Building AI Apps with the Gemini API

3h 43m 41s
English
Paid

Course description

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.

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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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#1: Introduction

All Course Lessons (39)

#Lesson TitleDurationAccess
1
Introduction Demo
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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