Bayesian for Researching & Data Science
The use of P values for conventional significance testing has proven to be misused and misunderstood. Bayesian methods are emerging as the primary alternative to the conventional frequentist approach to statistical inference. Bayes' theorem is a model for learning and making decisions based on empirical data. Bayesian approaches have many empirical implications and are used widely for machine learning.
M&S Research Hub provides full and comprehensive structured training for researchers, programmers, and data scientists at all proficiency levels to acquire detailed knowledge and become fully capable of using these models in their research and programming projects.
Learning by "Researching" TM
Training Calendar
May / - Normal Group (7-10 participants) 7 seats left
July / - Normal Group (7-10 participants) 7 seats left
October / - Normal Group (7-10 participants) 7 seats left
2024
REVIEWS
Turning Point
Doing a research related to Bayesian and think of how to go about it,but immediately after undergoing this training , there was a turning point on the way of how to go about it. Thanks to the tutor"
O. Kazeem
Researcher, University of Abeokuta, Nigeria
Full Package
I found the information very helpful and the option to rewatch videos is great
G. C.
Student, University of Puerto Rico
Tree-Structured Training
After finishing the first module, I decided to to do all modules because the first one has opened my mind, because here in Zambia there is no university or college where they offer as full program they way you offer it, it only comes as a course to those who are doing economics.
George
Researcher, Ministry of Energy Zambia
Live Training
Snapshots
Follow our channel and see other sessions on
Video 1: M&S Research Hub | Bayesian for Research& Data Science using Python | Part of Session 1| Probabilities (13 Minutes)
Video 2: M&S Research Hub | Bayesian for Research& Data Science using Python | Bayesian inference using Python (11 Minutes)
Bayesian Training Program
A fully-fledged intensive training on the fundamentals of the Bayesian approach for econometric modeling and data analysis using Python programming package.
Duration: Approx. 15 Hours
Training Mode: Normal group (7-10 trainees), small group (2-5 trainees), and one-to-one
Platform: online (Zoom)
Extra benefits:
- Certified certificate after completing the training
- 10% trainee discount on future bookings
- Trainees become eligible to submit their papers at the MSR working paper series (SSRN and RePEc indexed).
Training content is systematic and structured as follows:
1 - Introduction and Setup
2- Probability Theory
3- Model Inference
4- Probalistical programming
5- Bayesian A/B-testing
6- Hierarchical Models
7- Simple Linear Regression
8- Hierarchical Linear Regression
9- Logistic Regression
10- Bayesian Neural Network
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