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LifestyleMulti-Objective Optimization with Python Bootcamp A-Z (Udemy.com)
Mastering Multi-Objective Optimization and Decision-Making with pymoo: Balancing Objectives, Finding Solutions
Created by: Navid Shirzadi
Last updated October 2023
What you will learn
- Fundamentals of Multi-Objective Optimization (MOO)
- pymoo Library and How to Solve a MOO problem in Python
- Multi-Objective Optimization Algorithms and How to Initialize them
- Multi-Criteria Decision-Making Methods
- Compromise Programming
- Pseudo-Weights Method
How it compares
Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:
- Rating4.5 out of 5higher than 45% of them
- Reviews69#1,061 of 1,183 by number of reviews
- Length3.7 hoursshorter than 64% of them
- Last updatedOctober 2023earlier than 70% of them
Course Description
Course Description:
Welcome to "Multi-Objective Optimization with Python Bootcamp A-Z" In this comprehensive course, you will embark on a journey to become a skilled optimizer, equipped with the knowledge and tools to solve complex problems that involve conflicting objectives. With a focus on using the powerful Pymoo library in the Python environment, you will gain a deep understanding of multi-objective optimization techniques and strategies for making informed decisions.
Course Highlights:
Foundation of Multi-Objective Optimization: Understand the fundamentals of multi-objective optimization, Pareto optimality, and the challenges posed by conflicting objectives.
Optimization Algorithms: Explore a wide range of state-of-the-art algorithms, including genetic algorithms implemented using Pymoo.
Pymoo Library Mastery: Dive deep into the Pymoo library, from installation to customizing algorithms and interpreting results, maximizing your proficiency in multi-objective optimization.
Multi-Criteria Decision Making: Discover methods like Pseudo-Weights and Compromise Programming to make informed decisions while considering multiple criteria.
Real-World Applications: Apply your skills to practical case studies from various domains, learning how to address real challenges with optimization solutions.
Hands-On Projects: Work on hands-on coding exercises and assignments that reinforce your understanding and provide practical experience in solving multi-objective problems.
Visualization and Analysis: Utilize visualization tools to analyze Pareto fronts, trade-offs, and the impact of decision-making methods.
Problem-Solving Strategies: Develop strategies to tackle complex optimization problems, handling constraints, and achieving the right balance between convergence and diversity.
Whether you're a student, researcher, data scientist, or professional, this course offers valuable insights into multi-objective optimization and decision-making. By the end, you'll be equipped to approach complex challenges with confidence, optimize solutions effectively, and make well-informed decisions using the power of Pymoo.
Join us on this exciting journey of Multi-Objective Optimization with Python Bootcamp A-Z. Enroll today and unlock a new dimension of problem-solving expertise.
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Instructor Details
- 4.5 Rating
69 Reviews
Navid Shirzadi
Welcome! I'm Navid Shirzadi, and I'm thrilled you're here.
I’m an Applied Scientist with a Ph.D. in Engineering and over a decade of experience working with integrated energy systems, optimization, and intelligent control strategies. My background spans mathematical optimization, advanced control, and hybrid modeling techniques that blend physics‑based simulations with modern AI.
I’m deeply experienced in Python, and I build cutting‑edge machine learning, deep learning, and agentic AI models for real‑world applications. My recent work focuses on leveraging agentic AI workflows and LLM‑powered tools to automate and enhance building energy modeling, EnergyPlus pipelines, and large‑scale simulation tasks.
Throughout my career, I’ve published research on intelligent control strategies for energy systems and developed AI‑driven methods that improve efficiency, reliability, and decision‑making. My passion lies in teaching these concepts in a clear, practical, and intuitive way, helping learners build skills they can immediately apply in engineering, data science, and AI‑driven modeling.
I’m excited to share my knowledge and help you grow your expertise in AI, optimization, and energy systems.
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Reviews
By Agustín González Méndez on 5/3/2025
It covers the essentials to perform MOO. Something nice to add as extra material would be a lecture on how to mathematically model a project. The coding explanation is comprehensive, clear, and the optimization algorithms are explained from scratch, wich improved the learning experience.
By Muhammad on 3/18/2025
The explanation is clear, but it could include more performance indicators details like Hypervolume etc, and providing a lot of examples is better
By Sarah Fisher on 9/9/2024
It seems a comprehensive course and the instructor knows what he is talking about
By Adonis Andino on 7/23/2024
Good course and very good flow and practical example
By Bruno Nonohay Silva on 7/17/2024
The instructor is really clear and the course is logical and easy to follow. However, it is really short. I would really like to see more information about the differences between the different methods (advantages, disadvantages, typical cases to use A instead of B, etc...). I recommend this if you are looking for a quick way to implement a python code to optimize a multi-objective problem.
By Gerardo Zelaya Eufemia on 4/11/2024
Great introduction to the library PYMOO, but he postpones too much the theoretical background (e.g. Pareto Front and other definitions) to understand what we are doing until too much later. I guess he cares about novice programmers to dedicate explanations of trivial lines (e.g. self in object oriented), but he does not do the same on the matter of MultiObjective Optimization.
By Linda Wahyuningrum on 2/15/2024
The delivery of the knowledge and skills are in a very good structure. Unfortunately, this course didn't give some real case examples (The Pyomo Course gave many real case examples and teached us how to build the equations from scratch). I hope you can give us more real case examples in industry such as operation research etc. and teach how to build the equations. Thanks
By Emma Randall on 12/7/2023
Great explanation, you are supporting me through my masters course thank you!
By Sharvin Nagane on 9/5/2023
I recently had the pleasure of enrolling in the "Multi-Objective Optimization with Python Bootcamp A-Z," and I can confidently say that it has been a game-changer in my understanding of optimization techniques. The course also provides valuable resources, including code samples, documentation, and supplementary materials, which are instrumental in the learning process. I highly recommend this course to anyone looking to expand their Python and optimization skills.
By Robert on 8/31/2023
A good course about multi-objective optimization. Thanks, Navid
Quality Score
No CourseDuck member has rated this course yet. Taken it? Give each part a thumbs up or down.
Overall Score : 90 / 100
- Video Duration:
3.7h - Price: $12.99
- Provider: Udemy
- Updated:
October 2023 - Level:
All Levels - Language:
English - Certificate:
Yes
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