Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
دوراتنا
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.
-
Course by
-
Self Paced
-
29 ساعات
-
الإنجليزية
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.
-
Course by
-
Self Paced
-
الإنجليزية
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.
-
Course by
-
Self Paced
-
14 ساعات
-
الإنجليزية
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.
-
Course by
-
Self Paced
-
1 ساعات
-
الإنجليزية
Generative Adversarial Networks (GANs)
About GANs Generative Adversarial Networks (GANs) are powerful machine learning models capable of generating realistic image, video, and voice outputs. Rooted in game theory, GANs have wide-spread application: from improving cybersecurity by fighting against adversarial attacks and anonymizing data to preserve privacy to generating state-of-the-art images, colorizing black and white images, increasing image resolution, creating avatars, turning 2D images to 3D, and more. About this Specialization The DeepLearning.AI Generative Adversarial Networks (GANs) Specialization provides an exciting
-
Course by
-
Self Paced
-
الإنجليزية
Encoder-Decoder Architecture - Italiano
Questo corso ti offre un riepilogo dell'architettura encoder-decoder, che è un'architettura di machine learning potente e diffusa per attività da sequenza a sequenza come traduzione automatica, riassunto del testo e risposta alle domande. Apprenderai i componenti principali dell'architettura encoder-decoder e come addestrare e fornire questi modelli. Nella procedura dettagliata del lab corrispondente, implementerai in TensorFlow dall'inizio un semplice codice dell'architettura encoder-decoder per la generazione di poesie da zero.
-
Course by
-
Self Paced
-
1 ساعات
-
الإنجليزية
Launching Machine Learning: Delivering Operational Success with Gold Standard ML Leadership
Machine learning runs the world. It generates predictions for each individual customer, employee, voter, and suspect, and these predictions drive millions of business decisions more effectively, determining whom to call, mail, approve, test, diagnose, warn, investigate, incarcerate, set up on a date, or medicate. But, to make this work, you've got to bridge what is a prevalent gap between business leadership and technical know-how. Launching machine learning is as much a management endeavor as a technical one. Its success relies on a very particular business leadership practice.
-
Course by
-
Self Paced
-
14 ساعات
-
الإنجليزية
Unsupervised Learning and Its Applications in Marketing
Welcome to the Unsupervised Learning and Its Applications in Marketing course! In this course, you will delve into the fascinating world of unsupervised machine learning and its relevance to the field of marketing. Unsupervised learning is a powerful approach that allows us to uncover hidden patterns and insights from vast amounts of historical data without the need for explicit labels or human intervention.
-
Course by
-
Self Paced
-
22 ساعات
-
الإنجليزية
Practical Predictive Analytics: Models and Methods
Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems. Learning Goals: After completing this course, you will be able to: 1.
-
Course by
-
7 ساعات
-
الإنجليزية
Self Service ML Pipelines Using Dataprep and AutoML Tables
This is a self-paced lab that takes place in the Google Cloud console. In this lab you will learn how to use Dataprep in conjunction with AutoML Tables to build and operate your machine learning pipelines.
-
Course by
-
Self Paced
-
2 ساعات
-
الإنجليزية
Clinical Decision Support Systems - CDSS 4
Machine learning systems used in Clinical Decision Support Systems (CDSS) require further external validation, calibration analysis, assessment of bias and fairness. In this course, the main concepts of machine learning evaluation adopted in CDSS will be explained. Furthermore, decision curve analysis along with human-centred CDSS that need to be explainable will be discussed. Finally, privacy concerns of deep learning models and potential adversarial attacks will be presented along with the vision for a new generation of explainable and privacy-preserved CDSS.
-
Course by
-
Self Paced
-
8 ساعات
-
الإنجليزية
CertNexus Certified Ethical Emerging Technologist
The Certified Ethical Emerging Technologist (CEET) industry validated certification helps professionals differentiate themselves from other job candidates by demonstrating their ability to ethically navigate data driven emerging technologies such as AI, Machine Learning and Data Science. Organizations and governments are seeking out ethics professionals to minimize risk and guide their decision-making about the design of inclusive, responsible, and trusted technology.
-
Course by
-
Self Paced
-
الإنجليزية
Essential Causal Inference Techniques for Data Science
Data scientists often get asked questions related to causality: (1) did recent PR coverage drive sign-ups, (2) does customer support increase sales, or (3) did improving the recommendation model drive revenue?
-
Course by
-
Self Paced
-
3 ساعات
-
الإنجليزية
Managing Machine Learning Projects
This second course of the AI Product Management Specialization by Duke University's Pratt School of Engineering focuses on the practical aspects of managing machine learning projects. The course walks through the keys steps of a ML project from how to identify good opportunities for ML through data collection, model building, deployment, and monitoring and maintenance of production systems.
-
Course by
-
18 ساعات
-
الإنجليزية
AI Workflow: Machine Learning, Visual Recognition and NLP
This is the fourth course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. Course 4 covers the next stage of the workflow, setting up models and their associated data pipelines for a hypothetical streaming media company. The first topic covers the complex topic of evaluation metrics, where you will learn best practices for a number of different metrics including regressi
-
Course by
-
Self Paced
-
14 ساعات
-
الإنجليزية
Database Design and Operational Business Intelligence
Welcome to the course on Database Design and Operational Business Intelligence. This course is strategically crafted to empower you with the skills needed to design a robust database and efficiently manage intricate datasets. Throughout this course, you will acquire the expertise to develop well-formatted databases that are seamlessly designed to integrate with Power BI. Throughout this course, you'll delve into how Power BI and MS SQL Server are applied within specific industries. By the end of this course, you will be able to: 1.
-
Course by
-
Self Paced
-
الإنجليزية
Recommender Systems
In this course you will: a) understand the basic concept of recommender systems. b) understand the Collaborative Filtering. c) understand the Recommender System with Deep Learning. d) understand the Further Issues of Recommender Systems. Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, conditional probability, and basic machine learning algorithms.
-
Course by
-
الإنجليزية
Data Engineering Capstone Project
Showcase your skills in this Data Engineering project! In this course you will apply a variety of data engineering skills and techniques you have learned as part of the previous courses in the IBM Data Engineering Professional Certificate. You will demonstrate your knowledge of Data Engineering by assuming the role of a Junior Data Engineer who has recently joined an organization and be presented with a real-world use case that requires architecting and implementing a data analytics platform. In this Capstone project you will complete numerous hands-on labs.
-
Course by
-
13 ساعات
-
الإنجليزية
Machine Learning for Trading
This 3-course Specialization from Google Cloud and New York Institute of Finance (NYIF) is for finance professionals, including but not limited to hedge fund traders, analysts, day traders, those involved in investment management or portfolio management, and anyone interested in gaining greater knowledge of how to construct effective trading strategies using Machine Learning (ML) and Python. Alternatively, this program can be for Machine Learning professionals who seek to apply their craft to quantitative trading strategies.
-
Course by
-
Self Paced
-
الإنجليزية
Using R for Regression and Machine Learning in Investment
In this course, the instructor will discuss various uses of regression in investment problems, and she will extend the discussion to logistic, Lasso, and Ridge regressions. At the same time, the instructor will introduce various concepts of machine learning. You can consider this course as the first step toward using machine learning methodologies in solving investment problems. The course will cover investment analysis topics, but at the same time, make you practice it using R programming.
-
Course by
-
Self Paced
-
18 ساعات
-
الإنجليزية
Introduction to Discrete Mathematics for Computer Science
Discrete Mathematics is the language of Computer Science. One needs to be fluent in it to work in many fields including data science, machine learning, and software engineering (it is not a coincidence that math puzzles are often used for interviews). We introduce you to this language through a fun try-this-before-we-explain-everything approach: first you solve many interactive puzzles that are carefully designed specifically for this online specialization, and then we explain how to solve the puzzles, and introduce important ideas along the way.
-
Course by
-
Self Paced
-
الإنجليزية
Deep Learning and Reinforcement Learning
This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. Deep Learning is a subset of Machine Learning that has applications in both Supervised and Unsupervised Learning, and is frequently used to power most of the AI applications that we use on a daily basis. First you will learn about the theory behind Neural Networks, which are the basis of Deep Learning, as well as several modern architectures of Deep Learning.
-
Course by
-
32 ساعات
-
الإنجليزية
Preparing for Google Cloud Certification: Machine Learning Engineer
87% of Google Cloud certified users feel more confident in their cloud skills.
-
Course by
-
Self Paced
-
الإنجليزية
Learn SQL Basics for Data Science
This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency. Through four progressively more difficult SQL projects with data science applications, you will cover topics such as SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, Delta Lake and more.
-
Course by
-
Self Paced
-
الإنجليزية