Was Sie vorher wissen sollten
bevor Sie beginnen

Beginnt 4 June 2026 13:16

Endet 4 June 2026

00 Tage
00 Stunden
00 Minuten
00 Sekunden
course image

AI-Powered Data Analysis with Microsoft Copilot

Master AI-powered data analysis using Microsoft Copilot to transform raw data into insights, build dashboards, and automate workflows—no prior experience needed.
via Coursera

2868 Kurse


5 hours 21 minutes

Optionales Upgrade verfügbar

Anfänger

Lernen Sie in Ihrem eigenen Tempo

Paid Course

Optionales Upgrade verfügbar

Übersicht

Master the essential skills of data analysis and visualization, even with no prior experience. This course teaches you how to leverage Microsoft Copilot's AI-powered capabilities to transform raw data into actionable insights and compelling visualizations.

Through real-world case studies in financial analysis and business analytics, you'll learn to interpret trends, create professional dashboards, and make data-driven decisions with confidence. Whether you're looking to advance your career, understand your business better, or simply gain a valuable new skill, this course accelerates your learning by combining Copilot's intelligent features with proven analytical techniques.

You'll discover how AI can dramatically reduce the time spent on routine tasks, allowing you to focus on strategic thinking and decision-making. By the end of this course, you'll be equipped to analyze complex datasets, visualize patterns that matter, and communicate insights that drive real business results—all while building the confidence to tackle data challenges independently.

Lehrplan

  • Introduction to AI-Driven Analytics and Course Overview
  • This introductory module establishes the foundational principles of artificial intelligence and machine learning, offering a comprehensive architectural overview of Microsoft Copilot and its integration into modern business intelligence workflows.
  • Data Integration and System Configuration for AI Assistants
  • You will explore advanced methodologies for structuring scalable data pipelines, utilizing Microsoft Copilot to automate Power Query M code generation and optimize raw data transformation processes.
  • Preprocessing Methodologies: Data Cleansing and Outlier Detection
  • This section provides rigorous statistical approaches for anomaly detection and data standardization, empowering learners to leverage AI-driven prompt engineering for organizing and refining complex datasets.
  • Exploratory Data Analysis via Natural Language Processing and Statistics
  • Learners will master the application of natural language processing to conduct comprehensive exploratory data analysis, generating descriptive statistics, correlation matrices, and hypothesis tests to validate business assumptions.
  • Advanced Data Visualization and AI-Generated Graphical Insights
  • This module delves into the psychological and technical principles of data visualization, teaching students how to generate, style, and export dynamic AI-powered charts and dashboards within Microsoft Excel.
  • Strategic Application of Data Insights in Project Management
  • Focusing on operational efficiency, this concluding module demonstrates how to deploy Microsoft Copilot across Word, Excel, and Outlook to automate project forecasting, financial modeling, and performance reporting.

Unterrichtet von

Anton Voroniuk


Fachgebiete

Artificial Intelligence