Learn Google AI Studio in 50 minutes

Create your first prompt in Google AI Studio, explore prompt creation and running a protein-focused recipe query, and learn to save, edit, and rerun prompts.

Learn to set optional system instructions in Google AI Studio to control the model’s tone, save prompts, and run explain me like a ten year old for topics.

Learn to select LM models in Google AI Studio before prompting, and view details like context length, use case, features, rate limit, and latency, including Gemini 2.0 and Gemini gamma.

Compare llm models in google ai studio by running prompts, reviewing output, and evaluating speed and token counts to refine prompts and save comparisons.

Explore the model parameters in Google AI Studio, including token count, and learn that tokens can be words, subwords, or characters, with a 1 million limit.

Explore how temperature acts as a model parameter that controls randomness in language models, influencing next-token choices from predictable to creative outputs.

Discover how Google AI Studio uses structured output to format model responses as JSON for easy parsing, using prompts about Virat Kohli and options to run, download, and edit.

Use code execution in Google AI Studio to generate and run code from a prompt. Download the code and output for tasks like calculating the 30th prime number.

Enable grounding with Google AI Studio to fetch real-time results for prompts in Google AI Studio, compare outcomes with and without search, and view sources and suggestions.

Explore Google AI Studio’s safety settings, learn to edit advanced options, adjust harmful response levels, and block hate speech, harassment, dangerous content, and civic integrity issues to tailor content safety.

Learn to use stop sequence settings in Google AI Studio to control when the model stops generating text, using a specific token or word as the stop signal.

Adjust the output length in Google AI Studio by setting the maximum number of tokens, experimenting with 8192 and 200 tokens, and running prompts to control response length.

Read and scan images with Google AI Studio by uploading files or selecting from Google Drive, and observe how the tool reads text from images.

Upload videos to Google AI Studio and scan them to see how the platform analyzes content, extracting descriptions and topics from an Android Studio tutorial.

Learn to work with Google AI Studio's sample media by creating prompts, adding media, and generating image descriptions and similar image suggestions.

Record audio and give voice instructions for a prompt in Google AI Studio, then run it to see places to visit in Delhi, India.

Get code from google ai studio by using run settings, generate a template api code in Python, JavaScript, or Go, and create an api key for the Gemini 2.0 model.

Open your project code directly in Google Colab to run programs and combine executable code with rich text, using the Get code feature and API key creation.

Tune a model in Google AI Studio by selecting a data source, preparing input-output pairs, and configuring epochs, batch size, and learning rate multiplier to improve task performance.

Explore the prompt gallery in Google Studio to access ready-made prompts, run ideas like math tutor, sentiment, and comparing numbers, and learn how to test and run prompts.

Interact with the Gemini AI in real time via Google AI Studio’s stream feature, receiving immediate feedback, while optionally sharing your webcam or screen and choosing audio or text output.

Learn to display the webcam in Google AI Studio and use it to identify objects.

Utilize stream real time to share your screen with Google AI Studio, letting Gemini identify the operating system, read text, and demonstrate the full screen experience.