Hello everyone and welcome to the Python for data science and machine learning boot camp.
My name is Jose Portsea and I'll be your instructor for this course.
I've taught tens of thousands of students on to me about Python and data science and I'm so excited
to teach you about all these topics in my brand new course data scientist has been ranked the number
one job by glass door and is an excellent career path providing not just great salary potential but
the opportunity to work on some of the world's most interesting problems.
And this course will be covering the most popular Python data science libraries including numb pie site
pie pandas seaborne sikat learn map plot lib plot Lee pie spark for big data deep learning libraries
and much more.
Don't worry if you don't know all these library names yet by the end of the Course you'll feel very
comfortable putting these technologies on your resume.
Let's go ahead and take a quick look inside the course to see all the contents.
We'll start off of a crash course in Python.
This course is designed for students of some program experience.
You'll make sure to refresh your memory on important syntax and topics before we get started with the
data analysis material of the course.
Then we'll switch gears and start learning about pi.
A scientific computing library for Python that's going to allow us to work with data arrays in Python
.
Then we'll continue our understanding by learning about pandas.
The fantastic data analysis library allows us to read them manipulate data from multiple sources including
CAC files Excel workbooks H-2 mail web pages for web scraping sequel databases and much more all along
the way.
Have exercise notebooks or practice your new skills you'll be given real world data sets and questions
to answer about them.
After every exercise we also have a full solution walkthrough of the exercise questions.
Then we'll begin discussing basic data visualization.
By learning about the map plot lib library.
Then later on we'll create beautiful statistical plots for the Seaborn library will also cover interactive
plotting techniques so you can share your work in a way that's interactive for your users.
Also cover how to interactively plot financial information will even cover geographical plotting techniques
.
After that we'll reach a second half of the course where we all use sikat learn in Python to implement
machine learning algorithms including topics such as linear regression logistic regression several classification
techniques such as decision trees and random force unsupervised clustering algorithms.
Natural Language Processing and much much more.
After all of that you'll begin to learn how to work with big data using the latest SPARC technologies
.
I found on Amazon Web Services will even cover the basics of using the newest deep learning libraries
.
Every single section ends for full exercise and a solution walkthrough of the exercise questions Bielsa
capstone projects and over a dozen fully implemented machine learning portfolio projects.
This force consists of over 100 HD video lectures with fully written out code notebooks for reference
so you can learn in whatever way works best for you.
Not only do you get access to some of the best data science educational content on the web you'll get
access to our online community Q&A forms where thousands of students and I are happy to help you out
and answer any questions you may have after completing this course.
You'll also receive a certificate of completion that you can post here linked in profile.
All of this comes with a 30 day money back guarantee.
If you're unsatisfied for any reason you can get your money back no questions asked.
So what are you waiting for.
Jump start a career path in data science and enroll today.
I'll see you inside the course.