Certified Operation Data Analytics Professional (CODA-Pro)

Learn the fundamentals, how to model future demand uncertainties ,insights into a spectrum of real-world business cases

What you'll learn
Learn how to transform data into actionable insights and use it to make informed decisions in various business scenarios.
Gain knowledge and skills to effectively match supply with demand, even in uncertain settings, using methods like optimization, simulation, and decision trees.
Master the fundamentals of descriptive,predictive analytics for operations,& develop the ability to make prescriptive recommendations to solve real-world issues
Learn how to evaluate and compare decisions in the face of uncertainty, including measuring risk and reward, using simulation models to estimate outcomes
Requirements
A fundamental understanding of mathematics and analytical thinking will be beneficial for grasping the course concepts, especially in modules that involve optimization, simulation, and decision trees.
Depending on the course materials, participants may need access to specific software tools or spreadsheet applications. Ensure you have the necessary software or access to it before starting the course.
Description
About this Course -Certified Operation Data Analytics Professional (CODA-Pro)
This course is designed to impact the way you think about transforming data into better decisions. Recent extraordinary improvements in data-collecting technologies have changed the way firms make informed and effective business decisions.
The course on operations analytics, taught by three of leading experts, focuses on how the data can be used to profitably match supply with demand in various business settings. In this course, you will learn how to model future demand uncertainties, how to predict the outcomes of competing policy choices and how to choose the best course of action in the face of risk.
The course will introduce frameworks and ideas that provide insights into a spectrum of real-world business challenges, will teach you methods and software available for tackling these challenges quantitatively as well as the issues involved in gathering the relevant data. This course is appropriate for beginners and business professionals with no prior analytics experience. All 4 modules can also be learnt by planning as week 1 to week 4 schedule .
Module 1 - Introduction, Descriptive and Predictive Analytics
In this module you’ll be introduced to the Newsvendor problem, a fundamental operations problem of matching supply with demand in uncertain settings. You'll also cover the foundations of descriptive analytics for operations, learning how to use historical demand data to build forecasts for future demand. Over the week, you’ll be introduced to underlying analytic concepts, such as random variables, descriptive statistics, common forecasting tools, and measures for judging the quality of your forecasts.
Module 2 -Prescriptive Analytics, Low Uncertainty
In this module, you'll learn how to identify the best decisions in settings with low uncertainty by building optimization models and applying them to specific business challenges. During the week, you’ll use algebraic formulations to concisely express optimization problems, look at how algebraic models should be converted into a spreadsheet format, and learn how to use spreadsheet Solvers as tools for identifying the best course of action.
Module 3- Predictive Analytics, Risk
How can you evaluate and compare decisions when their impact is uncertain? In this module you will learn how to build and interpret simulation models that can help you to evaluate complex business decisions in uncertain settings. During the week, you will be introduced to some common measures of risk and reward, you’ll use simulation to estimate these quantities, and you’ll learn how to interpret and visualize your simulation results.
Module 4- Prescriptive Analytics, High Uncertainty
This module introduces decision trees, a useful tool for evaluating decisions made under uncertainty. Using a concrete example, you'll learn how optimization, simulation, and decision trees can be used together to solve more complex business problems with high degrees of uncertainty. You'll also discover how the Newsvendor problem introduced in module 1 can be solved with the simulation and optimization framework introduced in module 2 and 3.
Who this course is for:
Ideal for professionals looking to enhance their analytical skills and apply data-driven decision-making techniques in their roles.
Suitable for those in supply chain and operations management seeking to optimize supply and demand processes.
Great for individuals with an interest in data analytics, even if they have no prior experience, as the course is designed for beginners.
Relevant for executives and managers who want to improve their ability to make strategic decisions based on data and minimize risks in uncertain business environments.

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