К содержимому
learnspaceYOUR NEXT CHAPTER
ПРОСТРАНСТВО ОБУЧЕНИЯ
ГлавнаяКаталог курсовМоё обучениеCoursera

Знания без границ

Учитесь у лучших университетов и компаний мира.

Открыть Coursera
Интеграция
Пространство университета
Моё пространствоСтраница курса
↵
ЯЛичный кабинетСтудент
© 2026 LearnSpaceКаждый день — возможность узнать больше.Помощь
AI for Executives: The Basics · LearnSpace
Назад в каталог
courseraАнализ данных

AI for Executives: The Basics

Курс от Khalifa University
Начальный≈ 18.9 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

AI for Executives: The Basics gives managers a practical, non-technical introduction to artificial intelligence and machine learning for business decision-making. You’ll learn how AI fits into executive strategy, what ML models can and can’t do, and how to lead data-driven initiatives that create measurable value. Starting with the fundamentals, the course explains algorithms vs. models, core ML tasks, and the lifecycle for building and governing solutions. You’ll then design a data strategy—covering data quality, privacy, and responsible use—before applying techniques such as regression, decision trees, and modern large language models (LLMs) to real executive-level use cases. Finally, you’ll put it together by planning AI pipelines, evaluating model performance and non-functional properties, and knowing when to customize or reuse off-the-shelf models. Hands-on assignments use familiar tools and require no coding. By the end, you’ll be able to map business problems to the right AI approach, communicate with technical teams, and build an informed roadmap for adopting AI across your organization.

Навыки, которые вы освоите

Data QualityAI Product StrategyTransfer LearningData GovernancePredictive AnalyticsData ManagementApplied Machine LearningPredictive ModelingStatistical Machine LearningArtificial Intelligence and Machine Learning (AI/ML)AI EnablementModel TrainingData IntegrationData StrategyData LiteracyModel DeploymentMLOps (Machine Learning Operations)Decision IntelligenceData-Driven Decision-MakingModel Evaluation

Программа курса

5 модулей · 94 учебных материалов

01Module 1 - The Basics21 материалов

Lesson 1: Introduction to Decision Making

Introduction to the SpecializationВидеоIntroduction to Course OneВидеоGeneral Notions on Decision MakingВидеоBefore AI: Business Data Analysis by StatisticsВидео

Учитесь у экспертов

Prof. Ernesto Damiani

Преподаватель курса

AI for Executives: The Basics
В каталоге вашей программы

Инвестируйте в себя

Новые знания — в удобное для вас время.

Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 18.9 ч

5 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Испанский, Японский, Венгерский

Часть программы вашего университета
Before AI: Business Data Analysis by Statistics Key TopicsЧтение
Data Descriptive StatisticsВидео
Data Descriptive Statistics Key TopicsЧтение
Data Bivariate and Multivariate StatisticsВидео
Data Bivariate and Multivariate Statistics Key TopicsЧтение
Decision Making via Statistics and AlgorithmsВидео
Decision Making via Statistics and Algorithms Key TopicsЧтение
Decision Making via AIВидео
Decision Making via AI Key TopicsЧтение
Lab 1: Performing Basic Statistics Using Absenteeism DatasetЛабораторная
Google Sheets Output Assignment (Checker)Задание

Lesson 2: Introduction to Machine Learning

Introduction to Machine Learning (ML) TasksВидеоModel ValidationВидеоModel Validation Key TopicsЧтениеThe Machine Learning TasksВидеоThe Machine Learning Tasks Key TopicsЧтениеModule 1 QuizЗадание
02Module 2 - Building A Data Strategy9 материалов

Lesson 1: Managing data for AI

Introduction to Data Provisioning and ManagementВидеоData Strategy Objectives and Data PreparationВидеоData Strategy Objectives and Data Preparation Key TopicsЧтениеHow Data Lakes Support Business Ready AIВидеоDesigning the Data Architecture for Machine LearningВидеоBivariate Filtering Method and Data Improvement TechniquesВидеоBivariate Filtering Method and Data Improvement Techniques Key TopicsЧтениеLab 2: Improving Data Quality via Interpolation.ЛабораторнаяModule 2 QuizЗадание
03Module 3 - AI-Based Decision Making31 материалов

Lesson 1: Regression

Linear RegressionВидеоLinear Regression Key TopicsЧтениеLinear Regression Model SignificanceВидеоLinear Regression Model Significance Key TopicsЧтениеImproving the Quality of a Linear Regression ModelВидеоImproving the Quality of a Linear Regression Model Key TopicsЧтениеMultiple RegressionВидеоMultiple Regression Key TopicsЧтениеMultiple Regression Model SignificanceВидеоMultiple Regression Model Significance Key TopicsЧтениеInteractions Between Independent Variables in Multiple RegressionВидеоInteractions Between Independent Variables in Multiple Regression Key TopicsЧтениеLab 3: Building and Evaluating a Regression ModelЛабораторная

Lesson 2: Basic ML models

Decision Trees - Part 1ВидеоDecision Trees - Part 1 Key TopicsЧтениеDecision Trees - Part 2ВидеоDecision Trees - Part 2 Key TopicsЧтениеThe K-Nearest NeighborsВидеоThe K-Nearest Neighbors Key TopicsЧтение

Lesson 3: Language Models

The Fundamentals of Building Language ModelsВидеоThe Fundamentals of Building Language Models Key TopicsЧтениеTraining and Deploying Language ModelsВидеоTraining and Deploying Language Models Key TopicsЧтениеTechniques to Improve Language ModelsВидеоTechniques to Improve Language Models Key TopicsЧтение
04Module 4 - AI-Based Prediction and Classifications24 материалов

Lesson 1: Classification Problems in Business

Decision Tree InductionВидеоDecision Tree Induction Key TopicsЧтениеEntropy and Information Gain in Decision Tree InductionВидеоEntropy and Information Gain in Decision Tree Induction Key TopicsЧтениеInformation Gain for Continuous Value AttributesВидеоInformation Gain for Continuous Value Attributes Key TopicsЧтениеGini Index and Impurity ReductionВидеоGini Index and Impurity Reduction Key TopicsЧтение

Lesson 2: Classifier Models

Introduction to Deep LearningВидеоIntroduction to Deep Learning Key TopicsЧтениеConvolutional Neural NetworksВидеоConvolutional Neural Networks Key TopicsЧтениеHow Convolution WorksВидеоHow Convolution Works Key TopicsЧтение
05Module 5 - Putting It All Together9 материалов

Lesson 1: Design of ML Pipelines

Wrap Up Executive SummaryВидеоWrap up Executive Summary Key TopicsЧтениеAI Key Success FactorsВидеоAI Key Success Factors Key TopicsЧтениеDesign of AI-ML PipelinesВидеоPublicly Available ModelsЧтениеRetraining and MaintenanceЧтениеModule 5 QuizЗаданиеCourse One ConclusionВидео
Support Vector Machines (SVM)Видео
Support Vector Machines (SVM) Key TopicsЧтение
Improving The Generalization Capabilities of Language ModelsВидео
Improving The Generalization Capabilities of Language Models Key TopicsЧтение
Lab 4: LLM: How Does it Work?Лабораторная
Module 3 QuizЗадание
Convolutional vs Fully Connected ArchitecturesВидео
Convolutional vs Fully Connected Architectures Key TopicsЧтение
CNN for Tabular DataВидео
CNN for Tabular Data Key TopicsЧтение
Introduction to AutoencodersВидео
Introduction to Autoencoders Key TopicsЧтение
Introduction to Time-Series Prediction ModelsЧтение
Time Series DataВидео
Time Series Data Key TopicsЧтение
Module 4 QuizЗадание