AI CERTs

AI For Data Analysts

AI CERTs

AI For Data Analysts

AI CERTs Team

Instructor: AI CERTs Team

Access provided by Google

1,511 already enrolled

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

7 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

7 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • 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

Details to know

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Assessments

7 assignments

Taught in English

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There are 7 modules in this course

Introduces the fundamentals of AI agents, their architecture, capabilities, and role in modern AI systems. This module covers how AI agents perceive information, make decisions, perform tasks autonomously, and interact with users, data sources, and other systems to achieve specific objectives.

What's included

6 videos1 assignment1 plugin

Explores the concept of data agents and their importance in managing, processing, and utilizing data within AI ecosystems. Learners will understand how data agents support data-driven decision-making, automate data workflows, improve data accessibility, and enhance the performance of AI applications.

What's included

5 videos1 assignment1 plugin

Covers the principles and techniques involved in gathering high-quality data for AI data agents. This module focuses on data sources, data acquisition methods, data integration, data labeling, and strategies for ensuring data accuracy, relevance, and reliability.

What's included

6 videos1 assignment1 plugin

Provides an understanding of preparing raw data for AI systems through cleaning, transformation, and optimization techniques. Learners will explore data preprocessing methods, handling missing data, normalization, feature selection, and feature engineering approaches to improve AI model performance.

What's included

6 videos1 assignment1 plugin

Introduces machine learning algorithms and AI models that power data agents. This module explores model selection, training, evaluation, optimization, and the application of supervised, unsupervised, and advanced AI techniques to enable intelligent data processing and decision-making.

What's included

5 videos1 assignment1 plugin

Examines the ethical, security, and privacy considerations involved in developing and deploying AI data agents. Topics include responsible AI practices, data protection, access control, bias mitigation, transparency, compliance, and strategies for building trustworthy AI systems.

What's included

5 videos1 assignment1 plugin

Provides hands-on experience in designing and implementing an AI data agent solution. Learners will apply concepts from previous modules to develop a project involving data collection, processing, AI model integration, evaluation, and presentation of an AI-driven solution to address a real-world problem.

What's included

2 videos1 assignment

Instructor

AI CERTs Team
AI CERTs
62 Courses63,411 learners

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AI CERTs

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