Machine Learning on Google Cloud (Vertex AI) - Hands on!

🌩️ Master Machine Learning on Google Cloud with Vertex AI - Your Next Step in AI Mastery!

Course Instructor: Hemanth Kumar K

Course Headline:

Unlock the Power of Google Cloud for ML/DL Model Building and Deployment! 🚀

Are you a data scientist or AI practitioner looking to expand your horizons beyond Azure or AWS? Perhaps you're new to the world of cloud-based machine learning, seeking to leverage Google Cloud Platform (GCP) for your next project? If so, this course is tailor-made for you!

Course Description:

Dive into the Cloud with Confidence!

This comprehensive course is crafted for both beginners and seasoned AI practitioners who wish to explore Google Cloud Platform's capabilities in machine learning (ML) and deep learning (DL). Whether you're a data scientist, ML engineer, or simply curious about the power of GCP components like AutoML, AI Platform, and Vertex AI, this course will equip you with hands-on experience and practical knowledge.

What You'll Learn:

1. Introduction to Google Cloud Platform: 🌟

   • Overview of GCP and its significance in the ML ecosystem.
   • Steps to create a GCP account and navigate the platform.

2. Foundational GCP Services: 🛠️

   • An exploration of GCP's core services: Compute, Storage, Database, IAM, Analytics.
   • Live demonstration of a key GCP service to solidify your understanding.

3. Deep Dive into AI Services on GCP: 🧠

   • AutoML:
     • Creating models for tabular, image, and text data.
     • Utilizing API predictions in real-world scenarios.
   • AI Platform:
     • Model creation and deployment through both GUI and code.
     • Submitting jobs, evaluating model performance, and setting up Kubeflow pipelines.
   • Vertex AI:
     • AutoML for custom models with hyperparameter optimization.
     • Custom model training and deployment processes.
     • Kubeflow pipeline creation with AutoML & custom models, including feature store integration.

Course Breakdown:

1. Understanding the GCP Ecosystem: 🌱

   • A primer on Google Cloud's architecture.
   • Setting up your development environment for GCP.

2. Mastering AutoML with GCP: 🤖

   • Discover how to build, train, and deploy ML models at scale.
   • Best practices for using APIs to generate predictions.

3. Leveraging AI Platform on GCP: 🔧

   • A hands-on approach to creating and managing ML projects.
   • Insights into Kubeflow pipelines and their role in ML workflows.

4. Exploring Vertex AI's Capabilities: 🎨

   • Advanced techniques for custom model training.
   • Explore the power of hyperparameter optimization and the feature store.

By the End of This Course, You Will:

• Have a solid understanding of GCP's architecture and its role in machine learning.
• Be proficient in using AutoML for various types of data.
• Know how to deploy and manage ML models on AI Platform using both GUI and code.
• Understand the intricacies of setting up Kubeflow pipelines within Vertex AI.
• Gain practical experience in feature store integration within your ML projects.

Join us on this journey to harness the capabilities of Google Cloud for your machine learning endeavors! 📈📅

Enroll now and transform your data into intelligent solutions with confidence! 🌟