Master linear programming and Excel-based optimization techniques for data-driven business decisions.
Master linear programming and Excel-based optimization techniques for data-driven business decisions.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Analytics for Decision Making Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.8
(66 ratings)
6,117 already enrolled
Instructors:
English
21 languages available
What you'll learn
Formulate linear optimization problems from business scenarios
Use Excel Solver for practical decision-making
Analyze multiple solution scenarios and constraints
Implement prescriptive analytics in business contexts
Develop spreadsheet models for optimization
Skills you'll gain
This course includes:
4.6 Hours PreRecorded video
8 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course introduces students to linear optimization techniques for business decision-making. Learners master prescriptive analytics using Excel Solver, covering fundamental concepts of linear programming and practical applications. The curriculum progresses from basic problem formulation to advanced optimization scenarios, including multiple solutions and special cases. Students gain hands-on experience with real-world business problems, learning to model and solve optimization challenges using spreadsheet tools.
Module 1: Introduction to Linear Programming
Module 1 · 4 Hours to complete
Module 2: Solving Linear Programs
Module 2 · 3 Hours to complete
Module 3: Alternative Specifications & Special Cases in Linear Optimization
Module 3 · 2 Hours to complete
Module 4: Modeling & Solving Linear Problems in Excel
Module 4 · 3 Hours to complete
Fee Structure
Instructor
Pioneering Researcher in Internet Economics and Data Analytics
Dr. Soumya Sen is an Associate Professor of Information & Decision Sciences at the Carlson School of Management, University of Minnesota, where he integrates his extensive background in engineering and business to explore the intersections of technology and society. He earned his B.E. in Electronics and Instrumentation Engineering from BITS-Pilani, India, followed by an M.S. and Ph.D. in Electrical and Systems Engineering from the University of Pennsylvania, where he collaborated with faculty from both engineering and the Wharton School. His multidisciplinary research focuses on Internet economics, communication systems, and social networks, employing advanced quantitative methods to analyze complex data sets. Dr. Sen's work has garnered recognition in top academic journals and media outlets like The Wall Street Journal and MIT Technology Review. He has received numerous accolades, including the INFORMS ISS Design Science Award and the IEEE INFOCOM Best Paper Award. As the founder of the Smart Data Pricing Forum, he promotes collaboration between academia and industry on Internet pricing research. Additionally, he co-founded DataMi, a startup providing innovative Internet pricing solutions for telecom providers. Dr. Sen's commitment to education is reflected in his leadership roles within various academic programs, where he continues to inspire students through his research and teaching initiatives.
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4.8 course rating
66 ratings
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