Accelerating Data Engineering Pipelines Training
Course Authors
Accelerating Data Engineering Pipelines Training Hands-on (Online, Onsite, and Classroom Live)
| Commitment | 1 Day, 7-8 hours a day. |
| Language | English |
| User Ratings | Average User Rating 4.8 See what learners said |
| Price | REQUEST |
| Delivery Options | Instructor-Led Onsite, Online, and Classroom Live |
COURSE OVERVIEW
With Accelerating Data Engineering Pipelines Training, participants will explore applying advanced data engineering tools and techniques with GPUs to significantly improve data engineering pipelines.
Please note that once a booking has been confirmed, it is non-refundable. This means that after you have confirmed your seat for an event, it cannot be canceled, and no refund will be issued, regardless of attendance.
WHAT'S INCLUDED?
- 1 day of Accelerating Data Engineering Pipelines Training with an expert instructor
- Accelerating Data Engineering Pipelines Electronic Course Guide
- Certificate of Completion
- 100% Satisfaction Guarantee
RESOURCES
- Accelerating Data Engineering Pipelines – https://www.wiley.com/
- Accelerating Data Engineering Pipelines – https://www.packtpub.com/
- Accelerating Data Engineering Pipelines – https://store.logicaloperations.com/
- Accelerating Data Engineering Pipelines Training – https://us.artechhouse.com/
- Accelerating Data Engineering Pipelines Training – https://www.amazon.com/
RELATED COURSES
ADDITIONAL INFORMATION
COURSE OBJECTIVES
Upon completion of this Accelerating Data Engineering Pipelines Training course, participants can:
- How data moves within a computer. How to build the right balance between CPU, DRAM, Disk Memory, and GPUs.
- How different file formats can be read and manipulated by hardware.
- How to scale an ETL pipeline with multiple GPUs using NVTabular.
- How to build an interactive Plotly dashboard where users can filter on millions of data points in less than a second.
CUSTOMIZE IT
- We can adapt this Accelerating Data Engineering Pipelines Training course to your group’s background and work requirements at little to no added cost.
- If you are familiar with some aspects of this Accelerating Data Engineering Pipelines course, we can omit or shorten their discussion.
- We can adjust the emphasis placed on the various topics or build the Accelerating Data Engineering Pipelines course around the mix of technologies of interest to you (including technologies other than those in this outline).
- If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policymaker), and present the Accelerating Data Engineering Pipelines course in a manner understandable to lay audiences.
AUDIENCE/TARGET GROUP
The target audience for this Accelerating Data Engineering Pipelines Training course:
- ALL
CLASS PREREQUISITES
The knowledge and skills that a learner must have before attending this Accelerating Data Engineering Pipelines Training course are:
- Intermediate knowledge of Python (list comprehension, objects)
- Familiarity with pandas a plus
- Introductory statistics (mean, median, mode)
COURSE SYLLABUS
Introduction
- Meet the instructor.
- Create an account at courses.nvidia.com/join
Data on the Hardware Level
- Explore the strengths and weaknesses of different hardware approaches to data and the frameworks that support them:
- Pandas
- CuDF
- Dask
ETL with NVTabular
- Learn how to scale an ETL pipeline from 1 GPU to many with NVTabular through the perspective of a big data recommender system.
- Transform raw json into analysis-ready parquet files
- Learn how to quickly add features to a dataset, such as Categorify and Lambda operators
Data Visualization
- Step into the shoes of a meteorologist and learn how to plot precipitation data on a map.
- Learn how to use descriptive statistics and plots like histograms in order to assess data quality
- Learn effective memory usage, so users can quickly filter data through a graphical interface
Final Project: Data Detective
- Users are complaining that the dashboard is too slow. Apply the techniques learned in class to find and eliminate efficiencies in the backend code
Final Review
- Review key learnings and answer questions.
- Complete the assessment and earn your certificate.
- Complete the workshop survey.
- Learn how to set up your own AI application development environment.
