Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Analytics for Decision Making

via SWAYAM Plus

Overview

Google, IBM & Meta Certificates – 40% Off
One plan covers every Professional Certificate on Coursera.
Unlock All Certificates

This course introduces learners to the principles and practices of using analytics to support effective decision-making in business and organizational contexts. It focuses on how data, statistical models, and analytical tools can be leveraged to derive insights and guide strategic actions. Learners will gain an understanding of key concepts such as descriptive, diagnostic, predictive, and prescriptive analytics. The course emphasizes the application of analytical thinking to real-world problems, enabling participants to make evidence-based decisions that enhance efficiency, performance, and competitiveness. By the end of the course, learners will be able to interpret data-driven insights and apply them to informed managerial and operational decisions.

Intended audience

Data Analyst / Statistical Analyst, Business Analyst / Decision Support Specialist, Research Analyst / Quantitative Analyst, Data Scientist (Entry Level), Business Intelligence (BI) Analyst / Analytics Consultant

Prerequisites

  • UG 1st year onwards

Assessment & certification

  • Assessment fee: Included — no extra fee
  • Assessment mode: Online proctored
  • Assessment type: MCQ
  • Assessment provider: Amity Online
  • Certificate provider: SWAYAM Plus and Amity Online

NCrF level: 7 (NCrF credit-eligible)

Syllabus

  • Week 1: Module I: Data Science: Probability
  • Week 2: Module II: Data Science Inference
  • Week 3: Module III: Data Science Modeling
  • Week 4: Module IV: Statistical Thinking for Data Science
  • Week 5: Module V: Bayesian Modelling and Linear Regression

Taught by

Dr. Harshita Singh

Reviews

Start your review of Analytics for Decision Making

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.