Industrial & Systems Engineering from Udemy

This course offers a comprehensive introduction to Industrial and Systems Engineering, blending traditional principles with modern tools and techniques. Whether you’re just starting in the field or looking to expand your skillset, this course is designed to help you build a solid foundation and gain practical knowledge to address real-world challenges in various industries.

Industrial and Systems Engineering is about finding better ways to get things done. It’s about improving processes, making smarter decisions, and designing systems that work efficiently. Throughout this course, you’ll explore essential topics like systems thinking, process optimization, and quality control, while also diving into more advanced areas like decision analytics and reinforcement learning.

You’ll learn how to break down complex problems, analyze them systematically, and apply proven methods to develop effective solutions. From optimizing production lines to designing efficient supply chains, this course covers practical applications that are relevant across manufacturing, logistics, and operations.

In addition to the technical content, the course will also highlight how these methods are being applied in modern industries to adapt to technological advancements. We’ll discuss real-world case studies and provide hands-on examples to ensure that you can confidently put your knowledge to use.

By the end of the course, you’ll have a well-rounded understanding of Industrial and Systems Engineering, the ability to tackle challenges effectively, and the skills to create real impact in your field. No prior experience is required—just an interest in learning how to solve problems and improve systems.

What's inside

Learning objectives

Understand the core principles and methodologies of industrial and systems engineering, including systems thinking, optimization, and process improvement.
Apply practical tools and techniques, such as decision analytics, operations research, and simulation, to solve real-world problems effectively.

Analyze and optimize processes in manufacturing, logistics, and operations to improve efficiency and performance.
Learn to integrate modern concepts like reinforcement learning and data-driven decision-making into traditional industrial engineering practices.

Understand the core principles and methodologies of industrial and systems engineering, including systems thinking, optimization, and process improvement.
Apply practical tools and techniques, such as decision analytics, operations research, and simulation, to solve real-world problems effectively.
Analyze and optimize processes in manufacturing, logistics, and operations to improve efficiency and performance.
Learn to integrate modern concepts like reinforcement learning and data-driven decision-making into traditional industrial engineering practices.

Syllabus

Introduction

Start Smart: A Guide to Mastering This Course

IE History and Evolution

What do Industrial Engineers do?

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Provides a solid foundation in industrial and systems engineering, blending traditional principles with modern tools and techniques, which is useful for both beginners and those looking to expand their skillset

Covers essential topics like systems thinking, process optimization, and quality control, while also diving into more advanced areas like decision analytics and reinforcement learning, which are highly relevant in various industries

Explores practical applications relevant across manufacturing, logistics, and operations, such as optimizing production lines and designing efficient supply chains, which are essential for improving efficiency and performance

Includes a Python basics section, which is optional, but it is still useful for learners who want to implement the concepts and techniques taught in the course using a programming language

Requires learners to install Anaconda, Jupyter, and Visual Studio Code, which may require learners to have access to a computer with sufficient processing power and storage space

Teaches the use of Solver, which is an add-in for Microsoft Excel that is used for optimization, simulation, and risk analysis, and requires learners to have access to Microsoft Excel

Reviews summary

Broad intro to industrial systems engineering

According to learners, this course provides a broad overview of Industrial and Systems Engineering, covering key areas from Python basics and probability/statistics to Operations Research and optimization. Many appreciate the course for building a solid foundation and introducing various tools and techniques relevant to the field. While some find the breadth valuable, others feel certain advanced topics could benefit from more depth or that the prerequisites might be understated for those without a strong math background. The course is generally seen as a good starting point for understanding the diverse aspects of IE and its modern applications.

Requires some prerequisite understanding.

"While it says no prior experience, a solid math and stats background definitely helps."

"Some parts, like the Linear Algebra and Probability review, move quickly if you're unfamiliar."

"Might be challenging without prior exposure to calculus or linear algebra."

"Having some foundational knowledge makes following the OR and Optimization sections much easier."

Some topics are brief; others more detailed.

"Some sections felt a bit rushed, especially the more advanced OR techniques."

"Could use more in-depth coverage on complex topics like robust optimization."

"The Python basics are good, but other areas could go deeper."

"It's an introduction, so don't expect mastery in every single topic."

Introduces tools like Python and Solver.

"The introduction to Python and using solvers for optimization was very practical."

"Appreciated the hands-on examples with coding for mathematical models."

"Learning how to apply these techniques using software is a big plus."

"The Python section was useful for getting started with programming for IE tasks."

Establishes a strong base for key IE concepts.

"This course helped me build a solid foundation in core IE principles."

"It's a great starting point for anyone new to Industrial and Systems Engineering."

"I now have a much better understanding of systems thinking and process improvement basics."

"Learned fundamental concepts that are essential for the field."

Applicable to professional work.

"The concepts taught are highly relevant to real-world problems in operations and logistics."

"I can see how to apply these methods in my current job."

"This course provides practical tools and strategies I can use immediately."

"Good for professionals looking to expand their skillset in IE areas."

Covers many areas of Industrial Engineering.

"I was surprised by the breadth of topics covered, from Python and stats to OR and supply chain."

"It gives you a taste of everything an Industrial Engineer does."

"The syllabus is packed with useful information across different IE disciplines."

"This course touched upon many subjects relevant to modern IE practice."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Industrial & Systems Engineering with these activities:

Review Probability Theory

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Solidify your understanding of probability theory to better grasp concepts in operations research and supply chain analytics.

Browse courses on Probability Theory

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Review basic probability concepts.
Work through practice problems.
Consult online resources for clarification.

Read 'Introduction to Operations Research' by Hillier and Lieberman

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Gain a deeper understanding of operations research principles with a comprehensive textbook.

View ISE Introduction to Operations Research on Amazon

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Read assigned chapters related to the course syllabus.
Work through the examples provided in the book.
Attempt the end-of-chapter problems.

Read 'The Goal: A Process of Ongoing Improvement'

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Understand the Theory of Constraints through a narrative approach, enhancing your grasp of process improvement.

View The Goal: A Process of Ongoing Improvement -... on Amazon

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Read a chapter each day.
Reflect on the concepts presented.
Relate the concepts to real-world scenarios.

Four other activities

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Linear Programming Problem Sets

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Reinforce your understanding of linear programming by solving a variety of practice problems.

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Find a collection of linear programming problems.
Solve each problem using the Simplex method or software.
Check your answers and review the solutions.

Optimize a Local Business Process

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Apply industrial engineering principles to a real-world scenario by optimizing a process at a local business.

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Identify a local business with a process that can be improved.
Analyze the current process and identify bottlenecks.
Develop a plan to optimize the process.
Implement the plan and measure the results.

Create a Video Explaining Simplex Method

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Solidify your understanding of the Simplex method by creating a video tutorial explaining the process.

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Review the Simplex method thoroughly.
Prepare a script and visual aids.
Record and edit the video.
Share the video with peers for feedback.

Build a Supply Chain Simulation

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Create a simulation model of a supply chain to analyze and optimize its performance.

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Choose a supply chain to model.
Gather data on the supply chain's parameters.
Build a simulation model using appropriate software.
Run simulations and analyze the results.
Present your findings in a report.

Career center

Learners who complete Industrial & Systems Engineering will develop knowledge and skills that may be useful to these careers:

Process Improvement Specialist

A process improvement specialist focuses on enhancing organizational efficiency and productivity. This role involves analyzing existing processes, identifying areas for improvement, and implementing changes to streamline operations. This course introduces methodologies for process optimization, which directly correlate with the daily tasks of a process improvement specialist. The course's emphasis on systems thinking and quality control helps individuals develop a holistic understanding of process management. Furthermore, the material discussing data preprocessing helps a process improvement specialist use data to improve a process.

See salaries and explore the career path for Process Improvement Specialist

Operations Analyst

An operations analyst examines and improves an organization's operational efficiency. Operations analysts leverage data to identify trends, develop insights, and recommend strategies for improvement. The 'Industrial & Systems Engineering' course helps build a strong foundation in systems thinking and process optimization, which are valuable skills for operations analysts. The course's practical application of decision analytics provides the tools to approach real-world problems effectively. Additionally, the syllabus includes data preprocessing, linear algebra, and optimization which helps the analyst improve operations.

See salaries and explore the career path for Operations Analyst

Research Scientist

A research scientist designs and conducts experiments, analyzes data, and publishes findings in their area of expertise. This often requires an advanced degree. The course may be useful for those doing research into industrial processes. The course's content on linear algebra, and statistics may also be useful for analyzing data and building models. The optimization and data preprocessing content also helps the research scientist.

See salaries and explore the career path for Research Scientist

Supply Chain Analyst

A supply chain analyst optimizes the flow of goods and services from suppliers to consumers. Supply chain analysts work to improve efficiency, reduce costs, and enhance overall supply chain performance. This course can be highly relevant, as it covers essential topics such as process optimization, decision analytics, and operations research. The supply chain analytics module helps one to apply these methods to real challenges within the supply chain. Additionally, the course's focus on mathematical modeling can help the supply chain analyst.

See salaries and explore the career path for Supply Chain Analyst

Statistician

Statisticians collect, analyze, and interpret numerical data to identify trends and relationships. They apply statistical methodologies to solve problems in various fields, such as healthcare, business, and engineering. This course helps statisticians enhance their analytical skills and apply their knowledge to real-world problems. The course's exploration of probability theory may be useful to a statistician. The treatment of optimization can also help statisticians.

See salaries and explore the career path for Statistician

Quality Control Engineer

A quality control engineer ensures that products and processes meet specific standards and requirements. A quality control engineer will often use statistical analysis to monitor production processes. The coverage of quality control, probability, and statistics in this course will be useful. The course's treatment of hypothesis testing and probability distributions may provide a solid foundation. The course's emphasis on data-driven decision-making complements the need for precision and accuracy in quality control.

See salaries and explore the career path for Quality Control Engineer

Data Scientist

A data scientist analyzes large datasets to extract meaningful insights and inform data-driven decisions. Often, data scientists create models, use machine learning, and communicate insights to stakeholders. The course's syllabus includes data preprocessing, linear algebra, and optimization, which may be useful for data scientists. The course touches on Python, which is often used by data scientists. The material on handling missing values, feature scaling, and dimensionality reduction helps a data scientist deal with real-world data.

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Logistics Coordinator

A logistics coordinator manages the transportation and storage of goods. The goal is to ensure efficient and timely delivery. This course may be useful through its coverage of supply chain analytics and process optimization. These topics provide insights into improving the overall efficiency of logistics operations. The course's focus on real-world case studies could benefit those pursuing a role as a logistics coordinator.

See salaries and explore the career path for Logistics Coordinator

Manufacturing Engineer

Manufacturing engineers design, develop, and improve manufacturing processes. A key aspect of this role involves optimizing production lines and ensuring efficient resource utilization. This course may be useful given its curriculum covering process optimization and quality control, which directly relate to the responsibilities of a manufacturing engineer. The lean manufacturing optimization module can help improve production processes. By understanding these principles, a manufacturing engineer can contribute to enhanced productivity and reduced waste in manufacturing operations.

See salaries and explore the career path for Manufacturing Engineer

Business Analyst

A business analyst identifies business needs and determines solutions to business problems. They often bridge the gap between IT and the business using data analytics to assess processes and determine requirements. While this course does not focus on Business Analysis concepts, it may be useful for analysts working closely with Industrial and Systems Engineers. The course could provide a foundational understanding of the systems and processes and the data preprocessing concepts could also be useful.

See salaries and explore the career path for Business Analyst

Management Consultant

A management consultant advises organizations on how to improve their performance and efficiency. Management consultants analyze business problems and develop solutions. This course may be useful, as it provides a foundation in systems thinking and process optimization which helps a management consultant improve efficiency. The course's exploration of real-world case studies helps one apply their knowledge of industrial and systems engineering to consulting engagements.

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Project Manager

A project manager plans, organizes, and oversees projects to ensure they are completed on time and within budget. They work with various teams to define project goals and implement project plans. This course may be useful as it teaches one the fundamentals of process optimization. Project managers must understand the optimization of the processes they plan and execute. Also, the project manager often applies mathematical modeling to optimize tasks.

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Healthcare Operations Manager

A healthcare operations manager oversees the administrative and operational functions of a healthcare facility. They work to improve efficiency, reduce costs, and ensure high-quality patient care. The course may be useful through its focus on process optimization and systems thinking which enables efficiency improvements in healthcare settings. The course's content on data analytics may support data-driven decision-making.

See salaries and explore the career path for Healthcare Operations Manager

Financial Analyst

A financial analyst analyzes financial data, prepares reports, and provides investment recommendations. They use financial modeling to forecast future performance and assess investment opportunities. This course may be useful given its optimization content. Financial analysts at times must optimize portfolios and determine sensitivities to changes in financial constraints. The course's content on Python can provide an introduction to using financial engineering tools.

See salaries and explore the career path for Financial Analyst

Urban Planner

An urban planner develops plans and programs for the use of land, helping to create communities, accommodate population growth, and revitalize physical facilities in towns and cities. While not immediately obvious, this course may be useful for those interested in urban planning. The course discusses process optimization, which could be useful for planning transit and logistical routes. Also, the mathematical modeling skills can be repurposed to model population growth.

See salaries and explore the career path for Urban Planner

Industrial & Systems Engineering

What's inside

Learning objectives

Syllabus

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Reviews summary

Broad intro to industrial systems engineering

Activities

Career center

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