Master the latest AI models from OpenAI, Anthropic, and Google. Learn to build applications that process text, images, audio, and video with cutting-edge multimodal techniques.
Explore the current landscape of state-of-the-art LLMs. Understand what makes a model "frontier" - massive scale, emergent capabilities, and architectural innovations that push the boundaries of AI.
Compare the three leading frontier models: GPT-4's versatility, Claude's long-context expertise, and Gemini's native multimodality. Learn when to use each model based on your application requirements.
Discover how modern AI models perceive and understand the world beyond text. Learn about vision transformers, audio processing, video understanding, and how to combine modalities for richer AI applications.
Master techniques for working with massive context windows (100K-1M+ tokens). Learn how models handle long documents, maintain coherence, and solve problems that require reasoning over extensive information.
Learn production-ready techniques for integrating frontier models into your applications. Cover API authentication, rate limiting, error handling, cost optimization, and monitoring.
By the end of this module, you will:
Build a real-world application that processes text, images, and audio simultaneously. Create an intelligent document analyzer that can extract insights from PDFs with embedded images, audio transcripts, and complex tables.
What you'll build:
Duration: 4-5 hours | Stack: Python, OpenAI API, FastAPI, Docker
Start Lab →Test your understanding with 15 advanced questions covering frontier models, multimodal AI, long-context processing, and API best practices. You need 70% or higher to pass.