Optimization with Python: Solve Operations Research Problems from Udemy

Operational planning and long term planning for companies are more complex in recent years. Information changes fast, and the decision making is a hard task. Therefore, optimization algorithms (operations research) are used to find optimal solutions for these problems. Professionals in this field are one of the most valued in the market.

In this course you will learn what is necessary to solve problems applying Mathematical Optimization and Metaheuristics:

Linear Programming (LP)
Mixed-Integer Linear Programming (MILP)
NonLinear Programming (NLP)
Mixed-Integer Linear Programming (MINLP)
Genetic Algorithm (GA)
Multi-Objective Optimization Problems with NSGA-II (an introduction)
Particle Swarm (PSO)
Constraint Programming (CP)
Second-Order Cone Programming (SCOP)
NonConvex Quadratic Programming (QP)

The following solvers and frameworks will be explored:

Solvers: CPLEX – Gurobi – GLPK – CBC – IPOPT – Couenne – SCIP
Frameworks: Pyomo – Or-Tools – PuLP – Pymoo
Same Packages and tools: Geneticalgorithm – Pyswarm – Numpy – Pandas – MatplotLib – Spyder – Jupyter Notebook

Moreover, you will learn how to apply some linearization techniques when using binary variables.

In addition to the classes and exercises, the following problems will be solved step by step:

Optimization on how to install a fence in a garden
Route optimization problem
Maximize the revenue in a rental car store
Optimal Power Flow: Electrical Systems
Many other examples, some simple, some complexes, including summations and many constraints.

The classes use examples that are created step by step, so we will create the algorithms together.

Besides this course is more focused in mathematical approaches, you will also learn how to solve problems using artificial intelligence (AI), genetic algorithm, and particle swarm.

Don't worry if you do not know Python or how to code, I will teach you everything you need to start with optimization, from the installation of Python and its basics, to complex optimization problems. Also, I have created a nice introduction on mathematical modeling, so you can start solving your problems.

I hope this course can help you in your career. Yet, you will receive a certification from Udemy.

Operations Research | Operational Research | Mathematical Optimization

See you in the classes.

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Teaches mathematical optimization, which is standard in operations research, data science, and artificial intelligence

Develops real-world problem-solving skills using optimization algorithms

Builds a foundation for advanced optimization techniques, machine learning, and data mining

Taught by instructors with extensive experience in optimization and operations research

Uses Python and industry-standard solvers, making it highly relevant to the job market

Requires some familiarity with Python and optimization concepts

Reviews summary

Practical python optimization for operations research

According to learners, this course offers a comprehensive and practical introduction to solving operations research problems using Python. Many find the content well-structured and easy to follow, especially appreciating the step-by-step examples and hands-on coding. Students highlight the course's strength in covering a wide array of optimization techniques like LP, MILP, and various metaheuristics, alongside practical use of industry-standard solvers and frameworks such as Pyomo, Or-Tools, CPLEX, and Gurobi. While designed to be accessible for those new to Python, some advanced users desired deeper dives into specific complex topics.

Instructor's teaching style is clear and engaging.

"The instructor explains complex topics in a very clear and understandable way, making the learning process enjoyable."

"I found the lectures well-paced and easy to follow. The examples built up logically, which helped me solidify my understanding."

"The instructor was very articulate and broke down the material effectively. Their passion for the subject really shone through."

Suitable for those new to Python and mathematical modeling.

"As someone new to Python, I really appreciated the instructor's patience in teaching the basics before diving into optimization. It made a huge difference."

"The introduction to mathematical modeling was very well done. It helped me bridge the gap between theory and coding optimization problems effectively."

"They promised to teach Python from scratch, and they delivered! I felt comfortable even without prior coding experience."

Strong emphasis on coding practical, real-world problems.

"The step-by-step approach to solving problems like route optimization and revenue maximization was incredibly helpful for my understanding."

"I loved the hands-on coding sessions. Creating algorithms together with the instructor made complex topics much easier to grasp and apply."

"This course is highly practical; I appreciated that it focuses on solving actual problems rather than just theoretical concepts. It's truly applied."

Broad coverage of optimization techniques and industry tools.

"This course provided a really comprehensive overview of different optimization types, from LP to genetic algorithms. I learned so much!"

"I was impressed by the sheer number of solvers and frameworks covered. I now feel comfortable using Pyomo, Or-Tools, and even understanding CPLEX/Gurobi concepts."

"The course introduces a vast range of optimization techniques and their practical application, which is exactly what I needed for my work."

Some advanced users desired more complex problem coverage.

"While excellent for beginners, I felt some topics, like NSGA-II, were only briefly introduced. I would have liked a more in-depth exploration for complex scenarios."

"For experienced OR professionals, some parts might feel a bit basic. I was hoping for more advanced problem formulations or real-world large-scale case studies."

"I got a great overview, but to truly master certain areas, I'll need to seek additional resources beyond this course for deeper understanding."

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Career center

Learners who complete Optimization with Python: Solve Operations Research Problems will develop knowledge and skills that may be useful to these careers:

Operations Research Analyst

Operations Research Analysts use advanced analytical techniques to solve complex problems in various industries. This course provides a solid foundation in mathematical optimization and metaheuristics, equipping you with the skills to develop and implement solutions for operational planning and long-term decision-making. By mastering these techniques, you'll be well-versed in addressing real-world challenges faced by Operations Research Analysts.

See salaries and explore the career path for Operations Research Analyst

Data Scientist

Data Scientists leverage data to extract insights and drive decision-making. This course enhances your problem-solving abilities through mathematical optimization, enabling you to effectively analyze and interpret complex datasets. The focus on metaheuristics provides you with advanced techniques to handle large-scale and non-linear optimization problems, making you a valuable asset in the field of Data Science.

See salaries and explore the career path for Data Scientist

Management Consultant

Management Consultants provide strategic advice to businesses, helping them improve their operations and achieve their goals. This course empowers you with a comprehensive understanding of optimization techniques, enabling you to analyze business scenarios, identify areas for improvement, and develop data-driven recommendations. The focus on mathematical modeling and linear programming will equip you with the tools to tackle complex decision-making challenges faced by Management Consultants.

See salaries and explore the career path for Management Consultant

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to assess financial risks and make investment decisions. This course provides a strong foundation in optimization techniques, including linear programming, non-linear programming, and metaheuristics. By mastering these concepts, you'll gain the skills to develop and implement sophisticated models for risk management and portfolio optimization, making you a sought-after professional in the financial industry.

See salaries and explore the career path for Quantitative Analyst

Software Engineer

Software Engineers design, develop, and maintain software systems. This course provides a comprehensive understanding of optimization algorithms and their implementation in software. By learning to apply mathematical modeling and metaheuristic techniques, you'll be equipped to develop efficient and scalable software solutions for a wide range of industries, including operations research, logistics, and supply chain management.

See salaries and explore the career path for Software Engineer

Supply Chain Manager

Supply Chain Managers optimize the flow of goods and services from suppliers to consumers. This course provides a solid understanding of mathematical optimization and metaheuristics, enabling you to analyze and improve supply chain networks. The focus on linear programming and mixed-integer linear programming will equip you with the tools to design and manage efficient supply chains, reducing costs and improving customer satisfaction.

See salaries and explore the career path for Supply Chain Manager

Business Analyst

Business Analysts bridge the gap between business stakeholders and IT teams, translating business requirements into technical specifications. This course provides a foundation in mathematical modeling and optimization techniques, enabling you to analyze business processes, identify areas for improvement, and develop data-driven solutions. The focus on constraint programming and second-order cone programming will equip you with the skills to handle complex business constraints and optimize decision-making.

See salaries and explore the career path for Business Analyst

Financial Analyst

Financial Analysts evaluate financial data and make recommendations for investments. This course provides a strong foundation in optimization techniques, including linear programming and non-linear programming. By mastering these concepts, you'll gain the skills to develop and implement financial models for risk assessment, portfolio optimization, and investment analysis, making you a valuable asset in the financial industry.

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Risk Manager

Risk Managers identify, assess, and mitigate risks to an organization's financial health and reputation. This course provides a comprehensive understanding of optimization techniques, including linear programming and mixed-integer linear programming. By mastering these concepts, you'll gain the skills to develop and implement risk management models, enabling you to make informed decisions and protect your organization from potential threats.

See salaries and explore the career path for Risk Manager

Actuary

Actuaries use mathematical and statistical techniques to assess and manage financial risks. This course provides a strong foundation in optimization techniques, including linear programming and non-linear programming. By mastering these concepts, you'll gain the skills to develop and implement actuarial models for insurance pricing, risk assessment, and financial planning, making you a valuable asset in the insurance industry.

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Statistician

Statisticians collect, analyze, interpret, and present data. This course provides a solid understanding of optimization techniques, including linear programming and non-linear programming. By mastering these concepts, you'll gain the skills to develop and implement statistical models for data analysis, hypothesis testing, and forecasting, making you a valuable asset in various fields such as research, healthcare, and marketing.

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Economist

Economists analyze economic trends and data to develop policies and make predictions. This course provides a foundation in mathematical modeling and optimization techniques, enabling you to analyze economic data, forecast economic outcomes, and develop data-driven policy recommendations. The focus on linear programming and mixed-integer linear programming will equip you with the tools to handle complex economic models and optimize decision-making.

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Operations Manager

Operations Managers oversee the day-to-day operations of an organization. This course provides a comprehensive understanding of optimization techniques, including linear programming and mixed-integer linear programming. By mastering these concepts, you'll gain the skills to analyze and improve operational processes, reduce costs, and increase efficiency, making you a valuable asset in any industry.

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Project Manager

Project Managers plan, execute, and close projects. This course provides a solid understanding of optimization techniques, including linear programming and non-linear programming. By mastering these concepts, you'll gain the skills to develop and implement project plans, allocate resources, and manage risks, making you an effective Project Manager in any industry.

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Consultant

Consultants provide advice and expertise to organizations on a variety of topics. This course provides a foundation in mathematical modeling and optimization techniques, enabling you to analyze business scenarios, identify areas for improvement, and develop data-driven recommendations. By mastering these techniques, you'll become a valuable asset to clients in various industries, helping them solve complex problems and achieve their goals.

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