Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
دوراتنا
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.
-
Course by
-
Self Paced
-
38 ساعات
-
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.
-
Course by
-
Self Paced
-
20 ساعات
-
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.
-
Course by
-
Self Paced
-
2 ساعات
-
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.
-
Course by
-
Self Paced
-
10 ساعات
-
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.
-
Course by
-
Self Paced
-
2 ساعات
-
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.
-
Course by
-
Self Paced
-
2 ساعات
-
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.
-
Course by
-
Self Paced
-
16 ساعات
-
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.
-
Course by
-
Self Paced
-
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.
-
Course by
-
Self Paced
-
43 ساعات
-
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.
-
Course by
-
Self Paced
-
14 ساعات
-
الإنجليزية
Create Your First Chatbot with Rasa and Python
In this 2 hour long project-based course, you will learn to create chatbots with Rasa and Python. Rasa is a framework for developing AI powered, industrial grade chatbots. It’s incredibly powerful, and is used by developers worldwide to create chatbots and contextual assistants. In this project, we are going to understand some of the most important basic aspects of the Rasa framework and chatbot development. Once you’re done with this project, you will be able to create simple AI powered chatbots on your own.
-
Course by
-
Self Paced
-
3 ساعات
-
الإنجليزية
Foundations of Data Science
This is the first of seven courses in the Google Advanced Data Analytics Certificate, which will help develop the skills needed to apply for more advanced data professional roles, such as an entry-level data scientist or advanced-level data analyst. Data professionals analyze data to help businesses make better decisions. To do this, they use powerful techniques like data storytelling, statistics, and machine learning. In this course, you’ll begin your learning journey by exploring the role of data professionals in the workplace.
-
Course by
-
Self Paced
-
23 ساعات
-
الإنجليزية
Statistics for Machine Learning for Investment Professionals
One of the biggest changes in the past decade is the rapid adoption of machine learning, AI, and big data in investment decision making. This course introduces learners with knowledge of the investment industry to foundational statistical concepts underpinning machine learning as well as advanced AI techniques. This course demonstrates core modeling frameworks along with carefully selected real-world investment practice examples. The course seeks to familiarize learners with two important programming languages — Python and R (no prior knowledge of Python or R necessary).
-
Course by
-
Self Paced
-
18 ساعات
-
الإنجليزية
Naive Bayes 101: Resume Selection with Machine Learning
In this project, we will build a Naïve Bayes Classifier to predict whether a given resume text is flagged or not. Our training data consist of 125 resumes with 33 flagged resumes and 92 non flagged resumes. This project could be practically used to screen resumes in companies.
-
Course by
-
Self Paced
-
3 ساعات
-
الإنجليزية
Hands-on Machine Learning with AWS and NVIDIA
Machine learning (ML) projects can be complex, tedious, and time consuming. AWS and NVIDIA solve this challenge with fast, effective, and easy-to-use capabilities for your ML project.
-
Course by
-
Self Paced
-
23 ساعات
-
الإنجليزية
Ethical Issues in Data Science
Computing applications involving large amounts of data – the domain of data science – impact the lives of most people in the U.S. and the world. These impacts include recommendations made to us by internet-based systems, information that is available about us online, techniques that are used for security and surveillance, data that is used in health care, and many more.
-
Course by
-
Self Paced
-
24 ساعات
-
الإنجليزية
Predict Baby Weight with TensorFlow on AI Platform
In this lab you train, evaluate, and deploy a machine learning model to predict a baby’s weight. You then send requests to the model to make online predictions. This lab is part of a series of labs on processing scientific data.
-
Course by
-
Self Paced
-
2 ساعات
-
الإنجليزية
TensorFlow Serving with Docker for Model Deployment
This is a hands-on, guided project on deploying deep learning models using TensorFlow Serving with Docker. In this 1.5 hour long project, you will train and export TensorFlow models for text classification, learn how to deploy models with TF Serving and Docker in 90 seconds, and build simple gRPC and REST-based clients in Python for model inference.
-
Course by
-
Self Paced
-
3 ساعات
-
الإنجليزية
Regression with Automatic Differentiation in TensorFlow
In this 1.5 hour long project-based course, you will learn about constants and variables in TensorFlow, you will learn how to use automatic differentiation, and you will apply automatic differentiation to solve a linear regression problem. By the end of this project, you will have a good understanding of how machine learning algorithms can be implemented in TensorFlow.
In order to be successful in this project, you should be familiar with Python, Gradient Descent, Linear Regression.
-
Course by
-
Self Paced
-
2 ساعات
-
الإنجليزية
Data Science for Business Innovation
This is your chance to learn all about Data Science for Business innovation and future-proof your career. Match your business experience tech and analytics! The Data Science for Business Innovation nano-course is a compendium of the must-have expertise in data science for executives and managers to foster data-driven innovation. The course explains what Data Science is and why it is so hyped.
-
Course by
-
Self Paced
-
7 ساعات
-
الإنجليزية
CUDA Advanced Libraries
This course will complete the GPU specialization, focusing on the leading libraries distributed as part of the CUDA Toolkit. Students will learn how to use CuFFT, and linear algebra libraries to perform complex mathematical computations. The Thrust library’s capabilities in representing common data structures and associated algorithms will be introduced. Using cuDNN and cuTensor they will be able to develop machine learning applications that help with object detection, human language translation and image classification.
-
Course by
-
Self Paced
-
25 ساعات
-
الإنجليزية
Unsupervised Algorithms in Machine Learning
One of the most useful areas in machine learning is discovering hidden patterns from unlabeled data. Add the fundamentals of this in-demand skill to your Data Science toolkit. In this course, we will learn selected unsupervised learning methods for dimensionality reduction, clustering, and learning latent features. We will also focus on real-world applications such as recommender systems with hands-on examples of product recommendation algorithms. Prior coding or scripting knowledge is required. We will be utilizing Python extensively throughout the course.
-
Course by
-
Self Paced
-
38 ساعات
-
الإنجليزية
Interpretable machine learning applications: Part 5
You will be able to use the Aequitas Tool as a tool to measure and detect bias in the outcome of a machine learning prediction model. As a use case, we will be working with the dataset about recidivism, i.e., the likelihood for a former imprisoned person to commit another offence within the first two years, since release from prison. The guided project will be making use of the COMPAS dataset, which already includes predicted as well as actual outcomes.
-
Course by
-
Self Paced
-
3 ساعات
-
الإنجليزية
Code Free Data Science
The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data Science without any programming requirements. Machine Learning methods will be presented by utilizing the KNIME Analytics Platform to discover patterns and relationships in data. Predicting future trends and behaviors allows for proactive, data-driven decisions.
-
Course by
-
Self Paced
-
14 ساعات
-
الإنجليزية
Calculus for Machine Learning and Data Science
Newly updated for 2024! Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. In machine learning, you apply math concepts through programming. And so, in this specialization, you’ll apply the math concepts you learn using Python programming in hands-on lab exercises.
-
Course by
-
Self Paced
-
26 ساعات
-
الإنجليزية