Advanced Models for Decision Making from Coursera

Business analysts need to be able to prescribe optimal solution to problems. But analytics courses are often focused on training students in data analysis and visualization, not so much in helping them figure out how to take the available data and pair that with the right mathematical model to formulate a solution. This course is designed to connect data and models to real world decision-making scenarios in manufacturing, supply chain, finance, human resource management, etc. In particular, we understand how linear optimization - a prescriptive analytics method - can be used to formulate decision problems and provide data-based optimal solutions. Throughout this course we will work on applied problems in different industries, such as:

(a) Finance Decisions: How should an investment manager create an optimal portfolio that maximizes net returns while not taking too much risks across various investments?

(b) Production Decisions: Given projected demand, supply of raw materials, and transportation costs, what would be the optimal volume of products to manufacture at different plant locations?

(c) HR Decisions: How many workers need to be hired or terminated over a planning horizon to minimize cost while meeting operational needs of a company?

(c) Manufacturing: What would be the profit maximizing product mix that should be produced, given the raw material availability and customer demand?

We will learn how to formulate these problems as mathematical models and solve them using Excel spreadsheet.

What's inside

Syllabus

Module 1: LPs for Financial Decisions

In this module we will look at examples illustrating the application of linear optimization in finance. In particular, we will learn to formulate problems in investment portfolio optimization and multi-period cash flow management.

Module 2: LP for Supply Chain Decisions

This module explores the use of linear optimization in supply chain decisions, particularly in the context of inventory transportation or logistics problems as well as in production and inventory management.

Module 3: LP for Staffing Decisions

This module explores how human resource managers can use optimization as a prescriptive analytics tool to plan staff schedules, room allocation, and workforce size management.

Module 4: LP for Production Decisions

Linear optimization plays an important role in the decision making process in the manufacturing sector. This module explores how optimization can be used to prescribe product mix and blending decisions.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches linear optimization as a method of prescriptive analytics to develop optimal business solutions

Explorations of real-world case studies to connect theory and practice in business analytics

Taught by Soumya Sen, an experienced instructor and researcher in business analytics

Uses Excel spreadsheets as a practical tool for applying linear optimization

Reviews summary

Highly recommended decision making course

According to students, Advanced Models for Decision Making is a highly recommended course with engaging assignments and well-explained concepts. They say that this course largely positive reviews because it provides practical knowledge that can be applied in various settings. The level of difficulty is considered intermediate, and it follows the previous course of Optimization in this specialization.

Intermediate difficulty level.

"The level of difficulty is intermediate."

Offers practical knowledge that can be applied in various settings.

"All of the courses in this series are very practical based and give a lot of practice in using the tools."

"Very useful content, very detailed lecture!"

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 Advanced Models for Decision Making with these activities:

Reviewing basic probability and statistics concepts

Show steps

Refresh your understanding of probability and statistics to strengthen your foundation for linear programming.

Browse courses on Probability

Show steps

Review textbooks or online resources on probability and statistics.
Solve practice problems to test your understanding.

Identifying a mentor to guide your learning

Show steps

Seek guidance and support from an experienced professional in the field to enhance your learning.

Show steps

Identify potential mentors through networking or online platforms.
Reach out and request a meeting to discuss your learning goals.
Meet regularly with your mentor to receive advice and feedback.

Create a curated list of resources on linear programming

Show steps

Build a curated collection of resources to aid in your learning of linear programming.

Browse courses on Optimization

Show steps

Gather resources from various sources such as books, websites, and online courses.
Organize the resources based on topic or difficulty level.
Create a document or website to share the curated list.

Five other activities

Expand to see all activities and additional details

Show all eight activities

Reviewing the book 'Linear Programming: Theory and Applications'

Show steps

Reinforce your understanding of linear programming concepts through a comprehensive review of a foundational book.

View Linear Programming: Foundations and Extensions... on Amazon

Show steps

Read the book and take notes on key concepts.
Solve practice problems from the book.
Write a summary of the book's main ideas.

Solving problems from the Linear Programming chapter of a textbook

Show steps

Solve linear programming problems from a textbook to reinforce the concepts learned in the course.

Browse courses on Linear Programming

Show steps

Pick a textbook with a dedicated chapter on linear programming.
Read the chapter and understand the concepts of linear programming.
Solve the practice problems at the end of the chapter.
Check your solutions against the provided answer key.

Participating in a study group

Show steps

Engage in collaborative learning by joining a study group to discuss course concepts, solve problems, and quiz each other.

Show steps

Find a study group or create one with classmates.
Meet regularly to discuss course material and work on assignments together.
Take turns presenting concepts to the group.

Following tutorials to implement linear programming algorithms in Python

Show steps

By following a series of online tutorials, practice implementing linear programming algorithms in Python.

Browse courses on Python

Show steps

Search for tutorials on implementing linear programming algorithms in Python.
Choose a tutorial that is well-rated and clear.
Follow the steps in the tutorial to implement the algorithm.
Test your implementation by solving practice problems.

Developing a linear programming model for a real-world problem

Show steps

Conceptualize and build a linear programming model to solve a real-world problem.

Browse courses on Optimization

Show steps

Identify a real-world problem that can be solved using linear programming.
Define the decision variables, objective function, and constraints of the problem.
Formulate the linear programming model using a modeling software or Python.
Solve the model using a solver.
Analyze the results and draw conclusions.

Career center

Learners who complete Advanced Models for Decision Making will develop knowledge and skills that may be useful to these careers:

Business Analyst

Business Analysts assess and develop new and existing IT systems for companies, consulting on technical issues and finding ways to implement solutions. A course in Advanced Models for Decision Making can help aspiring Business Analysts develop the skills needed to understand and solve real-world problems using data, which can lead to a competitive advantage in the job market.

See salaries and explore the career path for Business Analyst

Financial Analyst

Financial Analysts prepare financial reports, make recommendations on investments, and analyze the financial performance of companies and other organizations. Knowledge in business analytics is very useful to Financial Analysts, and coursework in Advanced Models for Decision Making can help aspiring Financial Analysts improve their problem-solving and modeling skills.

See salaries and explore the career path for Financial Analyst

Quantitative Analyst

Quantitative Analysts analyze complex financial data, often while working with risk management and portfolio managers, and devise complex quantitative models. Knowledge in business analytics is essential for aspiring Quantitative Analysts. Advanced Models for Decision Making can help teach aspiring analysts how to model complex financial data in order to make better predictions and develop profitable investment strategies.

See salaries and explore the career path for Quantitative Analyst

Operations Research Analyst

Operations Research Analysts use advanced analytics and mathematical models to improve the efficiency of an organization's operations. Advanced Models for Decision Making can help build a foundation for aspiring Operations Research Analysts, who can use this course to develop the skills needed to model and improve complex systems in various industries.

See salaries and explore the career path for Operations Research Analyst

Investment Analyst

Investment Analysts evaluate investment opportunities such as stocks or bonds and make recommendations to clients based on their findings. Coursework in Advanced Models for Decision Making can help future Investment Analysts gain a better understanding of advanced modeling and how to solve problems using data, increasing their value to clients.

See salaries and explore the career path for Investment Analyst

Supply Chain Manager

Supply Chain Managers oversee all aspects of a company's supply chain, including planning, sourcing, manufacturing, and delivery. This role requires a deep understanding of business analytics. Advanced Models for Decision Making can help teach aspiring Supply Chain Managers how to use data to model and optimize supply chains.

See salaries and explore the career path for Supply Chain Manager

Management Consultant

Management Consultants help organizations improve their performance by analyzing their operations and developing and implementing solutions. Advanced Models for Decision Making can be useful for those interested in a career in Management Consulting and can help develop the skills needed to analyze complex business problems and develop data-driven recommendations based on mathematical modeling.

See salaries and explore the career path for Management Consultant

Data Scientist

Data Scientists collect, interpret, and communicate data to help organizations understand market trends, customer behavior, and areas for improvement. A foundation in business analytics can help build a foundation for aspiring Data Scientists, who often require a master's degree or PhD. coursework in Advanced Models for Decision Making can help a Data Scientist develop the skills needed to model decision-making and other complex systems, bringing an enhanced skill set to potential employers.

See salaries and explore the career path for Data Scientist

Risk Manager

Risk Managers identify and assess potential risks to an organization and take steps to mitigate those risks. Advanced Models for Decision Making can help build a foundation for aspiring Risk Managers, who can use this course to develop the skills needed to model and assess risk, which could increase their value to potential employers.

See salaries and explore the career path for Risk Manager

Actuary

Actuaries use mathematical and statistical models to assess risk and uncertainty in a variety of industries, including insurance, finance, and healthcare. Advanced Models for Decision Making may be useful for aspiring Actuaries, teaching foundational knowledge needed to succeed in the field.

See salaries and explore the career path for Actuary

Statistician

Statisticians collect, analyze, interpret, and present data in a way that can be easily understood. Advanced Models for Decision Making may be useful for aspiring Statisticians, teaching foundational knowledge needed to succeed in the field.

See salaries and explore the career path for Statistician

Software Developer

Software Developers design, develop, and test software applications. Advanced Models for Decision Making may be useful for aspiring Software Developers, teaching foundational coding skills that may be useful in development.

See salaries and explore the career path for Software Developer

Market Researcher

Market Researchers conduct research on consumer behavior and market trends to help organizations understand their customers and make better decisions. Advanced Models for Decision Making may be useful for aspiring Market Researchers, teaching foundational knowledge needed to succeed in the field.

See salaries and explore the career path for Market Researcher

Data Analyst

Data Analysts collect, clean, and analyze data to help organizations understand their customers, improve their products and services, and make better decisions. Advanced Models for Decision Making may be useful for aspiring Data Analysts, teaching foundational knowledge needed to succeed in the field.

See salaries and explore the career path for Data Analyst

Product Manager

Product Managers are responsible for the overall vision and strategy for products and features within a company, working with engineering, design, and marketing to bring new products to market. Advanced Models for Decision Making may be useful for Product Managers, exposing them to different real-world applications of mathematical modeling and how it can be used to develop data-driven product roadmaps.

See salaries and explore the career path for Product Manager