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.
Building AI Apps with the Gemini API
3h 43m 41s
English
Paid
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.
About the Author: Zero To Mastery
Zero To Mastery (ZTM) is a Toronto-based online coding academy founded by Andrei Neagoie, originally a senior developer at large Canadian tech firms before turning to teaching full-time. The academy's signature is the cohort-based bootcamp track combined with a deep self-paced course library, all aimed at career-changers and self-taught developers preparing to land software-engineering roles at top companies.
The instructor roster has grown well beyond Andrei to include other senior practitioners: Daniel Bourke (machine learning), Aleksa Tešić (DevOps), Jacinto Wong, and others. Courses cover the full software-engineering career path: web development with React and Next.js, Python, machine learning and deep learning, DevOps and cloud, system design, mobile, and the algorithm / data-structure interview prep that gates engineering jobs.
The CourseFlix listing under this source carries over 120 ZTM courses spanning that full range. Material is paid; ZTM itself runs on a monthly / annual membership model. The teaching style favours long-form, project-based courses where students build complete portfolio-quality applications rather than disconnected feature tutorials.
Watch Online 39 lessons
0:00
/ #1: Introduction
All Course Lessons (39)
| # | Lesson Title | Duration | Access |
|---|---|---|---|
| 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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39 lessons · 3h 43m 41sShow all 39 lessons
- 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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Frequently asked questions
What is Building AI Apps with the Gemini API about?
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.
Who teaches Building AI Apps with the Gemini API?
Building AI Apps with the Gemini API is taught by Zero To Mastery. You can find more courses by this instructor on the corresponding source page.
How long is Building AI Apps with the Gemini API?
Building AI Apps with the Gemini API contains 39 lessons with a total runtime of 3 hours 43 minutes. All lessons are available to watch online at your own pace.
Is Building AI Apps with the Gemini API free to watch?
Building AI Apps with the Gemini API is part of CourseFlix's premium catalog. A CourseFlix subscription unlocks the full video player; the course description, table of contents, and preview information are available to everyone.
Where can I watch Building AI Apps with the Gemini API online?
Building AI Apps with the Gemini API is available to watch online on CourseFlix at https://courseflix.net/course/building-ai-apps-with-the-gemini-api. The page hosts every lesson with the integrated video player; no download is required.