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Product Reviews Text-based Search - OpenAI Text Embedding
In this two-hour guided project, you will utilize the OpenAI API for text-based document search using the OpenAI text embedding model.
SphereZone, a leading security system company, has enlisted your expertise to enhance their customer product review analysis system. They require an intelligent text-based document search algorithm to parse through their customer reviews and evaluate how individuals are discussing various aspects of their product. You will be provided with a dataset containing 89 customer reviews related to their Solar-Powered Outdoor Security Camera. As an AI Engineer, your objective is to utilize OpenAI text-embedding models to develop a Python application for this purpose.
To get the most out of this course, you'll need access to the OpenAI API Key and a basic understanding of data analysis concepts, including data types, and data manipulation, along with some familiarity with Python.
Duration
6 Months
Institution
Coursera
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into Coursera.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$100
Total Est. Investment
$100
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the Product Reviews Text-based Search - OpenAI Text Embedding program at Coursera are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.