Are you ready to dive into the world of AI and unlock the potential of Google's most advanced AI technologies? Welcome to the Gemini Era Study Jams!

Through interactive sessions and hands-on coding exercises, you'll learn how to use the Google's gemini-pro and pro vision models to solve a wide range of real-world problems.

You will learn state-of-the-art prompting techniques to get the most out of these models.

We will also walk you through building an AI system that can query your documents & data using LangChains & the Gemini API.

Join us and unlock the power of Gemini API. Let's unleash the full potential of AI together!

Target Audience: Developers with basic Python programming experience and an interest in using large language models (LLMs).

notebook	open in colab	complementary materials	Quiz / Exercise
Lesson 1: Deep Learning Primer (Introduction to Generative AI )
Lesson 2: Getting Started with Gemini API (Gemini 101 )
Lesson 3: Using Gemini API with Python
Lesson 4: A Gentle Introduction to LLMs and LangChains
Lesson 5A: Getting started with Gemini and LangChains
Lesson 5B: Chat with your document using Gemini and LangChains
Lesson 6: Data Analysis with Gemini and PandasAI
Lesson 7 - Intro to Embeddings with Gemini APIs and LangChains
Lesson 8 - Project: WTM Chat
Lesson 9 - Building Chatbots with Gemini APIs and LangChains
Lesson 10 - Gemini Function Calling
Lesson 11: Gemini Prompt Engineering for Developers
Lesson 12 - Get started with Gemini on Web
Lesson 13 - Get started with Gemini on Android
Lesson 14 - Get started with Gemini on Flutter
Lesson 15 - Get started with Gemini on Angular

Week 1

Primer

Lesson 1 - Deep Learning Primer (Introduction to Generative AI )

Introduction to Generative AI concepts (for beginners).

Week 2

Foundations & Setup

Lesson 2 - Getting Started with Gemini API (Gemini 101 )

Google AI Studio 101: Set up your development environment and API access to use Gemini. Create freeform prompts with Gemini Pro Vision in Google AI Studio Text Generation: Create text from text inputs using Gemini Pro API and Python. Response Control: Fine-tuning the Response - Control how the model generates responses using Gemini API generation parameters: temperature, top_k, top_p, stop sequences and more Trying Gemini Pro Vision - Talking with an Image

Lesson 3 - Using Gemini API with Python

Generate text responses from multimodal inputs (text and images). Use Gemini for multi-turn conversations (chat). Chat Conversations

Lesson 4 - A Gentle Introduction to LLMs and LangChains Lesson 5 - Getting started with Gemini and LangChains Bonus - Get started with Gemini on Android / Web

Week 3

Gemini and LangChains

Lesson 6 - Chat with your document using Gemini and LangChains Lesson 7 - Intro to Embeddings with Gemini APIs and LangChains Use embeddings for large language models. - Create Vector Embeddings: Develop solutions using vector embeddings to capture semantic relationships in data. Bonus - Get started with Gemini on Flutter / Angular