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Understanding and Applying Numerical Optimization Techniques

Course Summary

Optimization is all about smart trade-offs given difficult choices. This course focuses on three specific aspects of numerical optimization: correctly setting up optimization problems, linear programming, and integer programming.


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    Course Syllabus

    Course Overview
    - 1m 40s

    —Course Overview 1m 40s
    Introducing Numerical Optimization
    - 30m 43s

    —Choices, Trade-offs, and Optimization 6m 24s
    —Objectives, Constraints, and Decision Variables 5m 16s
    —Optimality and Feasibility 5m 8s
    —Applications of Optimization 6m 55s
    —An Optimization Case Study 6m 59s
    Understanding Linear Programming
    - 42m 52s
    Implementing Linear Programming in Excel
    - 33m 27s
    Implementing Linear Programming in R
    - 29m 35s
    Implementing Linear Programming in Python
    - 24m 23s
    Understanding Integer Programming
    - 38m 34s
    Implementing Integer Programming in Excel
    - 16m 43s
    Implementing Integer Programming in R
    - 6m 42s
    Implementing Integer Programming in Python
    - 14m 42s


Course Fee:
USD 29

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

This course is listed under Open Source , Development & Implementations and Data & Information Management Community

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