Google Career Certificates CoursesLearn about top google career certificates courses on AI and big data for your career goals.

Big data analytics is the use of processes and technologies, including AI and machine learning, to combine and analyze massive datasets with the goal of identifying patterns and developing actionable insights. This helps you make faster, better, data-driven decisions that can increase efficiency, revenue, and profits.

So, google career certificates were designed and built by subject-matter experts and senior practitioners at google from each of the job fields. google career certificates flexible online training programs designed to earn job-ready skills in high-growth, high-demand career fields such as IT support, project management, data analytics, and UX design courses. No relevant experience or degree is required.

Here is the list of google career certified courses on AI and big data:

Google cloud big data and machine learning fundamentals:

This course introduces participants to the big data capabilities of google cloud and machine learning products like BigQuery, Cloud SQL, Dataproc, and more. Through a combination of presentations, demos, and hands-on labs, participants get an overview of google cloud and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud. Here can learn the best process data and create ML models.

Perform foundational data, ML, and AI tasks in google cloud:

This course started with big data, machine learning, and artificial intelligence. Here can learn the basic features for the following machine learning and AI technologies like BigQuery, Cloud Speech AI, Cloud Natural Language API, AI Platform, Dataflow, Cloud Dataprep by Trifacta, Dataproc, and Video Intelligence API. Here you can get the opportunity to earn a google cloud skill badge upon completion. A skill badge is an exclusive digital badge issued by google cloud in recognition of your proficiency with google cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment.

Machine learning on google cloud:

This course explains end-to-end machine learning on the google cloud series, starting from What is machine learning, building a machine learning-focused strategy and progressing into model training, and what kinds of problems can it solve? optimization, and product analysis. In the end with a recognition of the biases that machine learning can amplify and how to recognize those biases.

Advanced ML with TensorFlow on google cloud platform:

This course teaches how to implement the various flavors of production ML system static, dynamic, and continuous training; static and dynamic inference, and batch and online processing. This is the first course of the advanced ML on google cloud series. This advanced course learns how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text, and ends with building recommendation systems.

ML Operations fundamentals:

This course teaches MLOps tools and best practices for deploying, evaluating, monitoring, and operating production ML systems on google cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. ML engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with data scientists, who develop models, to enable velocity and rigor in deploying the best performing models.

ML Pipelines on google cloud:

This course teaches ML engineers and trainers who work with the state-of-the-art development of ML pipelines here at google cloud. The first few modules will cover TensorFlow extended, which is goggle’s production ML platform based on TensorFlow for management of ML pipelines and metadata. learn about pipeline components and pipeline orchestration with TFX.

You will also learn how to implement ML pipelines with continuous training and CI/CD practices to increase your ML workflow development and deployment velocity, automation, and ability to scale with your data on google cloud. How you can automate your pipeline through continuous integration and continuous deployment, and how to manage ML metadata.

Explore ML Models with explainable AI:

Learn how to build and deploy a model to an AI platform for serving and prediction with explainable AI. Can get practice tools like image recognition models, identifying bias in mortgage data, and using the what-If tool. A skill badge is an exclusive digital badge issued by google cloud in recognition of your proficiency with google cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment.

Build and deploy ML solutions on vertex AI

Here learn how to use google cloud’s unified vertex AI platform and its auto ML and custom training services to train, evaluate, tune, explain, and deploy ML solutions as well as how to leverage auto ML, custom training, and new MLOps services to significantly enhance developer productivity and accelerate time to value. Learners who complete this skill badge will gain hands-on experience with Vertex AI for new and existing ML workloads and be able to leverage auto ML, custom training, and new MLOps services to significantly enhance developer productivity and accelerate time to value.