- This course focuses on understanding how computer vision technology can be applied in business contexts to enhance decision-making, improve operational efficiency, and drive innovation. Students will learn how AI can process visual data, detect patterns, and automate key business processes like quality control, product analysis, and customer insights.
- Level: Basic
- Prerequisites: Basic understanding of business analytics, no coding required.
- Assessments: Weekly Micro Assessments, Final Project-based Assessment.
- Job Roles Applicability: Business Analyst, Product Manager, Operations Manager, Marketing Analyst.
Week 1 - Introduction to Computer Vision in Business
Learning OutcomeUnderstand the fundamentals of computer vision and its applications in business.
1.1 Introduction to computer vision and its role in business.1.2 Key business use cases (e.g., quality control, inventory management).
1.3 Overview of how computer vision algorithms function.
Practical Component
Introduction to a visual recognition tool, applying it to a sample business scenario (e.g., object detection in product inventory).
Week 2 - Data Collection and Preparation for Computer Vision
Learning OutcomeUnderstand how to collect and prepare visual data for computer vision tasks in a business environment.
2.1 Types of visual data in business applications (images, videos, and camera feeds).2.2 Data collection methods and business use case identification.
2.3 Data preprocessing for computer vision tasks.
Practical Component
Collect and clean sample images for a specific business case (e.g., product classification).
Week 3 - Understanding current Computer Vision Algorithms
Learning OutcomeLearn about various computer vision algorithms and their application to business use cases.
3.1 Image classification algorithms (e.g., CNNs).3.2 Object detection and segmentation techniques.
3.3 Deep learning applications in computer vision.
Practical Componenet
Build a basic object recognition model to classify products in an inventory.
Week 4 - Automating Business Processes, achieving efficiency, with Computer Vision
Learning OutcomeExplore how computer vision can automate business processes and increase efficiency.
4.1 Business automation opportunities with computer vision (e.g., quality checks, monitoring, employee efficiency).4.2 Integrating computer vision with other AI technologies for enhanced business automation.
4.3 Challenges in deploying computer vision in business processes.
Practical Componenet
Create a simple quality control system for detecting defective products using a computer vision algorithm.
Week 5 - Leveraging Computer Vision for Customer Insights and Marketing
Learning OutcomeLearn how computer vision can be used to gain insights into customer behavior and improve marketing strategies.
5.1 Analyzing customer interactions through visual data.5.2 Retail analytics and visual product placement strategies.
5.3 Consumer sentiment analysis using computer vision (e.g., facial recognition in advertisements).
Practical Component
Analyze customer interaction with a marketing campaign (e.g., tracking customer reactions to a visual ad).
Week 6 - Final Project and Assessment
Learning OutcomeApply the knowledge gained throughout the course to a real-world business problem using computer vision techniques.
6.1 Develop a solution using computer vision to address a business challenge (e.g., product classification, defect detection).6.2 Final presentations and peer reviews.
6.3 Evaluation based on practical application and outcomes
Practical Component
Present a computer vision-based solution to a business problem and demonstrate its effectiveness.