Upskilling via role-based pathways to speed up your information + AI profession
Databricks has spent years crafting and iterating technical trainings for learners throughout information, analytics, and AI disciplines to make sure that people, groups, and organizations that need to upskill or reskill have accessible and related content material. With the explosion of AI/ML and roles in information, analytics, and AI, the necessity to undertake new know-how has accelerated for a lot of organizations. It is predicted that 97 million jobs involving AI shall be created between 2022 and 2025. This presents a novel problem – upskilling expertise in a scalable manner.
Elevate your profession right this moment with Databricks’ Studying Pageant
Databricks’ digital Studying Pageant is a novel alternative to upskill and reskill throughout information engineering, information science, and information analytics programs constructed for our clients, prospects, and companions. This occasion will present entry to free self-paced, role-based content material. For individuals who efficiently full the self-paced coaching, they are going to be eligible to obtain a 50%-off Databricks certification voucher (extra particulars beneath).
Studying goals throughout self-paced programs
1: Information Engineer Course – Information Engineering with Databricks
This course prepares information professionals to leverage the Databricks Information Intelligence Platform to productionalize ETL pipelines. College students will use Delta Dwell Tables to outline and schedule pipelines that incrementally course of new information from quite a lot of information sources into the platform. College students will even orchestrate duties with Databricks Workflows and promote code with Databricks Repos.
- Use the Databricks Information Science and Engineering Workspace to carry out widespread code growth duties in an information engineering workflow.
- Use Spark SQL or PySpark to extract information from quite a lot of sources, apply widespread cleansing transformations, and manipulate complicated information with superior features.
- Outline and schedule information pipelines that incrementally ingest and course of information via a number of tables within the lakehouse utilizing Delta Dwell Tables in Spark SQL or Python.
- Orchestrate information pipelines with Databricks Workflow Jobs and schedule dashboard updates to maintain analytics up-to-date.
- Configure permissions in Unity Catalog to make sure that customers have correct entry to databases for analytics and dashboarding.
2: Information Engineer Course – Superior Information Engineering with Databricks
On this course, college students will construct upon their present data of Apache Spark, Structured Streaming, and Delta Lake to unlock the total potential of the generative information platform by using the suite of instruments supplied by Databricks. This course locations a heavy emphasis on designs favoring incremental information processing, enabling techniques optimized to constantly ingest and analyze ever-growing information. By designing workloads that leverage built-in platform optimizations, information engineers can scale back the burden of code upkeep and on-call emergencies, and rapidly adapt manufacturing code to new calls for with minimal refactoring or downtime. The subjects on this course needs to be mastered previous to trying the Databricks Licensed Information Engineering Skilled examination.
- Design databases and pipelines optimized for the Databricks Information Intelligence Platform.
- Implement environment friendly incremental information processing to validate and enrich information driving enterprise selections and functions.
- Leverage Databricks-native options for managing entry to delicate information and fulfilling right-to-be-forgotten requests.
- Handle code promotion, job orchestration, and manufacturing job monitoring utilizing Databricks instruments.
3: Information Analyst Course – Information Evaluation with Databricks SQL
This course offers a complete introduction to Databricks SQL. It’s designed with the intention of supporting people in search of the Affiliate Information Evaluation of Databricks SQL certification. Individuals will find out about ingesting information, writing queries, producing visualizations and dashboards, and how you can join Databricks SQL to further instruments through the use of Companion Join.
- Describe how Databricks SQL works within the Lakehouse structure
- Combine Unity Catalog and Delta Lake with Databricks SQL
- Describe how Databricks SQL implements information safety
- Question information in Databricks SQL
- Use SQL instructions particular to Databricks
- Create visualizations and dashboards in Databricks SQL
- Use automation and integration capabilities in Databricks SQL
- Share queries and dashboards with others utilizing Databricks SQL
4: Machine Studying Practitioner Course – Scalable Machine Studying with Apache Spark
This course teaches you how you can scale ML pipelines with Spark, together with distributed coaching, hyperparameter tuning, and inference. You’ll construct and tune ML fashions with SparkML whereas leveraging MLflow to trace, model, and handle these fashions. This course covers the most recent ML options in Apache Spark, reminiscent of Pandas UDFs, Pandas Features, and the pandas API on Spark, in addition to the most recent ML product choices, reminiscent of Function Retailer and AutoML.
- Carry out scalable EDA with Spark
- Construct and tune machine studying fashions with SparkML
- Observe, model, and deploy fashions with MLflow
- Carry out distributed hyperparameter tuning with HyperOpt
- Use the Databricks Machine Studying workspace to create a Function Retailer and AutoML experiments
- Leverage the pandas API on Spark to scale your pandas code
5: Machine Studying Practitioner Course – Machine Studying in Manufacturing
On this course, you’ll be taught MLOps finest practices for placing machine studying fashions into manufacturing. The primary half of the course makes use of a characteristic retailer to register coaching information and makes use of MLflow to trace the machine studying lifecycle, package deal fashions for deployment, and handle mannequin variations. The second half of the course examines manufacturing points together with deployment paradigms, monitoring, and CI/CD. By the top of this course, you should have constructed an end-to-end pipeline to log, deploy, and monitor machine studying fashions.
- Observe, model, and handle machine studying experiments.
- Leverage Databricks Function Retailer for reproducible information administration.
- Implement methods for deploying fashions for batch, streaming, and real-time.
- Construct monitoring options, together with drift detection.
There are 4 extra Studying Plans provided as a part of the Databricks Studying Pageant.
* Tips on how to be eligible for Databricks certification voucher
A 50%-off Databricks certification voucher1 shall be given to the primary 5,000 customers who full at the least one of many role-based programs throughout the period of the digital Studying Pageant.
1The remaining US $100 could be paid for via webassesor on the time of the examination registration via bank card solely.
- Just one voucher shall be given, whether or not the learner completes one or a number of course(s) / studying plan(s).
- The voucher could have a validity interval of 6 months (i.e. expire after 6 months).
- The voucher is relevant for the next exams solely:
- Databricks Licensed Information Engineer Affiliate
- Databricks Licensed Information Engineer Skilled
- Databricks Licensed Information Analyst Affiliate
- Databricks Licensed Machine Studying Affiliate
- Databricks Licensed Machine Studying Skilled
- The voucher shall be distributed 1-2 week(s) after the occasion closes.
- The certification voucher can’t be mixed with different presents or success credit.
Have questions? Ask within the Databricks Group: Databricks Academy Learners Group
Start upskilling and reskilling right this moment with Databricks Academy with the digital Databricks Studying Pageant