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MASTER GEN AI ON GOOGLE CLOUD : COMPREHENSIVE IN-DEPTH TRAINING
“GenAI On Google Cloud With Vertex AI And Generative AI Studio” Offers An Immersive Exploration Into The Realm Of GenAI On Google Cloud. The Course Marries Theoretical Knowledge With Practical Application, Ensuring That Participants Not Only Understand The Concepts But Also Know How To Leverage Them In Real-World Scenarios. Through Lectures, Discussions, And Hands-On Labs, Attendees Will Walk Away With A Robust Understanding Of Google Cloud’s AI Solutions And How To Harness Them For GenAI Projects.
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Anil Bidari
YOUR EXPERIENCED MENTOR
Anil Bidari is a versatile trainer and consultant specializing in GitLab, AWS, Azure, Google, DevOps, Jenkins, Kubernetes, Ansible, Docker, Agile, and Machine Learning. His expertise drives successful technology adoption and implementation, benefiting organizations and individuals alike.
- Instructor: Anil Bidari
- Participants: 1,550 Students
- Study Lecture : 9 Lectures
- Time Duration : 1 Day
- Certificate : Yes
- Training Delivery Mode : Online - Live Instructor Led training
COURSE OBJECTIVE
- Understand The Distinctions Between Narrow AI And GenAI And The Significance Of The Latter.
- Be Familiar With Google Cloud’s AI Offerings, Notably Vertex AI And Generative AI Studio.
- Gain Hands-On Experience In Setting Up, Experimenting With, And Deploying AI Projects On These Platforms.
- Extensive understanding of Generative AI principles and integration with Google Cloud services.
- Hands-on experience with Google Cloud AI tools for model deployment, management, and scalability.
- Certification for proficiency in Generative AI on Google Cloud, empowering comprehensive skills for AI innovation.
COURSE DESCRIPTION
This One-Day Training Course Dives Deep Into General AI (GenAI) On Google Cloud, Focusing On The Potent Capabilities Of Vertex AI And Generative AI Studio. Participants Will Explore The Conceptual Underpinnings Of GenAI, Its Differentiation From Narrow AI, And Experience Hands-On Labs That Highlight Google Cloud’s State-Of-The-Art AI Tools.
COURSE SUMMARY
“Master GenAI on Google Cloud: Comprehensive In-Depth Training” offers extensive education on integrating Generative AI with Google Cloud services. Participants gain hands-on experience in model deployment, optimization, and ethical considerations. Collaboration with Google Cloud experts ensures proficient and responsible AI deployment, empowering mastery in Generative AI on Google Cloud.
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Course Outline
Registration And Welcome Breakfast
Introduction To General AI (GenAI)
– What Is GenAI?
– Differences Between Narrow AI And General AI.
– The Evolution And Significance Of GenAI.
Overview Of Google Cloud’s AI Services
– Introduction To Google Cloud Platform (GCP).
– Brief On Vertex AI And Generative AI Studio.
Hands-On Lab 1: Setting Up GCP For GenAI Workloads
– Initiating A GCP Account & Project.
– Configuring IAM & Permissions.
– Introduction To Vertex AI Workspace.
Morning Break
Dive Into Vertex AI
– What Is Vertex AI?
– Components: Vertex Pipelines, Vertex Prediction, Etc.
– Use Cases And Applications.
Hands-On Lab 2: Building An End-To-End ML Workflow With Vertex AI
– Data Preparation And Preprocessing.
– Model Training And Deployment.
– Predictions With The Trained Model.
Lunch Break
Introduction To Generative AI Studio
– What Is Generative AI Studio?
– Overview Of Generative Models And Their Applications.
– Link Between Generative AI And GenAI Concepts.
Hands-On Lab 3: Experiencing Generative AI Studio
– Setting Up Generative AI Studio.
– Experimenting With Pre-Trained Generative Models.
– Fine-Tuning And Deploying Generative Models.
Afternoon Break
Advanced Features & Integrations
– Integrating Vertex AI And Generative AI Studio.
– Best Practices For Creating, Training, And Deploying Models.
– Exploring APIs And SDKs Related To These Platforms.
Hands-On Lab 4: Advanced Projects On Vertex AI And Generative AI Studio
– Implementing A Complex GenAI Project Leveraging Both Tools.
– Monitoring, Tuning, And Optimizing The Project.
– Evaluating And Interpreting Results.
Q&A, Feedback, And Closing Remarks