Technologies / Artificial Intelligence

Generative artificial intelligence with Google Cloud: from basics to advanced applications (with Vertex AI and Gemini)

Szkolenie wprowadza uczestników w świat generatywnej sztucznej inteligencji z wykorzystaniem najnowocześniejszych narzędzi Google Cloud Platform. Program łączy teoretyczne podstawy GenAI z praktycznym wykorzystaniem Vertex AI Generative AI Studio oraz modeli Gemini do tworzenia innowacyjnych aplikacji. Zajęcia prowadzone są w formie warsztatów, podczas których uczestnicy budują rzeczywiste rozwiązania oparte na technologiach generatywnych. Szkolenie przygotowuje do wykorzystania GenAI w projektach biznesowych z uwzględnieniem zasad odpowiedzialnej AI.

Issues

Generative artificial intelligence and its applications
Large language models (LLM) and transformers architecture
Vertex AI Generative AI Studio and Model Garden
Gemini model family and its capabilities
Prompt engineering and prompt optimization techniques
Fine-tuning and tuning of generative models
Diffusion models and image generation
Multimodal applications combining text, image and other modalities
Firebase Genkit and GenAI application development
Responsible AI and ethical aspects of GenAI
Security and privacy in generative systems
GenAI integration with Google Workspace and NotebookLM

Benefits

Understanding the principles and architecture of generative AI models including LLMs and diffusion models
Working with Vertex AI Generative AI Studio and Gemini model family in practice
Mastering advanced prompt engineering techniques including few-shot, chain-of-thought, and zero-shot prompting
Building applications that integrate text, image, and multimodal generative models
Implementing GenAI solutions in business projects following responsible AI principles
Applying ethical guidelines and bias mitigation strategies in generative AI systems
Evaluating and optimizing the performance of fine-tuned generative models
Deploying production-ready GenAI applications using Firebase Genkit and GCP services

Who is this training for?

Software developers interested in integrating AI into applications

AI/ML engineers developing competencies in the area of generative artificial intelligence

Data analysts (data scientists) learning the capabilities of generative models

Cloud solution architects designing systems using GenAI

Product managers responsible for innovative AI solutions

IT consultants specializing in the implementation of AI technologies

Entrepreneurs and innovators looking for new business opportunities

Candidates preparing for Generative AI Leader certification

Prerequisites

Basic knowledge of Python programming
Understand the basic concepts of machine learning and AI
Experience working with APIs and development libraries
Knowledge of the basics of natural language processing (NLP)
Motivation to learn about the latest artificial intelligence technologies

Training program

Definition of generative AI and differences from traditional machine learning
Overview of GenAI model types: large language models, image generation, multimodal
Google's GenAI portfolio: Vertex AI, Gemini, PaLM API, Imagen
GenAI beyond chatbot: exploring the strategic capabilities of Google Cloud
Overview of business applications and use cases

Architecture and principles of large language models
Practical work with text models in Vertex AI Generative AI Studio
Gemini model family: capabilities, specifications, API access
The basics of prompting: creating effective and contextual prompts
Advanced techniques: few-shot, chain-of-thought, zero-shot prompting

When and why to tune large language models
Tuning methods in Vertex AI: Parameter-Efficient Fine-Tuning (PEFT)
Preparation and structuring of data for the fine-tuning process
Metrics for evaluating the quality and performance of generative models

Generation of images and multimedia content
Introduction to diffusion models and image generation mechanisms
Working with image generating models (Imagen) in Vertex AI
Techniques for creating and editing images using text prompts
Generate other types of content: source code, documents, presentations
Integration of different modalities in one solution

Integration of GenAI models with applications (Python libraries, REST APIs)
Building intelligent chatbots and conversational agents
Q&A systems based on documents and knowledge bases
Automatic generation of reports, descriptions and marketing content
Firebase Genkit to simplify GenAI application development
Using Gemini in Google Workspace and NotebookLM

Google's principles for responsible development of artificial intelligence
Identification and mitigation of biases (biases) in GenAI models
Issues of justice (fairness) and ethics in AI systems
Data security and privacy in generative applications
Monitor, manage and update implemented models
Quality improvement techniques and dealing with model limitations

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Frequently asked questions

What are the prerequisites for this training?

For Generative artificial intelligence with Google Cloud: from basics to advanced applications (with Vertex AI and Gemini) we recommend: Basic knowledge of Python programming; Understand the basic concepts of machine learning and AI; Experience working with APIs and development libraries.

What is the format and duration of this training?

The training lasts 3 days and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.

Who is this training designed for?

This training is designed for: Software developers interested in integrating AI into applications; AI/ML engineers developing competencies in the area of generative artificial intelligence; Data analysts (data scientists) learning the capabilities of generative models.