Mastering OpenAI & Google Gemini APIs: Build AI Applications

About Mastering OpenAI & Google Gemini APIs: Build AI Applications

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!