Python for Optimization: From Basics to Pyomo & MEALPy
Published 10/2025
Duration: 10h 25m | .MP4 1920x1080 30 fps(r) | AAC, 44100 Hz, 2ch | 3.79 GB
Genre: eLearning | Language: English
Published 10/2025
Duration: 10h 25m | .MP4 1920x1080 30 fps(r) | AAC, 44100 Hz, 2ch | 3.79 GB
Genre: eLearning | Language: English
Master Python programming, build optimization models in Pyomo, and explore metaheuristics with MEALPy , all in one hands
What you'll learn
- Write clean, organized Python programs with control flow and functions
- Apply Object-Oriented Programming (OOP) using classes, inheritance, and polymorphism
- Manipulate and analyze data with Pandas and NumPy
- Formulate and solve linear, nonlinear, and integer problems in Pyomo
- Implement multi-objective techniques: Weighted Sum, Epsilon-Constraint, and Goal Programming
- Model binary systems such as TSP and N-Queens
- Design graphical interfaces using Tkinter
- Use MEALPy to implement and tune metaheuristic algorithms (PSO, GA, GWO, etc.)
- Evaluate and visualize optimization results with SciPy and Matplotlib
- Understand how optimization integrates with AI pipelines and decision systems
Requirements
- Basic math knowledge (algebra, functions, simple graphs)
- Installed Anaconda + Jupyter Notebook
- No prior coding experience required, everything is explained from scratch
Description
Do you want to connect Python programming with real-world optimization and AI applications?
This course takes you step-by-step from the very basics of Python to solving advanced optimization problems using Pyomo and MEALPy inside Anaconda / Jupyter Notebook.
You’ll learn to write efficient code, model mathematical problems, handle data with Pandas and NumPy, and apply both deterministic and metaheuristic optimization methods.
By the end of the course, you will be able to:
Design and solve optimization problems such as the Traveling Salesman Problem and N-Queens
Compare exact Pyomo solvers with MEALPy’s population-based algorithms
Build GUI applications and connect optimization with AI fundamentals
This course is structured for beginners to intermediate learners who want practical, research-oriented skills.
All notebooks, datasets, and source codes are provided, ready to run in both online and offline environments.
What You’ll Learn
Write clean, organized Python programs with control flow and functions
Apply Object-Oriented Programming (OOP) using classes, inheritance, and polymorphism
Manipulate and analyze data with Pandas and NumPy
Formulate and solve linear, nonlinear, and integer problems in Pyomo
Implement multi-objective techniques: Weighted Sum, Epsilon-Constraint, and Goal Programming
Model binary systems such as TSP and N-Queens
Design graphical interfaces using Tkinter
Use MEALPy to implement and tune metaheuristic algorithms (PSO, GA, GWO, etc.)
Evaluate and visualize optimization results with SciPy and Matplotlib
Understand how optimization integrates with AI pipelines and decision systems
All in one integrated package of 50 lectures, 10 hours of HD video, and 40 + code demonstrations.
Requirements
Basic math knowledge (algebra, functions, simple graphs)
Installed Anaconda + Jupyter Notebook
No prior coding experience required, everything is explained from scratch
Instructor
Assoc. Prof. Shady H. E. Abdel Aleem
AI & Optimization Specialist | Industry Consultant | Research Leader
Ph.D., Electrical Power & Machines – Cairo University (2013)
Fellow, Basic Sciences Council, Academy of Scientific Research and Technology, Cairo
Senior Member, IEEE (SM’21) | Former Member, IET
State Encouragement Award (2017) | Medal of Distinction – First Class (2020)
Ranked among Stanford University’s Top 2 % Scientists Worldwide
Author of 250 + research papers and 13 books on power systems and optimization
Course Features
10 + hours of HD content
50 structured lectures with source code
All resources and datasets included
Full lifetime access on mobile & desktop
Certificate of Completion
Start Learning Today
Take the leap from Python beginner to optimization professional.
Join now and learn how to model, analyze, and optimize real-world systems using Python, the language that powers AI and scientific discovery.
Who this course is for:
- Engineering / Computer Science students who want a solid, practical start in optimization
- Researchers who need ready-to-run Python models for academic projects
- Professionals seeking to automate or optimize systems using Python tools
- Anyone curious about bridging programming + mathematical modeling + AI
More Info