Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
دوراتنا
Unsupervised Learning, Recommenders, Reinforcement Learning
In the third course of the Machine Learning Specialization, you will: • Use unsupervised learning techniques for unsupervised learning: including clustering and anomaly detection. • Build recommender systems with a collaborative filtering approach and a content-based deep learning method. • Build a deep reinforcement learning model. The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online.
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Course by
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Self Paced
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28 ساعات
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الإنجليزية
Data Science Companion
The Data Science Companion provides an introduction to data science. You will gain a quick background in data science and core machine learning concepts, such as regression and classification. You’ll be introduced to the practical knowledge of data processing and visualization using low-code solutions, as well as an overview of the ways to integrate multiple tools effectively to solve data science problems. You will then leverage cloud resources from Amazon Web Services to scale data processing and accelerate machine learning model training.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Build a Machine Learning Image Classifier with Python
In this 1-hour long project-based course, you will learn how to build your own Machine Learning Image Classifier using Python and Colab. You will be able to easily load the data, preview it, process and normalize it, then train and test your model! I hope you enjoy the experience! 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
Machine Learning Rapid Prototyping with IBM Watson Studio
An emerging trend in AI is the availability of technologies in which automation is used to select a best-fit model, perform feature engineering and improve model performance via hyperparameter optimization. This automation will provide rapid-prototyping of models and allow the Data Scientist to focus their efforts on applying domain knowledge to fine-tune models. This course will take the learner through the creation of an end-to-end automated pipeline built by Watson Studio’s AutoAI experiment tool, explaining the underlying technology at work as developed by IBM Research.
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Course by
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Self Paced
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9 ساعات
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الإنجليزية
Python Essentials for MLOps
Python Essentials for MLOps (Machine Learning Operations) is a course designed to provide learners with the fundamental Python skills needed to succeed in an MLOps role. This course covers the basics of the Python programming language, including data types, functions, modules and testing techniques. It also covers how to work effectively with data sets and other data science tasks with Pandas and NumPy. Through a series of hands-on exercises, learners will gain practical experience working with Python in the context of an MLOps workflow.
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Course by
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Self Paced
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23 ساعات
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الإنجليزية
Solving ML Regression Problems with AWS AutoGluon
Hello everyone and welcome to this new hands-on project on Machine Learning Regression with Amazon Web Services (AWS) AutoGluon. In this project, we will train several regression models using a super powerful library known as AutoGluon. AutoGluon is the library behind AWS SageMaker autopilot and it allows for quick prototyping of several powerful models using a few lines of code.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Titanic Survival Prediction Using Machine Learning
In this 1-hour long project-based course, we will predict titanic survivors’ using logistic regression and naïve bayes classifiers. The sinking of the Titanic is one of the key sad tragedies in history and it took place on April 15th, 1912. The numbers of survivors were low due to lack of lifeboats for all passengers. This practical guided project, we will analyze what sorts of people were likely to survive this tragedy with the power of machine learning. Note: This course works best for learners who are based in the North America region.
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Course by
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3 ساعات
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الإنجليزية
Create a Connect Four Game in Python using Pygame
In this 1-hour 30 minutes long project-based course, you’ll be able to create a connect four game in python using python’s popular library Pygame. You will learn about most of pygame’s functions and modules. You'll be able to implement the connect four game logic. You’ll be able to insert drawings, images and texts into your game. You’ll be able to handle events and react to them being activated and finally, you’ll be able to take input from the user.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Creating a Rock, Paper, Scissors Game in Python
By the end of this project, you will be able to create a simple interactive game of rock, paper, or scissors. Throughout this guided project, you will be introduced to the basic skills needed for every programming language such as different data types, loops, and if conditions. Each part of the project will prepare you to code on your own in Python language, whether to create a game or simple coding.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Deep-Dive into Tensorflow Activation Functions
You've learned how to use Tensorflow. You've learned the important functions, how to design and implement sequential and functional models, and have completed several test projects. What's next? It's time to take a deep dive into activation functions, the essential function of every node and layer of a neural network, deciding whether to fire or not to fire, and adding an element of non-linearity (in most cases). In this 2 hour course-based project, you will join me in a deep-dive into an exhaustive list of activation functions usable in Tensorflow and other frameworks.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Prepare for DP-100: Data Science on Microsoft Azure 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-100 Azure Data Scientist Associate certification exam. You will refresh your knowledge of how to plan and create a suitable working environment for data science workloads on Azure, run data experiments, and train predictive models.
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Course by
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Self Paced
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9 ساعات
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الإنجليزية
Supervised Machine Learning: Regression
This course introduces you to one of the main types of modelling families of supervised Machine Learning: Regression. You will learn how to train regression models to predict continuous 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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21 ساعات
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الإنجليزية
Twitter API: Mining Data using Orange Data Mining Platform
In this one hour long project, you will mine, analyze and visualize various trending tweets using Word Cloud, Heat map, Document Map and perform sentiment analysis using Orange. Orange is an open-source data visualization, machine learning and data mining toolkit. Without any prior programming experience, Orange allows you to mine Twitter. If you are a corporate employee, marketer, or even a student who wants to explore how to mine tweets, Orange is the best platform for it.
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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: Predict Numbers from Handwritten Digits using a Neural Network, Keras, and R
In this 1-hour long project-based course, you will learn how to build a Neural Network Model using Keras and the MNIST Data Set. By the end of the course you will have built a model that will recognize the digits of han…
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
CUDA at Scale for the Enterprise
This course will aid in students in learning in concepts that scale the use of GPUs and the CPUs that manage their use beyond the most common consumer-grade GPU installations. They will learn how to manage asynchronous workflows, sending and receiving events to encapsulate data transfers and control signals.
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Course by
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Self Paced
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الإنجليزية
Machine Learning: Concepts and Applications
This course gives you a comprehensive introduction to both the theory and practice of machine learning. You will learn to use Python along with industry-standard libraries and tools, including Pandas, Scikit-learn, and Tensorflow, to ingest, explore, and prepare data for modeling and then train and evaluate models using a wide variety of techniques.
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Course by
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Self Paced
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38 ساعات
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الإنجليزية
Build Regression, Classification, and Clustering Models
In most cases, the ultimate goal of a machine learning project is to produce a model. Models make decisions, predictions—anything that can help the business understand itself, its customers, and its environment better than a human could. Models are constructed using algorithms, and in the world of machine learning, there are many different algorithms to choose from.
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Course by
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Self Paced
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20 ساعات
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الإنجليزية
Support Vector Machines in Python, From Start to Finish
In this lesson we will built this Support Vector Machine for classification using scikit-learn and the Radial Basis Function (RBF) Kernel. Our training data set contains continuous and categorical data from the UCI Machine Learning Repository to predict whether or not a patient has heart disease. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
How Entrepreneurs in Emerging Markets can master the Blockchain Technology
This course is for entrepreneurs needing to understand the blockchain and distributed ledger technologies that are fundamentally changing how financial and personal data is handled. The course will discuss blockchain as a distributed ledger and introduce distributed consensus as a mechanism to maintain the integrity of the blockchain. The other revolutionary technologies that are changing the world are artificial intelligence and machine learning. You will learn about the three major types of AI algorithms: supervised and unsupervised machine learning, as well as reinforcement learning.
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Course by
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Self Paced
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10 ساعات
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الإنجليزية
Scikit-Learn For Machine Learning Classification Problems
Hello everyone and welcome to this new hands-on project on Scikit-Learn Library for solving machine learning classification problems. In this project, we will learn how to build and train classifier models using Scikit-Learn library. Scikit-learn is a free machine learning library developed for python. Scikit-learn offers several algorithms for classification, regression, and clustering. Several famous machine learning models are included such as support vector machines, random forests, gradient boosting, and k-means.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Machine Learning with Spark on Google Cloud Dataproc
This is a self-paced lab that takes place in the Google Cloud console. In this lab you will learn how to implement logistic regression using a machine learning library for Apache Spark running on a Google Cloud Dataproc cluster to develop a model for data from a multivariable dataset.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Machine Learning Foundations for Product Managers
In this first course of the AI Product Management Specialization offered by Duke University's Pratt School of Engineering, you will build a foundational understanding of what machine learning is, how it works and when and why it is applied. To successfully manage an AI team or product and work collaboratively with data scientists, software engineers, and customers you need to understand the basics of machine learning technology.
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Course by
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Self Paced
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16 ساعات
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الإنجليزية
Introduction to Image Generation - Português Brasileiro
Neste curso, apresentamos os modelos de difusão, uma família de modelos de machine learning promissora no campo da geração de imagens. Os modelos de difusão são baseados na física, mais especificamente na termodinâmica. Nos últimos anos, eles se popularizaram no setor e nas pesquisas. Esses modelos servem de base para ferramentas e modelos avançados de geração de imagem no Google Cloud. Este curso é uma introdução à teoria dos modelos de difusão e como eles devem ser treinados e implantados na Vertex AI.
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Course by
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Self Paced
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الإنجليزية
Accounting Data Analytics with Python
This course focuses on developing Python skills for assembling business data. It will cover some of the same material from Introduction to Accounting Data Analytics and Visualization, but in a more general purpose programming environment (Jupyter Notebook for Python), rather than in Excel and the Visual Basic Editor.
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Course by
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Self Paced
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43 ساعات
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الإنجليزية
Introduction to Data Science and scikit-learn in Python
This course will teach you how to leverage the power of Python and artificial intelligence to create and test hypothesis. We'll start for the ground up, learning some basic Python for data science before diving into some of its richer applications to test our created hypothesis. We'll learn some of the most important libraries for exploratory data analysis (EDA) and machine learning such as Numpy, Pandas, and Sci-kit learn.
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Course by
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Self Paced
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14 ساعات
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الإنجليزية