Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
دوراتنا
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
A Geometrical Approach to Genome Analysis: Skew & Z-Curve
In this 1-hour long project-based course, you will learn how to analyze a complete viral genome using geometrical methods (skews and Z-curve), 2D- and 3D-plotting in Python, and how to use some important Python libraries (like Tkinter, Matplotlib, and NumPy) helping you accomplish this. You will also learn about the genomes of some viruses including, Corona, SARS, HIV, Zika, Nidovirous, and rubella viruses.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Linear Regression with Python
In this 2-hour long project-based course, you will learn how to implement Linear Regression using Python and Numpy. Linear Regression is an important, fundamental concept if you want break into Machine Learning and Deep Learning.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Choisir la Meilleure Méthode pour Illustrer les Données
La visualisation reste une étape importante et primordial dans l'exploration et l'analyse des ensembles de données du monde réel. En tant que telle, la visualisation est une méthode est indispensable dans la boîte à outils de tout Scientifique de données. C'est aussi un outil puissant pour identifier les problèmes dans les analyses et pour illustrer les résultats. Dans ce projet, vous serez en mesure de choisir la meilleure manière d'illustrer votre data à l'aide des Librairies de Visualisation de Python .
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Course by
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Self Paced
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3 ساعات
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الفرنسية
Introduction to Machine Learning: Supervised Learning
In this course, you’ll be learning various supervised ML algorithms and prediction tasks applied to different data. You’ll learn when to use which model and why, and how to improve the model performances. We will cover models such as linear and logistic regression, KNN, Decision trees and ensembling methods such as Random Forest and Boosting, kernel methods such as SVM. 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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40 ساعات
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الإنجليزية
Mathematics for Machine Learning
For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in mathematics - stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to how it’s used in Computer Science.
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Course by
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Self Paced
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الإنجليزية
Introduction to Computational Statistics for Data Scientists
The purpose of this series of courses is to teach the basics of Computational Statistics for the purpose of performing inference to aspiring or new Data Scientists. This is not intended to be a comprehensive course that teaches the basics of statistics and probability nor does it cover Frequentist statistical techniques based on the Null Hypothesis Significance Testing (NHST).
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Course by
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Self Paced
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الإنجليزية
IBM Data Science
Prepare for a career in the high-growth field of data science. In this program, you’ll develop the skills, tools, and portfolio to have a competitive edge in the job market as an entry-level data scientist in as little as 4 months. No prior knowledge of computer science or programming languages is required. Data science involves gathering, cleaning, organizing, and analyzing data with the goal of extracting helpful insights and predicting expected outcomes.
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Course by
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Self Paced
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الإنجليزية
IBM Data Analyst
Prepare for a career in the high-growth field of data analytics. In this program, you’ll learn in-demand skills like Python, Excel, and SQL to get job-ready in as little as 4 months. Data analysis is the process of collecting, storing, modeling, and analyzing data that can inform executive decision-making, and the demand for skilled data analysts has never been greater. This program will teach you the foundational data skills employers are seeking for entry-level data analytics roles.
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Course by
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التعلم الذاتي
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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
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Course by
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Self Paced
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14 ساعات
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الإنجليزية
Applied Data Science
This action-packed Specialization is for data science enthusiasts who want to acquire practical skills for real world data problems. If you’re interested in pursuing a career in data science, and already have foundational skills or have completed the Introduction to Data Science Specialization, this program is for you! This 4-course Specialization will give you the tools you need to analyze data and make data driven business decisions leveraging computer science and statistical analysis.
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Course by
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Self Paced
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الإنجليزية
Expressway to Data Science: Python Programming
How many times have you decided to learn a programming language but got stuck somewhere along the way, grew frustrated, and gave up? This specialization is designed for learners who have little or no programming experience but want to use Python as a tool to play with data. In the first course, Introduction to Python Fundamentals, you will learn the basic input and output methods in Python, so you can write your first program. You will learn variables, operations, and flow control statements for more advanced programming.
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Course by
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Self Paced
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الإنجليزية
Preparing Data for Machine Learning Models
By the end of this project, you will extract colors pixels as training dataset into a form where you can feed it to your Machine Learning Model using numpy arrays.
In this project we will work with images, you will get introduced to computer vision basic concepts.
Moreover, you will be able to properly handle arrays and preprocess your training dataset and label it.
Extracting features and preparing data is a very crucial task as it influences your model.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Supervised Machine Learning: Regression and Classification
In the first course of the Machine Learning Specialization, you will: • Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. • Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression 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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33 ساعات
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الإنجليزية
Analyzing Data with Python
In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using scikit-learn!
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Course by
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15
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الإنجليزية
Guided Tour of Machine Learning in Finance
This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures.
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Course by
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Self Paced
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24 ساعات
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الإنجليزية
Python for Data Science, AI & Development
Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the most popular languages in the programming and data science world and demand for individuals who have the ability to apply Python has never been higher. This introduction to Python course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn about Python basics and the different data types.
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Course by
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Self Paced
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27 ساعات
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الإنجليزية
NumPy Tutorial
Start learning NumPy with the w3schools course and improve your statistics and math programming skills. NumPy is a Python library for using arrays in statistics and math. This is a structured and interactive version of the W3Schools NumPy Tutorial. The course is self-paced with text based modules, practical interactive examples and exercises to check your understanding as you progress. W3Schools is the world's largest web developer learning site. Start learning with our proven tutorials used by millions of learners!
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Logistic Regression with Python and Numpy
Welcome to this project-based course on Logistic with NumPy and Python. In this project, you will do all the machine learning without using any of the popular machine learning libraries such as scikit-learn and statsmodels. The aim of this project and is to implement all the machinery, including gradient descent, cost function, and logistic regression, of the various learning algorithms yourself, so you have a deeper understanding of the fundamentals.
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Course by
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Self Paced
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4 ساعات
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الإنجليزية
Fundamental Tools of Data Wrangling
Data wrangling is a crucial step in the data analysis process, as it involves the transformation and preparation of raw data into a suitable format for analysis. The "Fundamental Tools for Data Wrangling" course is designed to provide participants with essential skills and knowledge to effectively manipulate, clean, and analyze data. Participants will be introduced to the fundamental tools commonly used in data wrangling, including Python, data structures, NumPy, and pandas.
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Course by
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Self Paced
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27 ساعات
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الإنجليزية
IBM Data Analyst Capstone Project
By completing this final capstone project you will apply various Data Analytics skills and techniques that you have learned as part of the previous courses in the IBM Data Analyst Professional Certificate. You will assume the role of an Associate Data Analyst who has recently joined the organization and be presented with a business challenge that requires data analysis to be performed on real-world datasets.
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Course by
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Self Paced
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21 ساعات
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الإنجليزية
Get Started with Python
This is the second of seven courses in the Google Advanced Data Analytics Certificate. The Python programming language is a powerful tool for data analysis. In this course, you’ll learn the basic concepts of Python programming and how data professionals use Python on the job. You'll explore concepts such as object-oriented programming, variables, data types, functions, conditional statements, loops, and data structures.
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Course by
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Self Paced
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31 ساعات
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الإنجليزية
Data Science with NumPy, Sets, and Dictionaries
Become proficient in NumPy, a fundamental Python package crucial for careers in data science. This comprehensive course is tailored to novice programmers aspiring to become data scientists, software developers, data analysts, machine learning engineers, data engineers, or database administrators. Starting with foundational computer science concepts, such as object-oriented programming and data organization using sets and dictionaries, you'll progress to more intricate data structures like arrays, vectors, and matrices.
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Course by
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Self Paced
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31 ساعات
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الإنجليزية
Get Familiar with ML basics in a Kaggle Competition
In this 1-hour long project, you will be able to understand how to predict which passengers survived the Titanic shipwreck and make your first submission in an Machine Learning competition inside the Kaggle platform. Also, you as a beginner in Machine Learning applications, will get familiar and get a deep understanding of how to start a model prediction using basic supervised Machine Learning models. We will choose classifiers to learn, predict, and make an Exploratory Data Analysis (also called EDA).
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Python for Data Analysis: Pandas & NumPy
In this hands-on project, we will understand the fundamentals of data analysis in Python and we will leverage the power of two important python libraries known as Numpy and pandas. NumPy and Pandas are two of the most widely used python libraries in data science. They offer high-performance, easy to use structures and data analysis tools. 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