In this program, you get familiar with Google Clouds suite and other offerings to facilitate the data-to-AI journey. The course delves into the intricacies of machine learning models using Vertex AI on Google Cloud, exploring the associated processes, obstacles, and advantages. You can engage in hands-on experience to reinforce theoretical concepts through practical application and explore real-world cases on big data. The course highlights challenges associated with the big data pipelines on Google Cloud to let you understand the tangible benefits while building, training, and fine-tuning models within the Google Cloud environment. By the end of this course, you will not only engage in theoretical understanding but also gain practical experience in navigating the complexities of building data in Google Clouds Vertex AI. You can build a customer machine learning model with BigQuery ML and predict visitor purchases. While identifying tools and products to support machine learning workflow with Vertex AI, you can build an end-to-end ML workflow
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Throughout this hands-on learning experience facilitated by our experts, you will achieve the following course objectives:
• Describe streaming data workflow from ingestion to data visualization
• Identify different options to build machine learning solutions on Google Cloud
• Explore a BigQuery Public Dataset
• Creating a streaming data pipeline for a real-time dashboard
• Define BigQuery processes queries and stores data
• Identify tools and products to support each stage
• Analyze big data at scale
• Recognize data-driven AI lifecycle on Google Cloud
• Process products of big data and machine learning
• Build machine learning pipeline using AutoML
• Describe a machine learning workflow and the key steps with Vertex AI
• Design streamlining pipelines with Dataflow and Pub/Sub
The GCF-BDM course is ideal for the target audience who have experience in IT and work in the position of data analyst or data scientist. In the management field, business analysts and project managers can enroll in the course to get ahead in the competition and get started with Google Cloud. Executives and IT decision-makers must enroll in the course to evaluate Google Cloud for use by data scientists. Moreover, IT aspirants and individuals who are responsible for creating and maintaining machine learning and statistical models at the organization should opt for the course. Those who want to strengthen their learnings, including pipeline design and architectural data processing, querying datasets, visualizing query results, and creating reports, must opt for the course and excel in their career ahead.
• Lab: Exploring a BigQuery Public Dataset
• Identify the different aspects of Google Cloud's infrastructure.
• Identify the big data and machine learning products on Google Cloud.
• Lab: Creating a Streaming Data Pipeline for a Real-Time Dashboard with Dataflow
• Describe an end-to-end streaming data workflow from ingestion to data visualization.
• Build collaborative real-time dashboards with data visualization tools.
• Identify modern data pipeline challenges and how to solve them at scale with Dataflow.
• Lab: Predicting Visitor Purchases Using BigQuery ML
• Describe the essentials of BigQuery as a data warehouse.
• Explain how BigQuery processes queries and stores data.
• Define BigQuery ML project phases.
• Build a custom machine learning model with BigQuery ML
• Describe AI solutions in both horizontal and vertical markets.
• Identify different options to build ML models on Google Cloud.
• Define Vertex AI and its major features and benefits.
• Describe the data-to-AI lifecycle on Google Cloud and identify the major products of big data and machine learning.
What is the course duration?
GCF-BDM, Google Cloud Fundamentals: Big Data and Machine Learning, is a 01-day expert-led course by Vinsys that contributes to smoother Big Data and ML project deployments at organizations.
What is the course code to access the learning material?
The course code through which it can be accessed is GCF-BDM.
Why should I enroll in this course by Vinsys?
Enrolling in this course offers a comprehensive learning experience of Big data and its critical role in Google Cloud deployment supporting AI lifecycles. You will learn to design and implement robust Big data principles and application mechanisms to spin up Vertex AI on Google Cloud. On top of that, you will get 24*7 support for pre-and post-course completion from Vinsys after you enroll in it.
Can a beginner enroll in this course?
This introductory course is suitable for those seeking to deepen their understanding of Big data techniques and secure their applications from potential threats to the systems. This includes those working majorly in the field of programming language data query language such as SQL, including Developers, IT Security Professionals, ML Engineers, and more.
How will the course help me in my professional development?
Designed with experts, the course can unlock the potential of hands-on skills in cloud-based solutions and securing real-world applications and their integration with Big data and ML workflows. The course directly applies to enhancing professional Google Cloud services tailored for Big data and ML tasks and detection capabilities. It covers future trends in Big data and ML deployment, ML Ethics, and Big data Algorithms, ensuring that you are well-prepared for upcoming developments in the field.
How is the course program carried out at Vinsys?
Our courses are delivered through instructor-led training (ILT), private group training, and virtual instructor-led training (vLIT). We boost your odds of success by helping you prepare for required exams and earn the certification. Effective course material accessed throughout the program makes learning about concepts beyond the class easier. You can choose your learning path to upskill with Vinsys' subject matter experts upon customizing training needs to ensure 100% results.
How will this course help the learners?
The course will help learners understand Big data Application Programming and learn to identify various types of deployment strategies using ML optimization models. The knowledge equips them to navigate the complex landscape of ML and Big data-enabled frameworks effectively.
Can learners interact with the instructors?
Yes, learners will have an opportunity to interact with the instructors till the time their confusion and queries are resolved. You can enjoy 24*7 support from Vinsys even after the course completion.
What are the job opportunities after GCF-BDM?
There are various options to choose from, including DevOps Engineers, Big Data Analysts, Google Cloud Developer, ML Engineer, Data Engineer, Cloud Solutions Architect, and more.
What are related courses to GCF-BDM?
Some follow-on courses include-
Data Warehousing with BigQuert: Storage Design, Query Optimization, and Administration (DWBQ-SDQA).
As a developer, this course has been a valuable lesson for me in the intricacies of Google Cloud's big data and machine learning offerings. The hands-on experience emphasizes the building of big data pipelines that have enhanced my opportunities in the field as a Big Data Engineer. All thanks to Vinsys, I was able to master Google Cloud's capabilities in big data and ML.
My team enrolled in the course and surpassed expectations upon its completion. They are able to implement Vertex AI learning into its implementation, meeting the needs of collaborative model development. The hands-on course is engaging, allowing my team to share their experiences and troubleshoot challenges together. Grateful to Vinsys!