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Overview
The field of analytics is typically built on four pillars: Descriptive Analytics, Predictive Analytics, Causal Analytics, and Prescriptive Analytics. Descriptive analytics (e.g., visualization, BI) deal with the exploration of data for patterns, predictive analytics (e.g., data mining, time-series forecasting) identifies what can happen next, causal modeling establishes causation, and prescriptive analytics help with formulating decisions.
This Analytics for Decision Making course offered by Coursera in partnership with University of Minnesota focuses on the Prescriptive Analytics (the final pillar). This specialization will review basic predictive modeling techniques that can be used to estimate values of relevant parameters, and then use optimization and simulation techniques to formulate decisions based on these parameter values and situational constraints.
The specialization will teach how to model and solve decision-making problems using predictive models, linear optimization, and simulation methods.
Applied Learning Project
- By the end of this specialization, learners will have completed four different types of projects using analytics, modeling, and simulation techniques to prescribe and inform decisions for a wide range of business problems. The courses provide a combination of conceptual and hands-on learning.
Skills You Will Gain:
- Data Analysis
- Decision Making
- Business Analysis
- Probability & Statistics
- Mathematics
- Spreadsheet Software
- General Statistics
- Mathematical Theory & Analysis
- Linear Algebra
Programme Structure
Courses include:
- Introduction to Predictive Modeling
- Optimization for Decision Making
- Advanced Models for Decision Making
- Simulation Models for Decision Making
Key information
Duration
- Part-time
- 1 months
- Flexible
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Campus Location
- Mountain View, United States
Disciplines
Data Analytics View 177 other Short Courses in Data Analytics in United StatesWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Beginner level
- Recommended experience: Familiarity with Microsoft Excel
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
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International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
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Domestic
Applies to youIn-StateFree
Additional Details
- This short course is included with Coursera Plus subscription
Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.
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