Build your own AI powered smart kitchen + recipe assistant

In Collaboration With
Google GeminiGoogle Gemini
MistralMistral

Course Outline

Learn to build FoodEase: a smart fridge analyzer and recipe generator that identifies food items in your fridge using AI. By simply uploading an image, users receive detailed insights about their fridge contents and can discover delicious recipes tailored to the ingredients available

Learning Outcomes

  • Implement image recognition and segmentation techniques using a multimodal Large Language Model (LLM)
  • Develop skills in advanced prompting to enhance AI responses and functionality
  • Utilize text prompting techniques with Groq’s hosted LLMs for generating customized recipe suggestions and detailed instructions

Who Is This Course For?

  • Tech enthusiasts interested in AI and its applications in daily life.Developers eager to explore AI-based solutions for home automation.Students or hobbyists looking to build real-world AI applications from scratch.Beginner to intermediate coders interested in working with image recognition, recipe generation, and data visualization.

Pre-requisites

  • Basic familiarity with Python programming.Access to an internet connection to install packages and interact with APIs.Enthusiasm for working with new technology and building practical AI applications.No prior experience in AI or machine learning is required.
LevelIntermediate
Your Instructor
AL
Annie Liao
Duration6 hours
Showcasing
Google GeminiGoogle Gemini
Progress0/6 chapters complete
0%
Your certificateComplete course to get your certificate
Certificate of Completion
Course Name
Why Enroll?
Are you curious about using AI to simplify everyday tasks? Do you want to understand the basics of image recognition and create a personalized recipe recommendation system? This course will guide you step-by-step through creating a functional AI-powered app that identifies ingredients and suggests recipes—all from a simple photo of your fridge.
With hands-on exercises, you’ll gain experience in project setup, secure API access, and interactive app design using Python and Streamlit. By the end, you’ll have the knowledge to develop AI-powered projects independently, equipping you with skills for the future of smart home technology.
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