Online Course – Certified Professional Internship in Analytics for Decision Making from the University of Minnesota

Enhance your career with business analytics. Learn the basics of contract analysis and prescriptive analysis to expand your career options in business analytics.

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קורס אונליין - התמחות מקצועית מוסמכת בAnalytics for Decision Making של University of Minnesota

Professional Certificate

Beginners

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Visualizing decision-making problems using predictive models.
  • Linear optimization.
  • Simulation methods.
  • Analytical techniques.
  • Modeling and simulation.

What you will learn in the course

Courses for which the course is suitable

  • Data Analyst
  • Data Scientist
  • Analytics Project Manager
  • Business consultant
  • Strategic planner
  • Optimization Expert
  • Predictive Model Developer
  • Decision-making manager
  • Business Analyst
  • Simulation expert

Internship – a four-part course series

The analytics area consists of four pillars:

  • Descriptive analytics: deals with studying data to identify patterns (e.g., visualization, BI).
  • Predictive analytics: identifies what might happen next (e.g., data mining, time series prediction).
  • Causal analytics: determines a causal relationship.
  • Prescriptive analytics: Helps in formulating decisions.

This specialization focuses on prescriptive analytics. It will review basic predictive modeling techniques for estimating values ​​of relevant parameters, and then use optimization and simulation techniques to formulate decisions.

What will you learn?

  • Visualizing decision-making problems using predictive models.
  • Linear optimization.
  • Simulation methods.

Hands-on Learning Project

Upon completion of the internship, learners will complete four different types of projects using analytical, modeling, and simulation techniques to recommend and inform decisions regarding a wide range of business problems.

Our courses offer a combination of conceptual and practical learning.

Details of the courses that make up the specialization

Introduction to predictive models

Welcome to the “Introduction to Predictive Models” course, the first course in the “Decision Analytics” specialization at the University of Minnesota.

This course will introduce you to the concepts, processes, and applications of predictive modeling, with an emphasis on linear regression and time series forecasting models and their practical use in Microsoft Excel. At the end of the course, you will be able to:

  • Understand the concepts, processes, and applications of predictive modeling.
  • Understand the structure and intuition behind linear regression models.
  • Fit simple and multivariate linear regression models to data.
  • Understand the over- and under-fitting problem and perform simple model selection.
  • Understand the concepts of time series forecasting.
  • Fit multiple time series forecasting models in Excel.
  • Understand different types of data and how to use them in predictive models.
  • Use Excel to prepare data for predictive models.

To succeed in this course, you should know basic math and basic statistics. The course does not require a programming background, but you should be familiar with basic Excel operations.

Skills you will acquire

  • Predictive analytics
  • Data preparation
  • Time series forecasting
  • Linear regression

Decision-making optimization

In a data-driven world, companies want to know what the best “move” is. Prescriptive analytics is the field that can provide answers to these questions. This course will introduce the basic principles of linear optimization for decision making.

We will learn to identify decision variables, objective function, and constraints of a problem, and use them to formulate and solve an optimization problem using Excel.

Skills you will acquire

  • Analytics
  • Operations Management
  • Linear Programming (LP)
  • Mathematical optimization

Advanced decision-making models

This course is designed to connect data and models for industrial decision-making scenarios. We will understand how linear optimization can be used to formulate decision problems and provide optimal solutions.

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

Skills you will acquire

  • Analytics
  • Operations Management
  • Linear Programming (LP)
  • Mathematical optimization

Simulation models for decision making

This course is designed for students interested in learning simulation techniques for solving business problems. We will learn how to explore different outcomes using the simulation model.

The course will introduce you to advanced Excel techniques to model and perform simulation models, including Monte Carlo simulation techniques.

After completing the course, the student will be able to develop advanced simulation models to explore a wide range of business environments.

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