Published 12/2020
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 615.25 MB | Duration: 1h 25m
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What you’ll learn
Stochastic Optimization
Probabilistic approaches
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Requirements
The only prerequisite is to take the first course of the "giannelos dot com" program , which is the course "Data Science Code that appears all the time at workplace".
Description
In this course we build the foundations for the concept of Decision Making under Uncertainty. Instead of focusing on theoretical / academic / abstract analyses, we move straight into action / practice / application by building a MATLAB model that detects the Optimal Investment Decisions under uncertainty. We adopt a step-by-step approach and build this model from scratch. Step – by – step we then add extra layers of code until the model is completed. We also implement this solver on Excel and use Excel Solver to find the optimal solution. In addition, we understand scenario trees. Scenario trees are vastly used in stochastic optimization.We also study mathematical formulations. I.e. the symbols/notation used and how to analyse and synthesize them.Through application and case studies, we develop understanding about Energy investments. We also look into relevant concepts such as "Demand Side Response" and "power flows". We study these but we also implement them in code. Also, you get lifetime access to the Q&A section, where you can ask any question and receive answers.Also, you download lots of material, including slides, as well as code. Please feel free to ask any questions, or make any recommendations that will enhance the course.I wish you the best of luck!
Overview
Lecture 1 Introduction
Section 1: Introduction
Lecture 2 Stochastics and probabilities
Lecture 3 Stochastic v2
Lecture 4 Extra analysis on histograms
Section 2: Conclusion
Lecture 5 Concluding remarks for stochasticity
Enterpreneurs,Economists.,Quants,Members of the highly googled giannelos dot com program,Investment Bankers,Academics, PhD Students, MSc Students, Undergrads,Postgraduate and PhD students.,Data Scientists,Energy professionals (investment planning, power system analysis),Software Engineers,Finance professionals
Homepage
https://www.udemy.com/course/stochastic_optimization_fundamentals/
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