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Quick Facts

Medium Of InstructionsMode Of LearningMode Of Delivery
EnglishSelf Study, Virtual ClassroomVideo and Text Based

Course Overview

Data, Models, and Decisions in Business Analytics, a certification course by edX, brings the ability to know, optimize, and alter the ways of business operations, marketing, transportation, and finance. In this course, the candidate will cover various topics and learn more in-depth about the various skills associated with each topic. Starting from introduction to Probability, where the candidate will go through random variables; Normal, Binomial, Exponential distributions with their various applications. Then the candidate will move up to estimation, where they will learn about Sampling, confidence intervals & hypothesis testing. Advancing further, the candidate will also learn about Regression, Linear Optimization & Dynamic Optimization. 

Any student or professional with knowledge of undergraduate probability, statistics, and linear algebra and with knowledge of Python, basic programming concepts can pursue this course. The programme will be completed within 12 weeks. Candidates need to dedicate 8 to 10 hours every week to attend this Data, Models, and Decisions in Business Analytics training.

Please note: This programme cannot be registered by students from Iran, Crimea, Cuba, and the Crimea region of Ukraine. 

The Highlights

  • The course duration is 12 weeks
  • Certificate provided by edX
  • 100% online learning
  • Free of cost programme
  • In association with ColumbiaX 
  • Instructors hail from Columbia University
  • 8 - 10 hours of weekly timing

Programme Offerings

  • instructor led training
  • Online exercises and assignments

Courses and Certificate Fees

Certificate AvailabilityCertificate Providing Authority
yesColumbia University, New York

Eligibility Criteria

Education

Students should have familiarity with basic programming concepts in the programming language and even have knowledge of Python. Basic concepts of linear algebra, statistics probability, and procedural programming language would be beneficial. 

Certification Qualifying Details

Participants will be given a Data, Models, and Decisions in Business Analytics certification by edX only after they make the payment for the certificate and complete the programme. 

What you will learn

Business analytics knowledge

After completion of the Data, Models, and Decisions in Business Analytics certification syllabus, the candidates will get to know:

  • Get knowledge about dynamic optimization
  • To develop the idea of the introduction to probability
  • To understand the concepts of probability, stochastic modeling, statistics
  • To develop systematic frameworks in a dynamic setting
  • To solve decision problems in business applications under uncertainty
  • To learn the underlying model and to use historical data
  • To get an idea of dummy variables, linear regression, regression

Who it is for

The course is recommended to be beneficial for: 

  • People working in the field like data analysts, business analysts, and wanting to brush their knowledge about the subject.
  • People want to start afresh with an edge over the others.

Admission Details

The candidates can apply for this Data, Models, and Decisions in Business Analytics classes by following the steps that are given below. 

Step1: Firstly, the programme URL https://www.edx.org/learn/business-analytics/columbia-university-data-models-and-decisions-in-business-analytics should be clicked. 

Step 2: Thereafter, candidates need to press on the ‘Enrol Now’ tab.

Step 3: Then candidates need to create an account. They need to set a password as well. 

Step 4: Once the account is created, candidates can further proceed to check out the programme. 

Step 5: Then, they can make the payment from the desired mode of payment. 

The Syllabus

  • Random variables
  • Normal
  • Binomial
  • Exponential distributions
  • applications

  • sampling
  • confidence intervals
  • hypothesis testing

  • linear regression
  • dummy variables
  • applications

  • Non-linear optimization
  • Discrete Optimization
  • applications

  • decision trees

Instructors

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