that you can see in sci-fi movies.
The last course in this group is reinforcement learning,
it teaches foundations of reinforcement learning like cool learning and stuff like that.
In this course you will build a neural network that
plays an Atari game, that is wonderful.
Then we move to a group of courses that try to fill the gap between theory and practice,
and the first one is how to win a data science competition.
This course will teach you how to get
high-rank solutions with focus on practical usage of machine learning.
You will learn to combine a lot of models,
and you will compete in cackling cost competition.
The last but not least,
addressing large hadron collider course,
because particle identification is one of
the key challenges in the large hadron collider experiment,
and you can't just throw any machine learning algorithm in there,
it just has some additional properties that you have to
satisfy and we will show you how to do that.
We hope you will love
our specialization and all programming assignments that we have for you.
We wish you good luck if you choose to accept this mission,
and we want to see you on board.