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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.

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