Conclusion

Congratulations! You have successfully completed the “Google Gemini: Advanced AI Applications” course. You did a great job. You’ve been on a challenging journey of AI technologies with Google Gemini and have gained a comprehensive understanding and implementation skills along the way.

Key takeaways

Let’s recap what you’ve learned throughout the course:

• Getting Started
  We started with the course overview to get an idea of our journey. Then, we learned the basics of Google Gemini, its workflow, comparison with other models. We also learned about the Gemini APIs and its setup to get started with the implementation details.

• Content Generation Using Gemini Models
  Here, we moved to the implementation part for different scenarios using the Gemini models. We had practical experience in text-to-text and image-to-text generation for real-world scenarios. We also implemented multimodal prompting by passing multiple format inputs, such as text and images, to the model.

• Building RAG Applications with Google Gemini
  We used the RAG technique with the Gemini model using the LangChain to generate responses for a real-world scenario. We started with a basic understanding of RAG and its implementation steps. We gained an understanding of LangChain and how it helps us perform RAG tasks. We implemented text retrieval using the gemini-1.5-pro-latest. We also implemented image retrieval using gemini-1.5-pro-latest.

• Customer Service Assistant—Multimodal RAG Interface
  To extend the functionality of the RAG system with Google Gemini, there was a mini project to implement the RAG with multimodal inputs, text, and image.

You’ve made prominent progress in understanding and implementing Google Gemini’s capabilities. The skills and knowledge you’ve gained will help you work on different AI applications using Google Gemini Power.