Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
دوراتنا
Reinforcement Learning for Trading Strategies
In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. You will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied to time series data.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Designing the Future of Work
The workplace of tomorrow is an uncertain place. We live in a rapidly changing world, and design innovations such as artificial intelligence (AI), robotics, and big data are rapidly changing the fundamental nature of how we live and work. As these technologies continue to evolve at an exponential rate - it is becoming critical to understand their impact on contemporary work practices, and for businesses and employees to understand how to design a secure future amidst this disruption. What new, disruptive technologies are on the horizon? How will jobs change?
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Causal Inference
This course offers a rigorous mathematical survey of causal inference at the Master’s level. Inferences about causation are of great importance in science, medicine, policy, and business. This course provides an introduction to the statistical literature on causal inference that has emerged in the last 35-40 years and that has revolutionized the way in which statisticians and applied researchers in many disciplines use data to make inferences about causal relationships. We will study methods for collecting data to estimate causal relationships.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Applying Machine Learning to your Data with Google Cloud
In this course, we define what machine learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels. In the interactive labs, you will practice invoking the pretrained ML APIs available as well as build your own Machine Learning models using just SQL with BigQuery ML.
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Course by
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Self Paced
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7 ساعات
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الإنجليزية
DevOps on AWS: Operate and Monitor
The third and the final course in the DevOps series will teach how to use AWS Services to control the architecture in order to reach a better operational state. Monitoring and Operation are key aspects for both the release pipeline and production environments, because they provide instruments that help discover what's happening, as well as do modifications and enhancements on infrastructure that is currently running. This course teaches how to use Amazon CloudWatch for monitoring, as well as Amazon EventBridge and AWS Config for continuous compliance.
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Course by
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Self Paced
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4 ساعات
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الإنجليزية
Data Science in Stratified Healthcare and Precision Medicine
An increasing volume of data is becoming available in biomedicine and healthcare, from genomic data, to electronic patient records and data collected by wearable devices. Recent advances in data science are transforming the life sciences, leading to precision medicine and stratified healthcare. In this course, you will learn about some of the different types of data and computational methods involved in stratified healthcare and precision medicine. You will have a hands-on experience of working with such data. And you will learn from leaders in the field about successful case studies.
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Course by
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Self Paced
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17 ساعات
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الإنجليزية
MLOps Platforms: Amazon SageMaker and Azure ML
In MLOps (Machine Learning Operations) Platforms: Amazon SageMaker and Azure ML you will learn the necessary skills to build, train, and deploy machine learning solutions in a production environment using two leading cloud platforms: Amazon Web Services (AWS) and Microsoft Azure.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Machine Learning in the Enterprise - Français
Ce cours présente une approche pratique du workflow de ML avec une étude de cas dans laquelle une équipe est confrontée à plusieurs exigences métier et cas d'utilisation de ML. Cette équipe doit comprendre quels outils sont nécessaires pour gérer et gouverner les données, et trouver la meilleure approche pour les prétraiter. On présente à cette équipe trois options de création de modèles de ML pour deux cas d'utilisation spécifiques. Ce cours explique pourquoi l'équipe tire parti des avantages d'AutoML, de BigQuery ML ou de l'entraînement personnalisé pour atteindre ses objectifs.
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Course by
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Self Paced
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الإنجليزية
ML: Diagnose the presence of Breast Cancer with Python
In this 1-hour long project-based course, you will learn how to set up and run your Jupyter Notebook, load, preview and visualize data, then train, test and evaluate a machine learning model that predicts if a patient has breast cancer or not.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Orchestrating a TFX Pipeline with Airflow
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you'll learn to create your own machine learning pipelines using TensorFlow Extended (TFX) and Apache Airflow as the orchestrator.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Data Analysis with Python
Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models.
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Course by
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Self Paced
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15 ساعات
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الإنجليزية
Bitcoin Price Prediction using Facebook Prophet
In this 1.5-hour long project-based course, you will learn how to create a Facebook Prophet Machine learning Model and use it to Forecast the Price of Bitcoin for the future 30 days.
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Course by
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Self Paced
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4 ساعات
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الإنجليزية
Introduction to Generative AI - Italiano
Questo è un corso di microlearning di livello introduttivo volto a spiegare cos'è l'AI generativa, come viene utilizzata e in che modo differisce dai tradizionali metodi di machine learning. Descrive inoltre gli strumenti Google che possono aiutarti a sviluppare le tue app Gen AI.
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Course by
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Self Paced
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1 ساعات
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الإنجليزية
Tesla Stock Price Prediction using Facebook Prophet
In this 1.5-hour long project-based course, you will learn how to build a Facebook Prophet Machine learning model in order to forecast the price of Tesla 30 days into the future. We will also visualize the historical performance of Tesla through graphs and charts using Plotly express and evaluate the performance of the model against real data using Google Finance in Google Sheets. We will also dive into a brief stock analysis of Tesla and we will discuss PE ratio, EPS, Beta, Market cap, Volume and price range of Tesla.
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Course by
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Self Paced
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4 ساعات
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الإنجليزية
Visualizing Filters of a CNN using TensorFlow
In this short, 1 hour long guided project, we will use a Convolutional Neural Network - the popular VGG16 model, and we will visualize various filters from different layers of the CNN. We will do this by using gradient ascent to visualize images that maximally activate specific filters from different layers of the model. We will be using TensorFlow as our machine learning framework.
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Course by
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Self Paced
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1 ساعات
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الإنجليزية
SVM Regression, prediction and losses
In this 1-hour long project-based course, you will learn how to
Train SVM regression model- with large & small margin, second degree polynomial kernel, make prediction using Linear SVM classifier; how a small weight vector results in a large margin? and finally
pictorial representation for Hinge loss. This project gives you easy access to the invaluable learning techniques used by experts in machine learning.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Data for Machine Learning
This course is all about data and how it is critical to the success of your applied machine learning model.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Semantic Segmentation with Amazon Sagemaker
Please note: You will need an AWS account to complete this course. Your AWS account will be charged as per your usage. Please make sure that you are able to access Sagemaker within your AWS account. If your AWS account is new, you may need to ask AWS support for access to certain resources. You should be familiar with python programming, and AWS before starting this hands on project.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Machine Learning: an overview
The course provides a general overview of the main methods in the machine learning field. Starting from a taxonomy of the different problems that can be solved through machine learning techniques, the course briefly presents some algorithmic solutions, highlighting when they can be successful, but also their limitations. These concepts will be explained through examples and case studies.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Explainable Machine Learning with LIME and H2O in R
Welcome to this hands-on, guided introduction to Explainable Machine Learning with LIME and H2O in R. By the end of this project, you will be able to use the LIME and H2O packages in R for automatic and interpretable machine learning, build classification models quickly with H2O AutoML and explain and interpret model predictions using LIME.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Simple Nearest Neighbors Regression and Classification
In this 2-hour long project-based course, we will explore the basic principles behind the K-Nearest Neighbors algorithm, as well as learn how to implement KNN for decision making in Python.
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Course by
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Self Paced
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4 ساعات
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الإنجليزية
Introduction to Generative AI
This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
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Course by
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Self Paced
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1 ساعات
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الإنجليزية
Preparing for DP-900: Microsoft Azure Data Fundamentals Exam
Microsoft certifications give you a professional advantage by providing globally recognized and industry-endorsed evidence of mastering skills in digital and cloud businesses. In this course, you will prepare to take the DP-900 Microsoft Azure Data Fundamentals certification exam. You will refresh your knowledge of the fundamentals of database concepts in a cloud environment, the basic skilling in cloud data services, and foundational knowledge of cloud data services within Microsoft Azure.
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Course by
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Self Paced
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6 ساعات
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الإنجليزية
Supervised Machine Learning: Classification
This course introduces you to one of the main types of modeling families of supervised Machine Learning: Classification. You will learn how to train predictive models to classify categorical outcomes and how to use error metrics to compare across different models.
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Course by
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Self Paced
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25 ساعات
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الإنجليزية
Introduction to Customer Segmentation in Python
In this 2 hour long project, you will learn how to approach a customer purchase dataset, and how to explore the intricacies of such a dataset. You will learn the basic underlying ideas behind Principal Component Analysis, Kernel Principal Component Analysis, and K-Means Clustering. You will learn how to leverage these concepts, paired with industry knowledge and auxiliary modeling concepts to segment the customers of a certain store, and find similarities and differences between different clusters using unsupervised machine learning techniques.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية