
Explore how Gemini fits into data science, processing text and images, and learn to build and deploy genai apps using Google AI studio and Streamlit.
Explore Gemini's capabilities, including text generation via the Gemini API, document and media processing (images, videos, and audio), and long context reasoning with JSON output for structured data.
Explore Gemini's conversational capabilities, from answers on chemistry and Indian geography to prompts that craft a blog post on Python and an image-based blog on a fruit with Gmail integration.
Discover how the Germany extension for Gemini connects Google Drive, Gmail, Google Flights, Maps, YouTube, and more to automate tasks and generate prompts like flight searches and email summaries.
Compare Gemini models 1.5 flash and 1.5 pro, highlighting multimodal inputs and text outputs for fast, creative apps or higher accuracy with 1.5 pro.
this module introduces large language models (LLMs), explains how they understand and generate language, and traces Gemini's evolution from Bard, models available, and uses like data cleaning and feature engineering.
Explore google ai studio to set up gemini prompts, obtain api key, and work with chat and structured prompts while adjusting token counts, temperature, safety, and stop sequences for integration.
Explore advanced Google AI Studio options by creating a custom tuned model from Google Sheets or CSV data, then apply it to structured prompts.
Explore inputting images into Google Gemini via Google AI Studio, building prompts and outputs like animal or not an animal; adjust temperature and safety settings, and review Python upload code.
Learn to obtain an API key to connect Google AI Studio Gemini with your codebase, enabling prompts access in JavaScript, Python, Kotlin, and Swift.
Build a python-based blog post generator by integrating Gemini with Google Colab, using a Google AI Studio chat prompt and API key to output a 150-word post.
Demonstrates creating a Jupyter notebook in PyCharm, installing Miniconda, configuring the Python interpreter, and running Hello World to access the notebook via a browser link for future Streamlit Gemini work.
Install and set up PyCharm to create a Python project with a virtual environment, run a hello world script, and explore Django, Flask, and Jupyter in web and data science.
Learn how Streamlit, a Python UI library, enables production-ready, data-driven AI apps and cloud deployment, addressing ease of running and multimodal use in Gemini projects.
Learn to build genai apps with Streamlit by creating a Python project, installing Streamlit, and rendering interactive elements like charts, markdown, code, a chat input, and Gemini integration.
Learn to deploy a Streamlit project using the Streamlit Community Cloud by connecting your code to a GitHub repo, pushing changes, and launching the app to a shareable link.
Kick off the capstone project part 1 by building a blog post generator in Streamlit, integrating Gemini, and deploying a chat-like interface with session state in Google AI Studio.
Capstone project part 2 adds image support in Streamlit by uploading jpg or png files, rendering them in the chat, and sending them to Gemini to generate a blog post.
Build a production ready GenAI app with Streamlit and Gemini that generates a 150 word blog post from a topic or image, showcased as a job ready blog post generator.
Discover how Gemini's text and multimodal capabilities power Streamlit apps, master prompts with Google AI Studio, and explore data science-driven, interactive tools from a capstone project to deployment.
Install Python 3 on Mac (Windows steps are similar), set up PyCharm or Atom, create a first Hello world program using print, then run it to see exit code zero.
Learn how a Python program runs line by line, using variables as containers and exploring strings, numbers, concatenation, and str conversions to avoid type errors.
Explore how Python variables hold values, enable operations on integers, floats, strings, and booleans, and how the type function reveals data types and dynamic typing lets a variable change types.
Learn basic arithmetic in Python using integers and floats, including division, multiplication, and the modulus operator. Understand order of operations and how parentheses affect results.
Learn to work with strings by indexing and slicing, handle quotes and apostrophes, use escape sequences, and extract characters or substrings with zero-based or negative indices and non-inclusive ranges.
Welcome to the Complete Gemini Course: Build GenAI Apps with Streamlit
Are you looking to harness the power of Generative AI with Google’s Gemini model?
Do you want to build AI-powered applications quickly and efficiently?
Are you interested in using Streamlit to create interactive, real-world GenAI applications?
Do you want a structured course that takes you from the basics to advanced implementations of Gemini AI?
If you answered yes, then this course is for you!
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.
What You’ll Learn:
Introduction: Begin with an overview of the course and discover the potential of data science through interactive applications.
Understanding LLMs and Gemini: Dive deep into LLMs, explore the evolution of Gemini, and learn how to utilize its features within the Google ecosystem.
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.
Setting Up Your Development Environment: Get hands-on with setting up essential libraries in PyCharm and Jupyter Notebook on both Mac and Windows platforms.
Introduction to Streamlit: Learn how to use the Streamlit framework to create dynamic data applications with widgets and visualizations.
Hands-On Project: Rebuild the blog post generator app using Streamlit, adding image input functionality to showcase Gemini’s multimodal capabilities.
Conclusion: Explore additional project ideas to further apply your newly acquired skills and reinforce your learning.
Extra: Python Basics
Includes a helpful appendix on setting up your Python environment, understanding variables, data types, basic arithmetic, and string manipulation.
What Makes This Course Stand Out?
Comprehensive & Hands-On Learning: Start with foundational AI concepts and progress to building production-ready GenAI applications.
Practical Implementation with Streamlit: Learn how to create AI-powered web apps effortlessly.
Google’s Gemini AI Model in Action: Gain hands-on experience using the Gemini API for text generation, image recognition, and more.
End-to-End Project-Based Approach: Work on real-world projects that showcase Gemini AI's capabilities.
Beginner to Advanced Progression: Whether you're new to AI or an experienced developer, this course covers everything you need to succeed.
Important Announcement: This course will continue to be updated with the latest advancements in AI, including new features from Google’s Gemini model and best practices for AI-driven app development.
Why This Course Is Essential:
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.
Whether you're a seasoned professional looking to expand your AI toolkit or a beginner eager to explore the world of artificial intelligence, this course offers valuable insights and practical skills. By the end of this course, you'll have a solid grasp of Google’s Gemini AI model and how to use it effectively in your GenAI apps. Join us and embark on a journey to master Google’s Gemini AI model with Python and Streamlit.
KEY BENEFITS OF MASTERING GENERATIVE AI & STREAMLIT
Generative AI is revolutionizing the tech industry, enabling developers to build intelligent applications with minimal effort. By mastering Gemini AI and Streamlit, you will:
Enhance Your AI Development Skills: Build AI-powered applications from scratch.
Increase Your Career Prospects: AI expertise is in high demand across industries.
Create Cutting-Edge AI Applications: Learn practical implementation beyond theory.
Stay Ahead in the AI Revolution: Work with the latest advancements in Generative AI.
KEY TAKEAWAY:
By the end of this course, you’ll have a solid grasp of Google’s Gemini AI model and how to use it effectively in your GenAI apps. You’ll walk away with the skills to develop AI-powered applications with Streamlit and confidently apply your knowledge in real-world scenarios.
So, let’s get started on your journey to mastering Generative A.I. Enroll Now and start your AI journey today!
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, including JavaScript, Node.js, Angular, React, React Native, MEAN, MERN, Java, Spring Boot, Kotlin, Native Android App Development, and Git.
Gurkeerat’s passion for innovation and problem-solving has led him to participate in numerous developer hackathons, where he has consistently performed at a high level. Notably, he secured 1st place in the prestigious Bengaluru Open Mobility Challenge '23, demonstrating his ability to apply his skills to real-world challenges.
In addition to his professional achievements, 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.