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How Google does Machine Learning
Our Courses
Machine Learning: Theory and Hands-on Practice with Python
In the Machine Learning specialization, we will cover Supervised Learning, Unsupervised Learning, and the basics of Deep Learning. You will apply ML algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Starting with supervised learning, we will cover linear and logistic regression, KNN, Decision trees, ensembling methods such as Random Forest and Boosting, and kernel methods such as SVM. Then we turn our attention to unsupervised methods, including dimensionality reduction techniques (e.g., PCA), clustering, and recommender systems.
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English
MLOps | Machine Learning Operations
This comprehensive course series is perfect for individuals with programming knowledge such as software developers, data scientists, and researchers. You'll acquire critical MLOps skills, including the use of Python and Rust, utilizing GitHub Copilot to enhance productivity, and leveraging platforms like Amazon SageMaker, Azure ML, and MLflow.
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English
NoSQL, Big Data, and Spark Foundations
Big Data Engineers and professionals with NoSQL skills are highly sought after in the data management industry. This Specialization is designed for those seeking to develop fundamental skills for working with Big Data, Apache Spark, and NoSQL databases.
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DeepLearning.AI TensorFlow Developer
TensorFlow is one of the most in-demand and popular open-source deep learning frameworks available today. The DeepLearning.AI TensorFlow Developer Professional Certificate program teaches you applied machine learning skills with TensorFlow so you can build and train powerful models. In this hands-on, four-course Professional Certificate program, you’ll learn the necessary tools to build scalable AI-powered applications with TensorFlow. After finishing this program, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects.
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English
Sports Performance Analytics
Sports analytics has emerged as a field of research with increasing popularity propelled, in part, by the real-world success illustrated by the best-selling book and motion picture, Moneyball.
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English
TensorFlow: Advanced Techniques
About TensorFlow TensorFlow is an end-to-end open-source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML, and developers easily build and deploy ML-powered applications. TensorFlow is commonly used for machine learning applications such as voice recognition and detection, Google Translate, image recognition, and natural language processing. About this Specialization Expand your knowledge of the Functional API and build exotic non-sequential model types.
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IBM Data Science
Prepare for a career in the high-growth field of data science. In this program, you’ll develop the skills, tools, and portfolio to have a competitive edge in the job market as an entry-level data scientist in as little as 4 months. No prior knowledge of computer science or programming languages is required. Data science involves gathering, cleaning, organizing, and analyzing data with the goal of extracting helpful insights and predicting expected outcomes.
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Machine Learning on Google Cloud
What is machine learning, and what kinds of problems can it solve? How can you build, train, and deploy machine learning models at scale without writing a single line of code?
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Deep Learning for Healthcare
This specialization is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios.
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Exam Prep MLS-C01: AWS Certified Specialty Machine Learning
Gain Skills to understand the fundamentals of Machine Learning. Learn working with various AWS Services necessary for Machine Learning. Hands on Experience working with AWS Management Console. Prepare for AWS Certified Machine Learning Specialty Certification
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Data Science: Statistics and Machine Learning
Build models, make inferences, and deliver interactive data products. This specialization continues and develops on the material from the Data Science: Foundations using R specialization. It covers statistical inference, regression models, machine learning, and the development of data products. In the Capstone Project, you’ll apply the skills learned by building a data product using real-world data.
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Google Advanced Data Analytics
Get professional training designed by Google and take the next step in your career with advanced data analytics skills. There are over 144,000 open jobs in advanced data analytics and the median salary for entry-level roles is $118,000.¹ Advanced data professionals are responsible for collecting, analyzing, and interpreting extremely large amounts of data.
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Ethics in the Age of AI
As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations. In this specialization, we will explore the rise of algorithms, fundamental issues of fairness and bias in machine learning, and basic concepts involved in security and privacy of machine learning projects. We'll finish with a study of 3 projects that will allow you to put your new skills into action.
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English
Visual Machine Learning with Yellowbrick
Welcome to this project-based course on Visual Machine Learning with Yellowbrick.
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3 hours
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English
Machine/Deep Learning for Mining Quality Prediction-Enhanced
In this hands-on project, we will train machine learning and deep learning models to predict the % of Silica Concentrate in the Iron ore concentrate per minute. This project could be practically used in Mining Industry to get the % Silica Concentrate at much faster rate compared to the traditional methods.
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Self Paced
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3 hours
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English
Evaluate Machine Learning Models with Yellowbrick
Welcome to this project-based course on Evaluating Machine Learning Models with Yellowbrick.
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3 hours
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English
Attention Mechanism - Português Brasileiro
Este curso é uma introdução ao mecanismo de atenção, uma técnica avançada que permite que as redes neurais se concentrem em partes específicas de uma sequência de entrada. Você vai entender como a atenção funciona e como ela pode ser usada para melhorar o desempenho de várias tarefas de machine learning (como tradução automática, resumo de texto e resposta a perguntas).
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Advanced Machine Learning on Google Cloud
This 5-course specialization focuses on advanced machine learning topics using Google Cloud Platform where you will get hands-on experience optimizing, deploying, and scaling production ML models of various types in hands-on labs. This specialization picks up where “Machine Learning on GCP” left off and teaches you how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text. It ends with a course on building recommendation systems.
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How to Use Microsoft Azure ML Studio for Kaggle Competitions
In this 90 minutes long project-based course, you will learn how to create a Microsoft Azure ML Studio account, a Kaggle account for competitions and use both of them to build a machine learning model which we will be using to make predictions.
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Self Paced
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3 hours
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English
Advanced AI Techniques for the Supply Chain
In this course, we’ll learn about more advanced machine learning methods that are used to tackle problems in the supply chain. We’ll start with an overview of the different ML paradigms (regression/classification) and where the latest models fit into these breakdowns. Then, we’ll dive deeper into some of the specific techniques and use cases such as using neural networks to predict product demand and random forests to classify products. An important part to using these models is understanding their assumptions and required preprocessing steps.
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22 hours
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English
Machine Learning with Python
Get ready to dive into the world of Machine Learning (ML) by using Python! This course is for you whether you want to advance your Data Science career or get started in Machine Learning and Deep Learning. This course will begin with a gentle introduction to Machine Learning and what it is, with topics like supervised vs unsupervised learning, linear & non-linear regression, simple regression and more. You will then dive into classification techniques using different classification algorithms, namely K-Nearest Neighbors (KNN), decision trees, and Logistic Regression.
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Self Paced
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33 hours
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English
DevOps, DataOps, MLOps
Learn how to apply Machine Learning Operations (MLOps) to solve real-world problems. The course covers end-to-end solutions with Artificial Intelligence (AI) pair programming using technologies like GitHub Copilot to build solutions for machine learning (ML) and AI applications.
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29 hours
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English
AI for Scientific Research
In the AI for Scientific Research specialization, we'll learn how to use AI in scientific situations to discover trends and patterns within datasets. Course 1 teaches a little bit about the Python language as it relates to data science. We'll share some existing libraries to help analyze your datasets. By the end of the course, you'll apply a classification model to predict the presence or absence of heart disease from a patient's health data.
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Wrangling Data in the Tidyverse
Data never arrive in the condition that you need them in order to do effective data analysis. Data need to be re-shaped, re-arranged, and re-formatted, so that they can be visualized or be inputted into a machine learning algorithm. This course addresses the problem of wrangling your data so that you can bring them under control and analyze them effectively.
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14 hours
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English
BigQuery Machine Learning using Soccer Data
This is a self-paced lab that takes place in the Google Cloud console. Learn how to use BigQuery ML with soccer shot data to create and use an expected goals model.
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1 hour
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English