Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
دوراتنا
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.
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Course by
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Self Paced
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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.
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Course by
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Self Paced
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18 ساعات
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الإنجليزية
Data Science Methods for Quality Improvement
Data analysis skills are widely sought by employers, both nationally and internationally. This specialization is ideal for anyone interested in data analysis for improving quality and processes in business and industry. The skills taught in this specialization have been used extensively to improve business performance, quality, and reliability. By completing this specialization, you will improve your ability to analyze data and interpret results as well as gain new skills, such as using RStudio and RMarkdown.
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Course by
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Self Paced
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الإنجليزية
Bayesian Statistics: Capstone Project
This is the capstone project for UC Santa Cruz's Bayesian Statistics Specialization. It is an opportunity for you to demonstrate a wide range of skills and knowledge in Bayesian statistics and to apply what you know to real-world data. You will review essential concepts in Bayesian statistics with lecture videos and quizzes, and you will perform a complex data analysis and compose a report on your methods and results.
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Course by
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12 ساعات
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الإنجليزية
Global Disease Masterclass: Global Disease Distribution
The Global Diseases Masterclass is part of the full-degree Masters of Public Health that the School of Public Health. By the end of this specialisation, our aim is that students will be able to critically apply epidemiological concepts to major global diseases and be able to appraise and recommend policy options to combat them. Global Diseases Masterclass: Global Disease Distribution In this course, we will introduce students to the most important trends and pattern in health and disease on a global scale.
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Course by
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Self Paced
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13 ساعات
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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.
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Course by
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32 ساعات
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الإنجليزية
What are the Chances? Probability and Uncertainty in Statistics
This course focuses on how analysts can measure and describe the confidence they have in their findings. The course begins with an overview of the key probability rules and concepts that govern the calculation of uncertainty measures. We’ll then apply these ideas to variables (which are the building blocks of statistics) and their associated probability distributions. The second half of the course will delve into the computation and interpretation of uncertainty. We’ll discuss how to conduct a hypothesis test using both test statistics and confidence intervals.
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Course by
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Self Paced
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11 ساعات
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الإنجليزية
The Data Driven Manager
In the Data Driven Manager specialization, you will learn how to first understand the type of data that you have (or want to generate), then describe it with numbers and graphs to communicate with your audience. You will practice using probability and distributions to understand the underlying nature of your data to make decisions and solve problems in a way that increases the likelihood of a desired outcome. You will learn the steps to create a plan to answer business and engineering questions and reduce risk when making decisions.
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Course by
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Self Paced
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الإنجليزية
Clinical Data Science
Are you interested in how to use data generated by doctors, nurses, and the healthcare system to improve the care of future patients? If so, you may be a future clinical data scientist! This specialization provides learners with hands on experience in use of electronic health records and informatics tools to perform clinical data science.
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Course by
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Self Paced
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الإنجليزية
Survey Data Collection and Analytics
This specialization covers the fundamentals of surveys as used in market research, evaluation research, social science and political research, official government statistics, and many other topic domains.
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Course by
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Self Paced
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الإنجليزية
Hypothesis Testing in R
Welcome to this project-based course Hypothesis Testing in R. In this project, you will learn how to perform extensive hypothesis tests for one and two samples in R.
By the end of this 2-hour long project, you will understand the rationale behind performing hypothesis testing. Also, you will learn how to perform hypothesis tests for proportions and means. By extension, you will learn how to perform a hypothesis test for means of matched or paired samples in R.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Effective Communication Capstone Project
In the Effective Communication Capstone learners apply the lessons of Business Writing, Graphic Design, and Successful Presentation to create a portfolio of work that represents their mastery of writing, design, and speaking and that expresses their personal brand. The portfolio includes three individual elements—a written memo, a slide deck, and a presentation—integrated around a single topic. We provide the elements for a basic capstone, but we also invite our learners to create their own project if they so choose.
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Course by
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Self Paced
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14 ساعات
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الإنجليزية
Python and Machine-Learning for Asset Management with Alternative Data Sets
Over-utilization of market and accounting data over the last few decades has led to portfolio crowding, mediocre performance and systemic risks, incentivizing financial institutions which are looking for an edge to quickly adopt alternative data as a substitute to traditional data. This course introduces the core concepts around alternative data, the most recent research in this area, as well as practical portfolio examples and actual applications.
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Course by
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Self Paced
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21 ساعات
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الإنجليزية
Scatter Plot for Data Scientists & Big Data Analysts-Visuals
This project gives you easy access to the invaluable learning techniques used by experts for visualization in statistics. We’ll learn about how to use wolfram language to draw curve in easiest way. We’ll also cover illustration and best practices shown by research to be most effective in helping you master plotting curves.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
How To Create Effective Metrics
By the end of this project, you will be able to create effective metrics for a business. You will learn what metrics are, how to create benchmarks, and how to build a system for sharing and evaluating metrics. Excel is a great tool to use if you have plans to adopt a data-driven approach to making business decisions. We will be sharpening our data analysis tools in Excel during this project.
This is a great tool to use if you have plans to use data, analytics, and or metrics to improve your business functions and decision making.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Using Descriptive Statistics to Analyze Data in R
By the end of this project, you will create a data quality report file (exported to Excel in CSV format) from a dataset loaded in R, a free, open-source program that you can download. You will learn how to use the following descriptive statistical metrics in order to describe a dataset and how to calculate them in basic R with no additional libraries.
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Course by
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Self Paced
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3 ساعات
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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
Predictive Modelling with Azure Machine Learning Studio
In this project, we will use Azure Machine Learning Studio to build a predictive model without writing a single line of code! Specifically, we will predict flight delays using weather data provided by the US Bureau of Transportation Statistics and the National Oceanic and Atmospheric Association (NOAA). You will be provided with instructions on how to set up your Azure Machine Learning account with $200 worth of free credit to get started with running your experiments!
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Topics in Applied Econometrics
In this course, you will discover models and approaches that are designed to deal with challenges raised by the empirical econometric modelling and particular types of data. You will: – Explore the motivations of each approach by means of graphs, preliminary statistics and presentation of economic theories – Discuss the problem of identification of the parameters, and how to address this problem by modelling simultaneous equations and causality in economics.
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Course by
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Self Paced
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28 ساعات
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الإنجليزية
Working with Objects in C++
This course is the fourth of five courses aiming to help you to become confident working in the object-oriented paradigm in the C++ language. This specialisation is for individuals who want to learn about objected oriented programming. It's an all-in-one package that will take you from the very fundamentals of C++, all the way to building a crypto-currency exchange platform. During the five courses, you will work with the instructor on a single project: a crypto-currency exchange platform.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
SQL for Data Science Capstone Project
Data science is a dynamic and growing career field that demands knowledge and skills-based in SQL to be successful. This course is designed to provide you with a solid foundation in applying SQL skills to analyze data and solve real business problems. Whether you have successfully completed the other courses in the Learn SQL Basics for Data Science Specialization or are taking just this course, this project is your chance to apply the knowledge and skills you have acquired to practice important SQL querying and solve problems with data.
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Course by
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Self Paced
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35 ساعات
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الإنجليزية
Generalized Linear Models and Nonparametric Regression
In the final course of the statistical modeling for data science program, learners will study a broad set of more advanced statistical modeling tools. Such tools will include generalized linear models (GLMs), which will provide an introduction to classification (through logistic regression); nonparametric modeling, including kernel estimators, smoothing splines; and semi-parametric generalized additive models (GAMs). Emphasis will be placed on a firm conceptual understanding of these tools.
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Course by
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Self Paced
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42 ساعات
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الإنجليزية
Math Prep: College & Work Ready
This MOOC will cover four main categories: Number Sense, Elementary Algebra, Intermediate Algebra, and Geometry and Statistics. The purpose of this course is to review and practice key concepts to prepare learners for college and the workforce. This course will help learners review and practice key concepts in preparation for the math portion of the Texas Success Initiative Assessment 2.0 (TSI2). The TSI2 is a series of placement tests for learners enrolling in public universities in Texas.
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Course by
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Self Paced
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35 ساعات
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الإنجليزية
Evaluating Problems
The second course of the specialization EVALUATING PROBLEMS will show you how humans think and how to utilize different disciplinary approaches to tackle problems more effectively. It advances your knowledge of your own field by teaching you to look at it in new ways. EVALUATING PROBLEMS is constructed in the following way: Week I. “Thinking about Thinking” – How problem solving evolved in nature, how the mechanics of our brains work, and the psychological biases that can emerge when we think. Week II.
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Course by
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Self Paced
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16 ساعات
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الإنجليزية
Analyze Data in Azure ML Studio
Did you know that you can use Azure Machine Learning to help you analyze data? In this 1-hour project-based course, you will learn how to display descriptive statistics of a dataset, measure relationships between variables and visualize relationships between variables. To achieve this, we will use one example diabetes data.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية