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Coursera

Generative AI: OpenAI API and Prompt Engineering

KodeKloud via Coursera

Overview

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Generative AI is reshaping every industry — and building with it starts here. This course gives you the practical foundation to engineer AI-powered applications immediately, combining a clear understanding of how large language models work with hands-on OpenAI API development and real project work. You'll begin by setting up the OpenAI platform: account configuration, secure API key generation, model selection, and library navigation. You'll then explore the mechanics of modern generative AI — how transformers and attention mechanisms power LLMs, how tokenization shapes model behavior, and how prompt engineering techniques including zero-shot, few-shot, and grounding strategies improve output accuracy. You'll also examine bias, fairness, and reinforcement learning, giving you the perspective needed to build responsibly. In the final module, you'll build three working applications: a recipe generator, an article translator, and an AI research assistant using the Chat Completions API — applying fine-tuning, embeddings, and text-to-speech through live project work. Designed for software engineers, data scientists, IT professionals, and career changers entering the AI field. Basic programming knowledge is recommended. No prior AI experience is required.

Syllabus

  • Introduction to OpenAI Platform
    • This module lays the foundation for your AI journey by introducing OpenAI and its platform. You will explore OpenAI’s history, how it works, and why it is essential for industries today. You'll also learn how to set up your account, navigate the platform, and understand crucial concepts like API keys and OpenAI models. By the end, you’ll be equipped with the knowledge to start working with OpenAI tools.
  • Transformers, Attention, Ethics
    • This module provides a comprehensive exploration of artificial intelligence, from its roots in rule-based systems to the current advances in deep learning. You'll learn how transformers and attention mechanisms drive generative AI, and dive into the crucial aspects of prompt engineering, tokenization, and fine-tuning. Additionally, you'll explore important topics like bias, fairness, and reinforcement learning, all while considering ethical implications of AI technologies.
  • Text Generation - Prompt Engineering, AI Assistants, Fine-Tuning
    • This module dives deep into the power of text generation using OpenAI, focusing on both theoretical and practical applications. You'll explore prompt engineering techniques, how to generate API keys securely, and work on projects like creating a recipe generator, translating articles, and generating short stories. Additionally, you'll learn about sentiment analysis, creating AI assistants, and advanced techniques like fine-tuning and embeddings, all while gaining hands-on experience through labs and real-world projects.

Taught by

Mumshad Mannambeth

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