Data Skills for Artificial Intelligence

Master essential data engineering and crowdsourcing skills for AI applications with hands-on Python and SQL training.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Data Skills for Artificial Intelligence Professional Certificate program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

English

This course includes

3 Months

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

26,045

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What you'll learn

Master data management fundamentals for AI applications

Develop SQL skills for data extraction and manipulation

Learn Python, Pandas, and Seaborn for data analysis

Understand crowdsourcing principles and best practices

Implement quality control in data collection

Skills you'll gain

Data Engineering

Python Programming

SQL

Pandas

Seaborn

Data Visualization

Crowdsourcing

AI Data Collection

Quality Control

Active Learning

This course includes:

13 Hours PreRecorded video

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

Created by

Delft University of Technology

Provided by

Edx

Top companies offer this course to their employees

Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

There are 2 modules in this course

This professional certificate program focuses on essential data skills for AI applications. Students learn data management fundamentals, SQL for data extraction, Python programming with Pandas for data manipulation, and Seaborn for visualization. The curriculum covers crowdsourcing methodologies, including task design, quality control mechanisms, and active learning principles. Through hands-on exercises and practical projects, participants develop the technical skills needed to gather, process, and prepare data for AI applications.

Fee Structure

Payment options

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