دوراتنا

Judgmental Business Forecasting in Excel

Judgmental Business Forecasting in Excel

In this course, we extend your business forecasting expertise from the first two courses of our Business Forecasting Specialisation on Time Series Models and Regression Models. We will explore the role of judgmental forecasting, when more quantitative forecasting methods have limitations, and we need to generate further business insights. We will be exploring some structured methodologies to create judgmental business forecasts using Business Indicators, Subjective Assessment Methods, and Exploratory Methods.

  • مقدم بواسطة
  • التعلم الذاتي
  • 10 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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AI and Climate Change

AI and Climate Change

In this course, you’ll start with a review of the mechanisms behind anthropogenic climate change and its impact on global temperatures and weather patterns. You will work through two case studies, one using time series analysis for wind power forecasting and another using computer vision for biodiversity monitoring. Both case studies are examples of where AI techniques can be part of the solution when it comes to the mitigation of and adaptation to climate change.

  • مقدم بواسطة
  • التعلم الذاتي
  • 15 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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Applying Data Analytics in Finance

Applying Data Analytics in Finance

This course introduces an overview of financial analytics. You will learn why, when, and how to apply financial analytics in real-world situations. You will explore techniques to analyze time series data and how to evaluate the risk-reward trade off expounded in modern portfolio theory. While most of the focus will be on the prices, returns, and risk of corporate stocks, the analytical techniques can be leverages in other domains.

  • مقدم بواسطة
  • التعلم الذاتي
  • 24 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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Predict Future Product Prices Using Facebook Prophet

Predict Future Product Prices Using Facebook Prophet

In this 1-hour long project-based course, you will be able to:
- Understand the theory and intuition behind Facebook times series forecasting tool
- Import Key libraries, dataset and visualize dataset
- Build a time series forecasting model using Facebook Prophet to predict future product prices
- Compile and fit time series forecasting model to training data
- Assess trained model performance
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.

  • مقدم بواسطة
  • التعلم الذاتي
  • 3 ساعات
  • language الإنجليزية
Introduction to Predictive Modeling

Introduction to Predictive Modeling

Welcome to Introduction to Predictive Modeling, the first course in the University of Minnesota’s Analytics for Decision Making specialization. This course will introduce to you the concepts, processes, and applications of predictive modeling, with a focus on linear regression and time series forecasting models and their practical use in Microsoft Excel.

  • مقدم بواسطة
  • التعلم الذاتي
  • 12 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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Intro to Time Series Analysis in R

Intro to Time Series Analysis in R

In this 2 hour long project-based course, you will learn the basics of time series analysis in R. By the end of this project, you will understand the essential theory for time series analysis and have built each of the major model types (Autoregressive, Moving Average, ARMA, ARIMA, and decomposition) on a real world data set to forecast the future. We will go over the essential packages and functions in R as well to make time series analysis easy.

  • مقدم بواسطة
  • التعلم الذاتي
  • 3 ساعات
  • language الإنجليزية
Specialized Models: Time Series and Survival Analysis

Specialized Models: Time Series and Survival Analysis

This course introduces you to additional topics in Machine Learning that complement essential tasks, including forecasting and analyzing censored data. You will learn how to find analyze data with a time component and censored data that needs outcome inference. You will learn a few techniques for Time Series Analysis and Survival Analysis.

  • مقدم بواسطة
  • التعلم الذاتي
  • 11 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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Global Statistics - Composite Indices for International Comparisons

Global Statistics - Composite Indices for International Comparisons

The number of composite indices that are constructed and used internationally is growing very fast; but whilst the complexity of quantitative techniques has increased dramatically, the education and training in this area has been dragging and lagging behind. As a consequence, these simple numbers, expected to synthesize quite complex issues, are often presented to the public and used in the political debate without proper emphasis on their intrinsic limitations and correct interpretations.

  • مقدم بواسطة
  • التعلم الذاتي
  • 16 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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Time Series Data Visualization And Analysis Techniques

Time Series Data Visualization And Analysis Techniques

By the end of this project we will learn how to analyze time series data. We are going to talk about different visualization techniques for time series datasets and we are going to compare them in terms of the tasks that we can solve using each of them. Tasks such as outlier detection, Key moments detection and overall tren

  • مقدم بواسطة
  • التعلم الذاتي
  • 3 ساعات
  • language الإنجليزية
Modeling Time Series and Sequential Data

Modeling Time Series and Sequential Data

In this course you learn to build, refine, extrapolate, and, in some cases, interpret models designed for a single, sequential series. There are three modeling approaches presented. The traditional, Box-Jenkins approach for modeling time series is covered in the first part of the course. This presentation moves students from models for stationary data, or ARMA, to models for trend and seasonality, ARIMA, and concludes with information about specifying transfer function components in an ARIMAX, or time series regression, model. A Bayesian approach to modeling time series is considered next.

  • مقدم بواسطة
  • التعلم الذاتي
  • 11 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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Introduction to Vertex Forecasting and Time Series in Practice

Introduction to Vertex Forecasting and Time Series in Practice

This course is an introduction to building forecasting solutions with Google Cloud. You start with sequence models and time series foundations. You then walk through an end-to-end workflow: from data preparation to model development and deployment with Vertex AI. Finally, you learn the lessons and tips from a retail use case and apply the knowledge by building your own forecasting models.

  • مقدم بواسطة
  • التعلم الذاتي
  • 15 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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Creating Features for Time Series Data

Creating Features for Time Series Data

This course focuses on data exploration, feature creation, and feature selection for time sequences. The topics discussed include binning, smoothing, transformations, and data set operations for time series, spectral analysis, singular spectrum analysis, distance measures, and motif analysis. In this course you learn to perform motif analysis and implement analyses in the spectral or frequency domain.

  • مقدم بواسطة
  • التعلم الذاتي
  • 8 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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Compare time series predictions of COVID-19 deaths

Compare time series predictions of COVID-19 deaths

By the end of this project, you will learn how to perform the entire time series analysis workflow for the daily COVID-19 deaths. This workflow includes the following steps: how to examine time series data, prepare the data for analysis, train different models and test their performance, and finally use the models to forecast into the future. You will learn how to visualize data using the matplotlib library, extract features from a time series data set, and perform data splitting and normalization. You will create time series analysis models using the python programming language.

  • مقدم بواسطة
  • التعلم الذاتي
  • 2 ساعات
  • language الإنجليزية
Policy Analysis Using Interrupted Time Series

Policy Analysis Using Interrupted Time Series

A comprehensive course on conducting and presenting policy evaluations using interrupted time series analysis.

  • مقدم بواسطة
  • التعلم الذاتي
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الاحترافية @ AED 149 + VAT
  • الباقة الإبتدائية @ AED 99 + VAT
اعرف المزيد
Machine Learning for Accounting with Python

Machine Learning for Accounting with Python

This course, Machine Learning for Accounting with Python, introduces machine learning algorithms (models) and their applications in accounting problems. It covers classification, regression, clustering, text analysis, time series analysis. It also discusses model evaluation and model optimization. This course provides an entry point for students to be able to apply proper machine learning models on business related datasets with Python to solve various problems. Accounting Data Analytics with Python is a prerequisite for this course.

  • مقدم بواسطة
  • التعلم الذاتي
  • 64 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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The Econometrics of Time Series Data

The Econometrics of Time Series Data

In this course, you will look at models and approaches that are designed to deal with challenges raised by time series data. The discussion covers the motivation for the use of particular models and the description of the characteristics of time series data, with a special attention raised to the potential memory. You will: – Discuss time series models, that refer to data that have been collected over a period on one or more variables for the same individual.

  • مقدم بواسطة
  • التعلم الذاتي
  • 31 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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Analyzing Time Series and Sequential Data

Analyzing Time Series and Sequential Data

Using SAS Visual Forecasting and other SAS tools, you will learn to explore time series, create and select features, build and manage a large-scale forecasting system, and use a variety of models to identify, estimate and forecast signal components of interest.

  • مقدم بواسطة
  • التعلم الذاتي
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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Practical Time Series Analysis

Practical Time Series Analysis

Welcome to Practical Time Series Analysis! Many of us are "accidental" data analysts. We trained in the sciences, business, or engineering and then found ourselves confronted with data for which we have no formal analytic training. This course is designed for people with some technical competencies who would like more than a "cookbook" approach, but who still need to concentrate on the routine sorts of presentation and analysis that deepen the understanding of our professional topics.

  • مقدم بواسطة
  • التعلم الذاتي
  • 26 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
اعرف المزيد
Excel Regression Models for Business Forecasting

Excel Regression Models for Business Forecasting

This course allows learners to explore Regression Models in order to utilise these models for business forecasting. Unlike Time Series Models, Regression Models are causal models, where we identify certain variables in our business that influence other variables. Regressions model this causality, and then we can use these models in order to forecast, and then plan for our business' needs. We will explore simple regression models, multiple regression models, dummy variable regressions, seasonal variable regressions, as well as autoregressions.

  • مقدم بواسطة
  • التعلم الذاتي
  • 9 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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Excel Skills for Business Forecasting

Excel Skills for Business Forecasting

The current state of the world makes business forecasting even more fundamental to the operation of institutions.

  • مقدم بواسطة
  • التعلم الذاتي
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
اعرف المزيد
Accounting Data Analytics

Accounting Data Analytics

This specialization develops learners’ analytics mindset and knowledge of data analytics tools and techniques. Specifically, this specialization develops learners' analytics skills by first introducing an analytic mindset, data preparation, visualization, and analysis using Excel. Next, this specialization develops learners' skills of using Python for data preparation, data visualization, data analysis, and data interpretation and the ability to apply these skills to issues relevant to accounting.

  • مقدم بواسطة
  • التعلم الذاتي
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
اعرف المزيد
Time Series Analysis (ARIMA) with R

Time Series Analysis (ARIMA) with R

In this project, you will learn to conduct a thorough analysis of a time series data using ARIMA. The project explains the basic concepts of time series analysis and illustrates the same with hands-on activity on R Studio. It describes the types of time series data and its distinct components. The project covers how to conduct diagnostic tests to check for core assumptions of ARIMA, evaluating model process and orders from ACF, PACF graphs. Finally, it derives best fit model to forecast future values.

  • مقدم بواسطة
  • التعلم الذاتي
  • 3 ساعات
  • language الإنجليزية
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.

  • مقدم بواسطة
  • التعلم الذاتي
  • 66 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الاحترافية @ AED 149 + VAT
  • الباقة الإبتدائية @ AED 99 + VAT
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Reinforcement Learning for Trading Strategies

Reinforcement Learning for Trading Strategies

In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. You will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied to time series data.

  • مقدم بواسطة
  • التعلم الذاتي
  • 12 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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Demand Forecasting Using Time Series

Demand Forecasting Using Time Series

This course is the second in a specialization for Machine Learning for Supply Chain Fundamentals. In this course, we explore all aspects of time series, especially for demand prediction. We'll start by gaining a foothold in the basic concepts surrounding time series, including stationarity, trend (drift), cyclicality, and seasonality. Then, we'll spend some time analyzing correlation methods in relation to time series (autocorrelation). In the 2nd half of the course, we'll focus on methods for demand prediction using time series, such as autoregressive models.

  • مقدم بواسطة
  • التعلم الذاتي
  • 9 ساعات
  • language الإنجليزية
الاشتراك الشهري
متضمن في
  • الباقة الإبتدائية @ AED 99 + VAT
  • الباقة الاحترافية @ AED 149 + VAT
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