What you'll learn:
- What is the OpenAI API
- LLMs, transformers, and high level how they work
- How to generate text with the OpenAI API
- How to summarize with OpenAI API
- How to translate with OpenAI API
- How to Fine Tune GPT 3.5 Turbo
- How to use OpenAI API with other libraries
- Deploying OpenAI applications with GCP and AWS
- How to use GPT Builder to create custom GPTs
Ready to build powerful applications fueled by leading Large Language Models? This comprehensive course provides developers with the practical skills to harness the OpenAI API ecosystem and the Google Gemini & Translate APIs. Go beyond theory and learn to integrate cutting-edge AI capabilities into your projects, from setup and prompt engineering to fine-tuning and deployment.
We cover the essential concepts and provide hands-on examples to ensure you can confidently build real-world AI solutions. Whether you want to create intelligent chatbots, automate content creation, translate languages, generate images, or analyze data with computer vision, this course provides the roadmap.
In this course, you will master:
LLM & Prompt Engineering Fundamentals: Understand Transformers, advanced Prompt Engineering (Zero/Few-Shot, Chain of Thought, Frameworks, Evaluation), RAG, AI Agents, and Open vs Closed Source Models.
OpenAI API Setup & Architecture: Get your OpenAI API Key, set up your environment, understand pricing/limits, and grasp essential AI Application Architecture principles.
Core OpenAI APIs (Text & Chat): Utilize the Completions API and Chat Completion API for tasks like translation, summarization, sentiment analysis, classification, and building interactive chatbots (including a financial statement analysis project).
OpenAI Multimodal APIs: Integrate Image Generation (DALL-E), Text-to-Speech (TTS), and Computer Vision (GPT-4V) capabilities into your applications with practical examples (phone wallpapers, blog post transcription, calorie counting).
Google Gemini & Translate APIs: Get started with the Google Gemini API via AI Studio & Colab, explore Large Context Window use cases, and leverage the Google Translate API for basic and advanced translation tasks (including a subtitle translation project).
Building RAG Pipelines: Implement Retrieval Augmented Generation (RAG) from scratch to ground LLM responses in external data.
Fine-Tuning & Deployment: Learn the concepts of Fine-Tuning, fine-tune a model using the OpenAI API, use GPT Builder, and understand how to deploy an AI application.
AI Ethics: Discuss the crucial dos and don'ts of responsible AI development.
This course is designed for developers, engineers, and technical individuals aiming to build practical AI applications. By the end, you'll possess the skills to leverage the OpenAI and Google AI ecosystems effectively and ethically.
Enroll today and start building the next generation of AI-powered applications!
