Applying Machine Learning to your Data with GCP
This module explores the use of Machine Learning on Google Cloud Platform (GCP) to help businesses gain insights from their data. It covers the fundamentals of Machine Learning and how to apply it to data stored on GCP. ▼
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Course Feature
Cost:
Free
Provider:
Coursera
Certificate:
No Information
Language:
English
Start Date:
Self Paced
Course Overview
❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [March 06th, 2023]
This course provides an overview of applying Machine Learning to data using Google Cloud Platform (GCP). Participants will learn how to use BigQuery to store and query data, as well as how to use Machine Learning to create predictive models. Additionally, participants will gain an understanding of cloud computing and how to use GCP to deploy their models. By the end of the course, participants will have the skills to apply Machine Learning to their own data and deploy models on GCP.
[Applications]
After completing this course, learners can apply the knowledge they have gained to their own data sets. They can use BigQuery to store and query large datasets, use Machine Learning to build models and use Google Cloud Platform to deploy and manage cloud computing applications. Additionally, learners can use the Cloud Computing tools to create and manage virtual machines, storage, and networking resources.
[Career Paths]
1. Data Scientist: Data Scientists use Machine Learning algorithms to analyze large datasets and uncover patterns and insights. They use GCP tools such as BigQuery and Cloud Computing to store and process data. With the increasing demand for data-driven decision making, Data Scientists are in high demand and the field is expected to continue to grow.
2. Machine Learning Engineer: Machine Learning Engineers use GCP tools such as BigQuery and Cloud Computing to develop and deploy Machine Learning models. They are responsible for building and maintaining the infrastructure needed to run Machine Learning algorithms. With the increasing demand for Machine Learning applications, Machine Learning Engineers are in high demand and the field is expected to continue to grow.
3. Cloud Computing Engineer: Cloud Computing Engineers use GCP tools such as BigQuery and Cloud Computing to develop and deploy applications on the cloud. They are responsible for building and maintaining the infrastructure needed to run applications on the cloud. With the increasing demand for cloud-based applications, Cloud Computing Engineers are in high demand and the field is expected to continue to grow.
4. Data Analyst: Data Analysts use GCP tools such as BigQuery and Cloud Computing to analyze large datasets and uncover patterns and insights. They are responsible for understanding the data and providing insights to help inform business decisions. With the increasing demand for data-driven decision making, Data Analysts are in high demand and the field is expected to continue to grow.
[Education Paths]
1. Bachelor of Science in Computer Science: This degree path provides students with a comprehensive understanding of computer science fundamentals, including programming, algorithms, data structures, and software engineering. Additionally, students will learn about the latest technologies and trends in cloud computing, machine learning, and big data. With the increasing demand for data-driven solutions, this degree path is becoming increasingly popular and provides students with the skills necessary to develop and deploy machine learning models on the Google Cloud Platform.
2. Master of Science in Artificial Intelligence: This degree path focuses on the development of artificial intelligence systems and their applications. Students will learn about the fundamentals of machine learning, deep learning, and natural language processing, as well as the latest trends in cloud computing and big data. With the increasing demand for AI-driven solutions, this degree path is becoming increasingly popular and provides students with the skills necessary to develop and deploy machine learning models on the Google Cloud Platform.
3. Master of Science in Data Science: This degree path focuses on the development of data-driven solutions. Students will learn about the fundamentals of data analysis, data mining, and machine learning, as well as the latest trends in cloud computing and big data. With the increasing demand for data-driven solutions, this degree path is becoming increasingly popular and provides students with the skills necessary to develop and deploy machine learning models on the Google Cloud Platform.
4. Master of Science in Cloud Computing: This degree path focuses on the development of cloud-based solutions. Students will learn about the fundamentals of cloud computing, distributed systems, and big data, as well as the latest trends in machine learning and artificial intelligence. With the increasing demand for cloud-based solutions, this degree path is becoming increasingly popular and provides students with the skills necessary to develop and deploy machine learning models on the Google Cloud Platform.
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