Building AI Apps with the Gemini API

3h 43m 41s
English
Paid

Learn to use Google's Gemini API for building AI-powered applications. Plus you'll put your skills into action by building three projects using the Gemini API.

Read more about the course

Take your first step into the world of AI application development by diving deep into a fundamental technology: Google's Gemini API. You'll learn everything there is about utilizing the API to power your AI applications with Google's leading Large Language Models.

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# Title Duration
1 Introduction 03:26
2 What We're Using 00:36
3 Jupyter Notebook 14:11
4 Google Colab 08:08
5 Getting a Gemini API Key 04:21
6 Installing the Python SDK for Gemini API and Authenticating to Gemini 09:52
7 Gemini Multimodal Models: Nano, Pro, and Ultra 05:15
8 Google AI Studio: Freeform Prompts With Gemini Pro Vision 06:12
9 Google AI Studio: Using Variables and Parameters in the Prompt 03:05
10 Generating Text From Text Inputs: Gemini Pro 04:23
11 Streaming Model Responses 03:36
12 Generating Text From Image and Text Inputs: Gemini Pro Vision 05:13
13 Gemini API Generation Parameters: Controlling How the Model Generates Responses 06:12
14 Gemini API Generation Parameters Explained 10:14
15 Building Chat Conversations 07:54
16 Project: Building a Conversational Agent Using Gemini Pro 07:19
17 Introduction to Gemini 1.5 Pro 04:11
18 System Instructions 05:43
19 The File API Prompting with Media Files 06:09
20 Tokens 06:42
21 Prompting with Audio 04:21
22 Project Requirements 05:54
23 Building the Application 05:23
24 Testing the Application 01:49
25 Streamlit: Transform Your Jupyter Notebooks into Interactive Web Apps 02:49
26 Creating the Web App Layout With Streamlit 11:20
27 Saving and Displaying the History Using the Streamlit Session State 05:20
28 Project Introduction 00:57
29 Getting Images Using a Generator 06:18
30 Renaming Images Using Gemini Pro Vision 09:35
31 Intro to Prompt Engineering the Gemini API 03:13
32 Tactic #1 - Position Instructions Clearly With Delimiters 05:02
33 Tactic #2 - Provide Detailed Instructions for the Context, Outcome, or Length 06:11
34 Tactic #3 - Specify the Response Format 06:14
35 Tactic #4 - Few-Shot Prompting 06:56
36 Tactic #5 - Specify the Steps Required to Complete a Task 06:29
37 Tactic #6 - Give Models Time to "Think" 04:34
38 Other Tactics for Better Prompting and Avoiding Hallucinations 06:21
39 Prompt Engineering Summary 02:13

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