Gen AI Supporting Data Engineers
Begin your vocation in generative AI data engineering. Obtain the necessary skills to secure a position as a data engineer by acquiring an understanding of generative AI. No prior experience is required.
Description for Gen AI Supporting Data Engineers
- Utilize your abilities to identify generative AI models and tools for text, code, image, audio, and video, as well as to identify real-world applications of generative AI.
- Describe the concepts, examples, and common tools of generative AI prompt engineering, and acquire the necessary techniques to develop effective, impactful prompts.
- Utilize generative AI tools to execute data engineering processes, including data warehouse schema design, data generation, augmentation, and anonymization.
- Assess real-world case studies that illustrate the successful implementation of generative AI in data repositories and ETL.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 21
Offered by: On Coursera offered by IBM
Duration: 2 months at 2 hours a week
Schedule: Flexible
Pricing for Gen AI Supporting Data Engineers
Use Cases for Gen AI Supporting Data Engineers
FAQs for Gen AI Supporting Data Engineers
Reviews for Gen AI Supporting Data Engineers
4.4 / 5
from 5 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Sari Noor
I�ve incorporated it into team projects with great success.
Reid Byrd
I rely on this AI tool more than I thought I would.
Ethan Davis
I can rely on it to draft solid beginnings to my work.
Ellis Wade
I�ve had a better work-life balance since using this regularly.
Grant Pike
Can be used in so many creative ways'it's very adaptable.
Alternative Tools for Gen AI Supporting Data Engineers
Featured Tools
The program provides students with the knowledge and abilities to differentiate between AI technologies, host models on Amazon Sagemaker, and apply AI and machine learning to real-world activities.
Learn to implement and apply unsupervised learning techniques, focusing on clustering and dimension reduction algorithms, in a business environment.
Gain practical skills in relational and NoSQL databases, Big Data tools, and data pipelines for comprehensive data engineering tasks.
Gain expertise in Bayesian statistics, Bayesian inference, and R programming through comprehensive courses, active learning, and a culminating real-world data analysis project.
Master TensorFlow and broaden your skill set. Four hands-on courses will enable you to personalize your machine learning models.