How is AI used in data analytics?

AI helps analysts automate reporting, identify trends, detect anomalies, improve forecasting accuracy, and process large datasets more efficiently.

Is this course suitable for non-technical learners?

Yes. It is designed for both technical and non-technical professionals.

Will I learn how AI tools support analytical workflows?

Yes. The course explains how AI tools support reporting automation, forecasting, trend analysis, anomaly detection, and operational insights.

Can AI improve reporting and forecasting accuracy?

Yes. AI helps reduce manual effort, accelerate reporting cycles, and improve forecasting quality through predictive insights and pattern recognition.

What industries use AI-powered data analytics?

AI-powered analytics is widely used across finance, healthcare, retail, telecom, manufacturing, and enterprise operations.

Is coding required for this course?

No coding is required. The course focuses on practical understanding and business applications.

How will this course help my career?

This course helps you build practical AI analytics skills that are increasingly valuable across industries using AI-powered reporting, forecasting, and business intelligence tools.

What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

AI For Data Analysts

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AI For Data Analysts

Dozent: AI CERTs Team

Bei enthalten

Mehr erfahren

7 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

7 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

Apply AI Across Data Analytics Functions
Use AI tools to support reporting, forecasting, trend analysis, and business intelligence activities
Analyze Data Faster and More Accurately
Identify patterns, detect anomalies, and interpret large datasets more efficiently using AI
Strengthen Forecasting and Reporting Quality
Apply AI-driven insights to improve forecasting accuracy and accelerate reporting processes
Support Smarter Business Insights
Use AI-powered analytics to generate clearer insights and contribute to faster strategic decisions

Kompetenzen, die Sie erwerben

Kategorie: Information Privacy
Kategorie: Advanced Analytics
Kategorie: Business Analytics
Kategorie: Business Intelligence
Kategorie: Predictive Analytics
Kategorie: Operational Efficiency
Kategorie: Financial Forecasting
Kategorie: Operational Performance Management
Kategorie: Anomaly Detection
Kategorie: Forecasting
Kategorie: Data Literacy
Kategorie: Business Reporting
Kategorie: Data Collection
Kategorie: Operational Analysis
Kategorie: AI Enablement
Kategorie: Data Preprocessing

Wichtige Details

Zertifikat zur Vorlage

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Kürzlich aktualisiert!

November 2025

Bewertungen

7 Aufgaben

Unterrichtet in Englisch

Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.

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In diesem Kurs gibt es 7 Module

Learn how to apply AI in data analysis to uncover insights faster, improve reporting accuracy, and support smarter business outcomes. For example, AI can help analysts identify customer behavior patterns, automate repetitive reporting tasks, detect anomalies in financial records, and improve forecasting speed across large datasets.

This AI for Data Analysts course explains how artificial intelligence is used across data preparation, visualization, forecasting, reporting, and predictive analytics functions. Designed for beginners, it helps you build practical AI knowledge without requiring advanced coding or technical expertise. You’ll explore how AI supports trend analysis, dashboard reporting, business intelligence, and forecasting activities across modern enterprises. The course focuses on practical applications that help reduce manual effort, accelerate reporting cycles, and improve analytical accuracy in real business environments. Through guided examples, you’ll learn how to identify opportunities for automation and apply AI-driven insights more effectively. Practical scenarios such as customer trend analysis, sales forecasting, anomaly detection, reporting automation, and operational performance tracking make learning easier to apply across industries. You’ll also understand how AI-powered analytics skills are becoming increasingly valuable across sectors such as finance, healthcare, retail, telecom, manufacturing, and enterprise operations. Organizations are actively seeking professionals who can interpret data efficiently and support faster strategic decisions using AI-enabled tools. Whether you are exploring AI-powered analytics tools or looking to understand how AI integrates into modern data environments, this course offers a clear and structured starting point. By the end of the course, you’ll be able to use AI tools to analyze data more efficiently, improve reporting quality, strengthen forecasting accuracy, and contribute more confidently to data-driven business initiatives. Enroll in this AI data analytics training course to build practical, career-relevant AI skills and confidently apply AI in modern analytics environments.

This module introduces the overall certification structure and explains how the learning experience is organized throughout the course. To support different learning preferences, the content is offered in multiple formats, including Videos, eBooks, Audiobooks, and Podcasts. Each format covers the same key concepts, giving you the flexibility to learn in the way that works best for you. You can choose any format based on your preferred learning style and move through the course at your own pace.

Das ist alles enthalten

7 Videos1 Lektüre1 Aufgabe2 Plug-ins

7 VideosInsgesamt 33 Minuten

Navigation Video2 Minuten
Course Introduction4 Minuten
1.1 Understanding AI Agents in Data Systems6 Minuten
1.2 Components of AI Agents5 Minuten
1.3 Types of AI Agents6 Minuten
1.4 Architectures and Real-World Applications of AI Agents4 Minuten
1.5 Ethical and Design Considerations in AI Agents & Future Scope5 Minuten

1 LektüreInsgesamt 10 Minuten

Hands - On10 Minuten

1 AufgabeInsgesamt 30 Minuten

Quiz 130 Minuten

2 Plug-insInsgesamt 30 Minuten

Module 1: Introduction to AI Agents15 Minuten
ACTIVITY: Hotspot15 Minuten

Das ist alles enthalten

5 Videos1 Lektüre1 Aufgabe2 Plug-ins

5 VideosInsgesamt 32 Minuten

2.1 AI Data Agents6 Minuten
2.2 AI vs. AI Data Agent4 Minuten
2.3 Components of AI Data Agents5 Minuten
2.4 Types of AI Data Agents4 Minuten
2.5 AI Data Agents – Types, Applications, and Real-World Case Studies11 Minuten

1 LektüreInsgesamt 10 Minuten

Hands - On10 Minuten

1 AufgabeInsgesamt 30 Minuten

Quiz 230 Minuten

2 Plug-insInsgesamt 30 Minuten

Module 2: Data Agents and their Role in AI Systems 15 Minuten
ACTIVITY: Tab15 Minuten

Das ist alles enthalten

6 Videos1 Aufgabe2 Plug-ins

6 VideosInsgesamt 35 Minuten

3.1 AI Data Agents – Data Acquisition, Planning, and Case Studies in Smart Agriculture7 Minuten
3.2 AI Data Collection – Design, Preparation, and Quality Assurance8 Minuten
3.3 Storing the Data and Process Documentation4 Minuten
3.4 Annotation of the Data7 Minuten
3.5 Methods of Data Collection and Real-Time Data Streaming4 Minuten
3.6 Batch and API-Based Data Collection5 Minuten

1 AufgabeInsgesamt 30 Minuten

Quiz 330 Minuten

2 Plug-insInsgesamt 30 Minuten

Module 3: Data Collection and Acquisition for AI Data Agents15 Minuten
ACTIVITY: Problem Statement15 Minuten

Das ist alles enthalten

6 Videos1 Lektüre1 Aufgabe2 Plug-ins

6 VideosInsgesamt 36 Minuten

4.1 Data Pre-processing and Feature Engineering7 Minuten
4.2 Feature Engineering for AI Models8 Minuten
4.3 Feature Selection, Feature Extraction, and Real-World Applications5 Minuten
4.4 Dimensionality Reduction & Encoding7 Minuten
4.5 Binning, Bucketing, Feature Transformation and Feature Engineering6 Minuten
4.6 No-Code AI Data Agent for Preprocessing & Feature Engineering3 Minuten

1 LektüreInsgesamt 10 Minuten

Hands - On10 Minuten

1 AufgabeInsgesamt 30 Minuten

Quiz 430 Minuten

2 Plug-insInsgesamt 30 Minuten

Module 4: Data Pre-Processing and Feature Engineering15 Minuten
ACTIVITY: Drag and Drop15 Minuten

Das ist alles enthalten

5 Videos1 Lektüre1 Aufgabe2 Plug-ins

5 VideosInsgesamt 22 Minuten

5.1 Overview of Machine Learning for AI Data Agents5 Minuten
5.2 Machine Learning Techniques in AI Data Agents6 Minuten
5.3 Advanced Machine Learning for AI Data Agents3 Minuten
5.4 Selecting and Training Machine Learning Models for AI Data Agents4 Minuten
5.5 Advanced Machine Learning Models and Optimization for AI Data Agents4 Minuten

1 LektüreInsgesamt 10 Minuten

Hands - On10 Minuten

1 AufgabeInsgesamt 30 Minuten

Quiz 530 Minuten

2 Plug-insInsgesamt 30 Minuten

Module 5: AI and Machine Learning Models for Data Agents15 Minuten
Activity: Accordion15 Minuten

Das ist alles enthalten

5 Videos1 Aufgabe2 Plug-ins

5 VideosInsgesamt 23 Minuten

6.1 Key Ethical Issues and Broader Ethical Principles in AI Data Agents6 Minuten
6.2 Fairness and Accountability in AI Data Agents5 Minuten
6.3 Risk of Bias and Ethical Frameworks in AI Data Agents4 Minuten
6.4 Security and Privacy Concerns in AI Data Agents4 Minuten
6.5 Legal, Regulatory, and Ethical Data Practices in AI Data Agents4 Minuten

1 AufgabeInsgesamt 30 Minuten

Quiz 630 Minuten

2 Plug-insInsgesamt 30 Minuten

Module 6: Ethics, Security, and Privacy in AI Data Agents15 Minuten
ACTIVITY: Case Study15 Minuten

Das ist alles enthalten

2 Videos1 Lektüre1 Aufgabe1 Plug-in

Dozent

AI CERTs Team

AI CERTs

58 Kurse38.041 Lernende

von

AI CERTs

Warum entscheiden sich Menschen für Coursera für ihre Karriere?

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Lernender seit 2018

„Es ist eine großartige Erfahrung, in meinem eigenen Tempo zu lernen. Ich kann lernen, wenn ich Zeit und Nerven dazu habe.“

Jennifer J.

Lernender seit 2020

„Bei einem spannenden neuen Projekt konnte ich die neuen Kenntnisse und Kompetenzen aus den Kursen direkt bei der Arbeit anwenden.“

Larry W.

Lernender seit 2021

„Wenn mir Kurse zu Themen fehlen, die meine Universität nicht anbietet, ist Coursera mit die beste Alternative.“

Chaitanya A.

„Man lernt nicht nur, um bei der Arbeit besser zu werden. Es geht noch um viel mehr. Bei Coursera kann ich ohne Grenzen lernen.“

Häufig gestellte Fragen

It is designed for data analysts, business analysts, reporting professionals, and learners interested in AI-powered analytics.

No. The course is beginner-friendly and focuses on practical AI applications in analytics.

You’ll learn how AI supports forecasting, reporting, visualization, predictive analytics, and business intelligence processes.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.