Complete Gemini Course: Build GenAI Apps with Streamlit

In this course, you'll learn everything you need to know about building Interactive GenAI Apps with Gemini, Python, Streamlit and Google AI Studio.

Unlock the potential of Google's Gemini AI model with our comprehensive beginner-friendly course! Designed for enthusiasts at all levels, this course will guide you through the fascinating world of Gemini, Generative AI, and Large Language Models (LLMs) using Google AI Studio, Python and Streamlit.

Have you ever wondered what terms like Gemini, Generative AI, and LLMs mean? Are you curious about how these cutting-edge technologies can be harnessed for real-world applications? If so, this course is perfect for you. You'll gain a solid understanding of these concepts and learn how to leverage Gemini to its fullest potential.
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➡️ Important Links:
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➡️ About the Instructor:
Gurkeerat Singh is a Senior Software Engineer with over 5 years of comprehensive experience in full-stack development. He excels in a diverse array of technologies. Gurkeerat is dedicated to sharing his knowledge and expertise with others. At Job Ready Programmer, he plays a pivotal role in teaching and mentoring students in the latest technologies, including Gemini AI. His commitment to education ensures that his students are well-prepared to stay ahead of the curve in the rapidly evolving tech industry.
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➡️ Course Highlights:
1. Introduction: Begin with an overview of the course and discover the potential of data science through interactive applications.
2. Understanding LLMs and Gemini: Dive deep into LLMs, explore the evolution of Gemini, and learn how to utilize its features within the Google ecosystem.
3. Google AI Studio and Python Integration: Master both basic and advanced features of Google AI Studio, secure your Gemini API key, and build a Python-powered blog post generator.
4. Setting Up Your Development Environment: Get hands-on with setting up essential libraries in PyCharm and Jupyter Notebook on both Mac and Windows platforms.
5. Introduction to Streamlit: Learn how to use the Streamlit framework to create dynamic data applications with widgets and visualizations.
6. Hands-On Project: Rebuild the blog post generator app using Streamlit, adding image input functionality to showcase Gemini’s multimodal capabilities.
7. Conclusion: Explore additional project ideas to further apply your newly acquired skills and reinforce your learning.
8. Extra: Python Basics
- Includes a helpful appendix on setting up your Python environment, understanding variables, data types, basic arithmetic, and string manipulation.
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➡️ Timestamps:
00:00 Introduction to Data Science
03:40 What is Gemini AI?
05:36 Course Overview
06:49 Capstone Project Details
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