Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
دوراتنا
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.
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Course by
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Self Paced
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38 ساعات
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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.
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Course by
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Self Paced
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14 ساعات
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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.
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Course by
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Self Paced
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26 ساعات
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الإنجليزية
AI Workflow: Feature Engineering and Bias Detection
This is the third 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 3 introduces you to the next stage of the workflow for our hypothetical media company. In this stage of work you will learn best practices for feature engineering, handling class imbalances and detecting bias in the data. Class imbalances can seriously affect the validity of your
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Analyze Datasets and Train ML Models using AutoML
In the first course of the Practical Data Science Specialization, you will learn foundational concepts for exploratory data analysis (EDA), automated machine learning (AutoML), and text classification algorithms. With Amazon SageMaker Clarify and Amazon SageMaker Data Wrangler, you will analyze a dataset for statistical bias, transform the dataset into machine-readable features, and select the most important features to train a multi-class text classifier.
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Course by
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Self Paced
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14 ساعات
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الإنجليزية
Using Sensors With Your Raspberry Pi
This course on integrating sensors with your Raspberry Pi is course 3 of a Coursera Specialization and can be taken separately or as part of the specialization. Although some material and explanations from the prior two courses are used, this course largely assumes no prior experience with sensors or data processing other than ideas about your own projects and an interest in building projects with sensors. This course focuses on core concepts and techniques in designing and integrating any sensor, rather than overly specific examples to copy.
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Course by
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Self Paced
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9 ساعات
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الإنجليزية
Extract, Transform, and Load Data
This course is designed for business and data professional seeking to learn the first technical phase of the data science process known as Extract, Transform and Load or ETL. Learners will be taught how to collect data from multiple sources so it is available to be transformed and cleaned and then will dive into collected data sets to prepare and clean data so that it can later be loaded into its ultimate destination. In the conclusion of the course learners will load data into its ultimate destination so that it can be analyzed and modeled.
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Course by
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Self Paced
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15 ساعات
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الإنجليزية
Julia Scientific Programming
This course introduces you to Julia as a first programming language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics, and many more.
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Course by
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Self Paced
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19 ساعات
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الإنجليزية
Regression and Classification
Introduction to Statistical Learning will explore concepts in statistical modeling, such as when to use certain models, how to tune those models, and if other options will provide certain trade-offs. We will cover Regression, Classification, Trees, Resampling, Unsupervised techniques, and much more! This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform.
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Course by
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35 ساعات
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الإنجليزية
Supervised Text Classification for Marketing Analytics
Marketing data often requires categorization or labeling. In today’s age, marketing data can also be very big, or larger than what humans can reasonably tackle. In this course, students learn how to use supervised deep learning to train algorithms to tackle text classification tasks. Students walk through a conceptual overview of supervised machine learning and dive into real-world datasets through instructor-led tutorials in Python.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Data Science as a Field
This course provides a general introduction to the field of Data Science. It has been designed for aspiring data scientists, content experts who work with data scientists, or anyone interested in learning about what Data Science is and what it’s used for. Weekly topics include an overview of the skills needed to be a data scientist; the process and pitfalls involved in data science; and the practice of data science in the professional and academic world.
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Course by
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Self Paced
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11 ساعات
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الإنجليزية
MongoDB Aggregation Framework
This course will teach you how to perform data analysis using MongoDB's powerful Aggregation Framework. You'll begin this course by building a foundation of essential aggregation knowledge. By understanding these features of the Aggregation Framework you will learn how to ask complex questions of your data.
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Course by
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Self Paced
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19 ساعات
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الإنجليزية
Advanced Data Science Capstone
This project completer has proven a deep understanding on massive parallel data processing, data exploration and visualization, advanced machine learning and deep learning and how to apply his knowledge in a real-world practical use case where he justifies architectural decisions, proves understanding the characteristics of different algorithms, frameworks and technologies and how they impact model performance and scalability.
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Course by
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9 ساعات
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الإنجليزية
توقع حضور المواعيد الطبية باستخدام Python
في نهاية المشروع ده هتقدر تصمم model ذكاء صناعي عشان يتوقع المريض هيجي المعاد إلي كان محدد ولا لاباستخدام Python و Jupyter Notebook. خلال المشروع هنمشى مع بعض خطوة بخطوة عشان نقدر نحلل البيانات إلي هتكون معنا من website Kaggle.com الdata دي هتكون عن مرضى في البرازيل.و هنقدر نحدد ازاي الmachine learning engineer بيختار الmachine learning model بتاعو. و ازاي إقدر إستعمل ال-machine learning model بتاعي ده عشان اتوقع هل المريض ده هيجي ولا لا. المشروع ده هيفيد الناس المهتمة بمجال الdata science.
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Course by
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Self Paced
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2 ساعات
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عربي
برنامج تنبيه سطح المكتب باستخدام Python: إشعارات Covid-19
فى نهاية هذا المشروع ، سوف تكون قادرًا على أن تصنع إشعارات مخصصة لل desktop بتاعك باستخدام Python. و هتعرف تستخدم بطريقه مفيده مكتبات Python مختلفه عشان تقدر تطلع بيانات من الانترنت و تقوم بمعالجتها و بعد كده تقدمها ك إشعارات. في المشروع ده هتعمل اخبار COVID-19 ك إشعارات عشان تبقى دايما عارف كل حاجه جديده اول باول.
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Course by
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Self Paced
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3 ساعات
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عربي
مطوّر الواجهة الخلفية من Meta
Ready to gain new skills and the tools developers use to create websites and web applications?
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Course by
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Self Paced
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عربي
Erste Schritte mit R
In diesem zweistündigen Projekt wirst du die Basics der Programmiersprache R kennen lernen. Darüberhinaus wirst du deine ersten Schritte mit R für Data Analysis gehen. Du wirst die Programmierumgebung RStudio benutzen und Datentypen und Datenstrukturen in R unterscheiden und benutzen lernen. Außerdem wirst du Daten, die in externen CSV- und XLSX-Dateien gespeichert sind, in RStudion einlesen und filtern.
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Course by
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Self Paced
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2 ساعات
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ألماني
Curso Completo de Data Science
Este proyecto es un curso práctico y efectivo para aprender Data Science de manera práctica y aplicada. Aprenderemos desde cero todo el proceso y fases del data science, desarrollando un proyecto práctico de cada una de estas fases.
Gracias a ello aprenderás a desarrollar un modelo completo de Machine learning, desde el pre-procesamiento de datos hasta la validación del modelo.
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Course by
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Self Paced
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3 ساعات
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الإسبانية
Ciclo completo del desarrollo de un proyecto de Data Science
En este curso aprenderemos a desarrollar el ciclo completo de la ciencia de datos, desarrollando en profundidad la parte del despliegue del modelo. Para ello utilizaremos tecnologías como Python, Flask, Postman, heroku, Scikit-learn o anaconda.
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Course by
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Self Paced
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3 ساعات
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الإسبانية
Business Transformation with Google Cloud auf Deutsch
Was ist Cloudtechnologie bzw. Data Science und warum ist der Begriff in aller Munde? Welche Vorteile bietet die Cloud für Sie, Ihr Team und Ihr Unternehmen? Wenn Sie sich mit dem Thema Cloudtechnologie vertraut machen möchten, um bessere Arbeit zu leisten, die Zukunft Ihres Unternehmens mitzugestalten und im Zeitalter der Cloud Ihr volles Potenzial zu entfalten, ist der Kurs "Business Transformation with Google Cloud" für Sie die richtige Wahl. In dieser interaktiven Schulung lernen Sie die wichtigsten Cloud-Geschäftsfaktoren kennen, insbesondere Google Cloud.
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Course by
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Self Paced
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18 ساعات
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ألماني
Introducción a Pandas para Data Science
En este proyecto guiado obtendrás experiencia práctica trabajando con la librería Pandas y creando tu propio cuaderno de Jupyter Lab. Los conocimientos básicos que obtengas te permitirán trabajar con cualquier base de datos para analizar la información. Al final de este proyecto serás capaz de crear tus propios cuadernos con análisis estadísticos de diferentes bases de datos.
Nota: Este curso está dirigido a personas que buscan iniciarse en el mundo de la ciencia de datos o el machine learning.
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Course by
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Self Paced
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3 ساعات
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الإسبانية
Ein Crashkurs in Datenwissenschaft
Inzwischen haben Sie sicher schon von Datenwissenschaft und Big Data gehört. In diesem einwöchigen Kurs werden wir in einem Crashkurs vermitteln, was diese Begriffe bedeuten und inwiefern sie in erfolgreichen Organisationen eine Rolle spielen. Dieser Kurs richtet sich an alle, die mehr über die Datenwissenschaft erfahren möchten, aber auch an jene, die vorhaben, ein Team von Datenwissenschaftlern zu leiten. Das Ziel ist es, Sie so schnell wie möglich pragmatisch mit der Datenwissenschaft vertraut zu machen.
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Course by
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Self Paced
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6 ساعات
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ألماني
Cómo importar datos y crear visualizaciones en Python
Al final de este proyecto, podrás importar fuentes básicas de datos en Python y crear potentes visualizaciones a partir de su información y con muy pocas instrucciones de código. En este proyecto guiado aprenderá qué es el Data Science y cómo podemos dominarlo con el lenguaje Python desde cero. Python tiene un inmenso potencial con todas las librerías enfocadas en Data Science que le harán cambiar su día a día en el análisis de datos aportándole un salto cualitativo en su carrera profesional mejorando sustancialmente sus habilidades analíticas de manera muy eficiente.
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Course by
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Self Paced
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3 ساعات
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الإسبانية
Ferramentas para Ciência de Dados: Introdução ao R
Nossas boas-vindas ao Curso Ferramentas para Ciência de Dados: Introdução ao R. Neste curso, você aprenderá que o mundo evoluiu muito quando o assunto é tomada de decisão baseada em dados e já não é possível comparar a quantidade de informações a que temos acesso atualmente com o que tínhamos disponíveis décadas atrás.
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Course by
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Self Paced
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البرتغالي
데이터 과학이란 무엇인가?
The art of uncovering the insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year. Since then, people working in data science have carved out a unique and distinct field for the work they do. This field is data science. In this course, we will meet some data science practitioners and we will get an overview of what data science is today.
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Course by
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Self Paced
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الكورية