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Probabilistic Programming
1. Privacy - Terms
Learn how to enhance your modelling abilities
and better communicate risk
Building easy to interpret models isn’t a nice to have anymore it is the reason people pay for
models in the first place
2. What the pros and students are saying
Peadar has turned his practical experience with Bayesian methods
into a course that explains the nuts and bolts of Bayesian statistics
and probabilistic programming at a good pace.#PyMC3 #ArviZ
Osvaldo Martin - PyMC3 and ArviZ contributor
Level up your Analytical/Data Science skills
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My complete, self-study probabilistic programming and Bayesian Machine Learning
course is trusted by members of top machine learning schools, companies, and
organizations, including Harvard, Quantopian, Farfetch, Intercom, OKCupid,
Mailchimp, Uber, Google, University of Chicago and more!
3. From the outside, information about this topic is not easy to find. If
you do find something, it is usually more advanced material or you
need a lot of time to get through it. ... the course saved me time by
slowly exposing me to problems and examples that I am able to go
through in my own tempo. Having someone to ask when I get stuck
is also valuable.
Marko P. - Data Scientist
Peadar has been producing insightful educational material on Data
Science and Bayesian Stats for years. Increasingly these Bayesian
methods will become important, particularly in regulated sectors.
Alejandro Correra Bahnsen - VP Research
I'm currently doing your probabilistic programming primer, after
recently completing a data science immersive course - and I think
it's brilliant. Very easy to understand, thanks!
Justin Crowe - Data Scientist
Peadar has a great deal of experience working with probabilistic
programming and communicates the fundamentals of Bayesian
methods extremely well. He is in an excellent position to guide
people through a course like this.
Eoin Hurrell - Data Scientist
4. I was so impressed with the clarity of Peadars' vision and writing
that I included references from him in an open access online course,
Sport Informatics and Analytics.
Professor Keith Lyons
Unlike academia or blogs which focus solely on theory or
application, Peadar combines both in those course to set a solid
foundation for his students. With the knowledge from this course
students will be empowered in Bayesian methods, whether they
want to read papers, or start applying the methods in PyMC3
themselves
Ravin Kumar - Engineer and Course student
The probabilistic programming primer is an incredible course that
offers a fast track to an incredibly exciting field. Peadar clearly
communicates the content and combines this with practical
examples which makes it very accessible for his students to get
started with probabilistic programming.
Peter Verheijen - Entrepreneur and Course Student
There's an awesome course on Bayesian Stats by one of the core
PyMC3 developers - you should check it out
Hubert Wassner - Chief Data Scientist
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