Learn AI model training using Vertex AI, Data Storage Solutions , Big Data Processing with BigQuery, ETL, ML using GCP
Sub Category
- No-Code Development
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Objectives
- You will learn about the Introduction to Google Cloud Platform (GCP), including the core benefits of cloud computing with GCP, its major services, and key use.
- You will also explore how GCP supports modern data science, machine learning, and business analytics workflows
- You will explore Data Storage Solutions in GCP, including the different storage types such as Cloud Storage, Cloud SQL, Firestore, and Bigtable
- You will learn how to choose the right storage service based on workload and data type, implement best practices
- You will get introduced to Big Data Processing with BigQuery, Google’s powerful serverless analytics platform
- You will understand the big data workflow in BigQuery, optimize query performance, and handle structured and semi-structured data.
- You will learn how to build Data Integration and ETL Pipelines on GCP. You will study the components of ETL workflows
- Explore data ingestion strategies using tools like Cloud Dataflow and Cloud Pub/Sub, and implement real-time and batch processing
- You will explore Data Visualization and Business Intelligence (BI) in GCP using tools such as Looker and Data Studio.
- You will learn about different types of visualizations, the BI process, and how to design interactive dashboards
- You will gain practical knowledge on Machine Learning with GCP, including how to prepare data, train models using Vertex AI
- You will explore pre-trained models and AutoML for faster experimentation. Hands-on tasks include training and evaluating a machine learning model
- You will understand MLOps and Workflow Automation on GCP, focusing on continuous integration and deployment (CI/CD)
- You will study tools like TFX, Cloud Build, and Vertex Pipelines, and examine case studies that demonstrate successful MLOps implementations
- You will study Security and Governance in GCP, including IAM (Identity and Access Management), data encryption, network security
- You will learn how to protect sensitive data and follow best practices for governance in analytics and ML projects. Hands-on tasks include setting up IAM roles,
Pre Requisites
- You should have an interest in data science, machine learning, and cloud technologies
- A desire to learn how to store, manage, analyze, and visualize data
- Interest in applying machine learning models to real-world scenarios
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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