دوراتنا

Forecasting Techniques for Slow and Rapidly Changing Demand

Master quantitative, judgmental and causal models used to forecast seasonal, intermittent, and new product future demand. Choose the right forecasting method for all kinds of demand patterns and sales data. Learn how to deal with randomness and low forecastability; missing data, outliers, and overfitting. Separate forecasting myths from reality and mitigate the risk of inaccurate forecasts.

Part of the ISCEA CFDP - Certified Forecaster and Demand Planner - Internationally Recognized Certificate.

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• الإنجليزية

Data Processing and Manipulation

The "Data Processing and Manipulation" course provides students with a comprehensive understanding of various data processing and manipulation concepts and tools. Participants will learn how to handle missing values, detect outliers, perform sampling and dimension reduction, apply scaling and discretization techniques, and explore data cube and pivot table operations. This course equips students with essential skills for efficiently preparing and transforming data for analysis and decision-making. Learning Objectives: 1.

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• التعلم الذاتي
• 29 ساعات
• 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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• التعلم الذاتي
• 3 ساعات
• الإنجليزية

Conditional Formatting, Tables and Charts in Microsoft Excel

In this project, you will learn how to analyze data and identify trends using a variety of tools in Microsoft Excel. Conditional formatting and charts are two tools that focus on highlighting and representing data in a visual form. With conditional formatting, you can define rules to highlight cells using a range of color scales and icons and to help you analyze data and identify trends or outliers. You will then use PivotTables to create summaries of the data that focuses on specific relationships which you will represent as a line chart and column chart.

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• التعلم الذاتي
• 3 ساعات
• الإنجليزية

Go Beyond the Numbers: Translate Data into Insights

This is the third of seven courses in the Google Advanced Data Analytics Certificate. In this course, you’ll learn how to find the story within data and tell that story in a compelling way. You'll discover how data professionals use storytelling to better understand their data and communicate key insights to teammates and stakeholders. You'll also practice exploratory data analysis and learn how to create effective data visualizations.

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• التعلم الذاتي
• 33 ساعات
• الإنجليزية

Association Rules Analysis

The "Association Rules and Outliers Analysis" course introduces students to fundamental concepts of unsupervised learning methods, focusing on association rules and outlier detection. Participants will delve into frequent patterns and association rules, gaining insights into Apriori algorithms and constraint-based association rule mining. Additionally, students will explore outlier detection methods, with a deep understanding of contextual outliers.

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• التعلم الذاتي
• 23 ساعات
• الإنجليزية

Data Analysis with Python Project

The "Data Analysis Project" course empowers students to apply their knowledge and skills gained in this specialization to conduct a real-life data analysis project of their interest. Participants will explore various directions in data analysis, including supervised and unsupervised learning, regression, clustering, dimension reduction, association rules, and outlier detection. Throughout the modules, students will learn essential data analysis techniques and methodologies and embark on a journey from raw data to knowledge and intelligence.

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• التعلم الذاتي
• 18 ساعات
• الإنجليزية

Data Analytics en Power BI

Este proyecto es un curso práctico y efectivo para aprender todo lo que necesitas saber de Data Analytics en Power BI. Te permitirá aprender a realizar funciones analíticas de datos, a identificar outliers, a aplicar técnicas de clustering y series temporales, a analizar los quick insights y AI insights, entre otros.

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• التعلم الذاتي
• 3 ساعات
• الإسبانية

Basic Statistics in Python (Correlations and T-tests)

By the end of this project, you will learn how to use Python for basic statistics (including t-tests and correlations). We will learn all the important steps of analysis, including loading, sorting and cleaning data. In this course, we will use exploratory data analysis to understand our data and plot boxplots to visualize the data. Boxplots also allow us to investigate any outliers in our datasets. We will then learn how to examine relationships between the different data using correlations and scatter plots. Finally, we will compare data using t-tests.

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• التعلم الذاتي
• 3 ساعات
• الإنجليزية

Exploratory Data Analysis for Machine Learning

This first course in the IBM Machine Learning Professional Certificate introduces you to Machine Learning and the content of the professional certificate. In this course you will realize the importance of good, quality data.

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• 14 ساعات
• الإنجليزية

Fundamentals of Scalable Data Science

Apache Spark is the de-facto standard for large scale data processing. This is the first course of a series of courses towards the IBM Advanced Data Science Specialization. We strongly believe that is is crucial for success to start learning a scalable data science platform since memory and CPU constraints are to most limiting factors when it comes to building advanced machine learning models.\n\nIn this course we teach you the fundamentals of Apache Spark using python and pyspark.

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• 22 ساعات
• الإنجليزية

Machine Learning: Regression

Case Study - Predicting Housing Prices In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied.

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• التعلم الذاتي
• 22 ساعات
• الإنجليزية