دوراتنا

Risk Management

Risk Management

This 4-course Specialization from the New York Institute of Finance (NYIF) is intended for STEM undergraduates, finance practitioners, bank and investment managers, business managers, regulators, and policymakers. This Specialization will teach you how to measure, assess, and manage risk in your organization.

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  • language الإنجليزية
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Computer Communications

Computer Communications

This specialization is developed for seniors and fresh graduate students to understand fundamental network architecture concepts and their impacts on cyber security, to develop skills and techniques required for network protocol design, and prepare for a future of constant change through exposure to network design alternatives. Students will require a prior knowledge of C programming, an understanding of math probability and a computer science background is a plus.

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  • language الإنجليزية
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Operational Risk Management: Frameworks & Strategies

Operational Risk Management: Frameworks & Strategies

In the final course from the Risk Management specialization, you will be introduced to the different roles in risk governance and the benefits of establishing an operational risk management program at your own workplace. This course will highlight key elements of an Operational Risk Management framework and help you identify the appropriate elements to incorporate in your own program.

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  • 7 ساعات
  • language الإنجليزية
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Econometrics: Methods and Applications

Econometrics: Methods and Applications

Welcome! Do you wish to know how to analyze and solve business and economic questions with data analysis tools? Then Econometrics by Erasmus University Rotterdam is the right course for you, as you learn how to translate data into models to make forecasts and to support decision making. * What do I learn? When you know econometrics, you are able to translate data into models to make forecasts and to support decision making in a wide variety of fields, ranging from macroeconomics to finance and marketing.

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  • 66 ساعات
  • language الإنجليزية
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Business Statistics and Analysis

Business Statistics and Analysis

The Business Statistics and Analysis Specialization is designed to equip you with a basic understanding of business data analysis tools and techniques. Informed by our world-class Data Science master's and PhD course material, you’ll master essential spreadsheet functions, build descriptive business data measures, and develop your aptitude for data modeling. You’ll also explore basic probability concepts, including measuring and modeling uncertainty, and you’ll use various data distributions, along with the Linear Regression Model, to analyze and inform business decisions.

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  • language الإنجليزية
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TensorFlow 2 for Deep Learning

TensorFlow 2 for Deep Learning

This Specialization is intended for machine learning researchers and practitioners who are seeking to develop practical skills in the popular deep learning framework TensorFlow. The first course of this Specialization will guide you through the fundamental concepts required to successfully build, train, evaluate and make predictions from deep learning models, validating your models and including regularisation, implementing callbacks, and saving and loading models. The second course will deepen your knowledge and skills with TensorFlow, in order to develop fully customised deep learning mode

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  • language الإنجليزية
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Statistical Analysis with R for Public Health

Statistical Analysis with R for Public Health

Statistics are everywhere. The probability it will rain today. Trends over time in unemployment rates. The odds that India will win the next cricket world cup. In sports like football, they started out as a bit of fun but have grown into big business. Statistical analysis also has a key role in medicine, not least in the broad and core discipline of public health. In this specialisation, you’ll take a peek at what medical research is and how – and indeed why – you turn a vague notion into a scientifically testable hypothesis.

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  • language الإنجليزية
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Introduction to Computational Statistics for Data Scientists

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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  • التعلم الذاتي
  • language الإنجليزية
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Self-Driving Cars

Self-Driving Cars

Be at the forefront of the autonomous driving industry. With market researchers predicting a $42-billion market and more than 20 million self-driving cars on the road by 2025, the next big job boom is right around the corner. This Specialization gives you a comprehensive understanding of state-of-the-art engineering practices used in the self-driving car industry.

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  • التعلم الذاتي
  • language الإنجليزية
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Bayesian Statistics

Bayesian Statistics

This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm. The course will apply Bayesian methods to several practical problems, to show end-to-end Bayesian analyses that move from framing the question to building models to eliciting prior probabilities to implementing in R (free statistical software) the final posterior distribution.

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Introduction to Topic Modelling in R

Introduction to Topic Modelling in R

By the end of this project, you will know how to load and pre-process a data set of text documents by converting the data set into a document feature matrix and reducing it’s dimensionality. You will also know how to run an unsupervised machine learning LDA topic model (Latent Dirichlet Allocation). You will know how to plot the change in topics over time as well as explore the distribution of topic probability in each document.

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  • التعلم الذاتي
  • 3 ساعات
  • language الإنجليزية
Advanced Statistics for Data Science

Advanced Statistics for Data Science

Fundamental concepts in probability, statistics and linear models are primary building blocks for data science work. Learners aspiring to become biostatisticians and data scientists will benefit from the foundational knowledge being offered in this specialization. It will enable the learner to understand the behind-the-scenes mechanism of key modeling tools in data science, like least squares and linear regression. This specialization starts with Mathematical Statistics bootcamps, specifically concepts and methods used in biostatistics applications.

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  • language الإنجليزية
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Mindware: Critical Thinking for the Information Age

Mindware: Critical Thinking for the Information Age

Most professions these days require more than general intelligence. They require in addition the ability to collect, analyze and think about data. Personal life is enriched when these same skills are applied to problems in everyday life involving judgment and choice. This course presents basic concepts from statistics, probability, scientific methodology, cognitive psychology and cost-benefit theory and shows how they can be applied to everything from picking one product over another to critiquing media accounts of scientific research.

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  • 13 ساعات
  • language الإنجليزية
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Fat Chance: Probability from the Ground Up

Fat Chance: Probability from the Ground Up

Increase your quantitative reasoning skills through a deeper understanding of probability and statistics.

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  • 30
  • language الإنجليزية
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AI Workflow: Feature Engineering and Bias Detection

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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  • 12 ساعات
  • language الإنجليزية
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Sports Performance Analytics

Sports Performance Analytics

Sports analytics has emerged as a field of research with increasing popularity propelled, in part, by the real-world success illustrated by the best-selling book and motion picture, Moneyball.

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  • language الإنجليزية
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Data Literacy

Data Literacy

This specialization is intended for professionals seeking to develop a skill set for interpreting statistical results. Through four courses and a capstone project, you will cover descriptive statistics, data visualization, measurement, regression modeling, probability and uncertainty which will prepare you to interpret and critically evaluate a quantitative analysis.

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  • language الإنجليزية
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Computer Vision Basics

Computer Vision Basics

By the end of this course, learners will understand what computer vision is, as well as its mission of making computers see and interpret the world as humans do, by learning core concepts of the field and receiving an introduction to human vision capabilities. They are equipped to identify some key application areas of computer vision and understand the digital imaging process. The course covers crucial elements that enable computer vision: digital signal processing, neuroscience and artificial intelligence.

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  • 13 ساعات
  • language الإنجليزية
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Pre-MBA Statistics

Pre-MBA Statistics

Welcome to the Pre-MBA Statistics course! By the end of this course, you will be able to describe how statistics can be used to summarize, analyze, and interpret data. This course introduces you to some aspects of descriptive and inferential statistics. You will learn to distinguish between various data types and describe the operations that you can execute with each type of data and the right tools to use. The course also discusses the concepts of probability, which form the backbone of statistical analysis.

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  • 24 ساعات
  • language الإنجليزية
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Statistics for Data Science with Python

Statistics for Data Science with Python

This Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and procedures used for data analysis. After completing this course you will have practical knowledge of crucial topics in statistics including - data gathering, summarizing data using descriptive statistics, displaying and visualizing data, examining relationships between variables, probability distributions, expected values, hypothesis testing, introduction to ANOVA (analysis of variance), regression and correlation analysis.

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  • 14 ساعات
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Probability Theory

Probability Theory

This course provides an introduction to probability theory. You will encounter discrete and continuous random variables and learn in which situations they appear, what their properties are and how they interact.

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  • 23
  • language الإنجليزية
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MathTrackX: Probability

MathTrackX: Probability

Understand probability and how it manifests in the world around us.

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  • 16
  • language الإنجليزية
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Statistics 2 Part 1: Probability and Distribution Theory

Statistics 2 Part 1: Probability and Distribution Theory

The third in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.

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Statistics 1 Part 1: Introductory statistics, probability and estimation

Statistics 1 Part 1: Introductory statistics, probability and estimation

The first in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.

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  • language الإنجليزية
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Introduction to Probability

Introduction to Probability

Learn probability, an essential language and set of tools for understanding data, randomness, and uncertainty.

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  • 30
  • language الإنجليزية
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