Certifications now time are very important in every field of life, whether it be jobs, internships, project undertakings, etc. If you got valuable certifications along with experience then you got more upper hand from other candidates. In this article, we are gonna talk about “Databricks Certifications”. Databricks conduct different exams for their different valuable certifications. Let’s get started with the first:
1.) Databricks Certified Professional Data Scientist certification exam
Databricks Certified Professional Data Scientist certification exam evaluates the understanding of the basics and steps involved in machine learning lifecycle including data preparation, feature engineering, training of models, model selection, interpreting models, and models production. It also evaluates the understanding of basics and techniques of machine learning algorithms including linear regression, logistic regression, regularization, decision trees, tree-based ensembles, basic clustering algorithms, and matrix factorization techniques. MLflow, the basics of model management such as logging and organization of model are also evaluated.
Qualification prerequisite
The qualified candidates should have –
- Comprehend basics of machine learning including bias-variance tradeoff, in-sample vs. out-of-sample data, machine learning categories, and applied statistics concepts.
- An intermediate understanding of the steps involved in the machine learning lifecycle including data preparation, feature engineering, model training, selection, and production as well as interpreting models.
- Comprehend basics of machine learning algorithms and techniques including –
- linear, logistic, and regularized regression.
- unsupervised techniques mainly PCA and K-means.
- tree-based models such as decision trees, gradient boosted trees, and random forest.
- Comprehend basics of machine learning management of model including logging and model organization with ML flow.
Exam Preparation
The following Databricks courses mentioned below should assist you to prepare for this exam
- Scalable Machine Learning with Apache Spark
- Machine Learning in Production.
Format of Exam
- The exam will be conducted through an online proctor and comprises 60 multiple-choice questions.
- Applicants have 120 minutes to complete the examination.
- The minimum passing score for the exam is 70%.
2.) Databricks Certified Associate Developer for Apache Spark 3.0 certification exam
It evaluates the understanding of the basics of Spark architecture and the ability to apply for Spark Data Frame API to complete individual data manipulation tasks. These tasks include selecting, renaming, and manipulating columns; handling missing data; filtering, dropping, sorting, and aggregating rows; reading, writing, combining, and partitioning Data Frames with schemas and working with Spark SQL and UDFs functions. Moreover, the exam will also evaluate the basics of Spark architecture like execution modes, execution hierarchy, fault tolerance, garbage collection, and broadcasting.
Qualification prerequisite
The qualified candidates should have –
- basic understanding of Spark architecture.
- be able to apply Spark DataFrame API to complete data manipulation task including:
- selecting, renaming, and manipulating columns.
- filtering, dropping, sorting, and aggregating rows.
- joining, reading, writing, and partitioning DataFrames.
Exam Preparation
The following Databricks courses mention below should assist you to prepare for this exam
- Apache Spark Programming with Databricks.
- Quick Reference: Spark Architecture.
- Learning spark.
Format of Exam
- The exam will be conducted through an online proctor and comprises 60 multiple-choice questions.
- Applicants have 120 minutes to complete the exam.
- The minimum passing score for the exam is 70%.
- For candidates who are appearing in exams having different languages, a PDF version of Apache Spark documentation will be provided.
3.) Azure Databricks Certified Associate Platform Administrator certification exam
Azure Databricks Certified Associate Platform Administrator certification exam evaluates the understanding of basics in security and network infrastructure, access and identity, cluster usage, and automation with a platform of Azure Databricks.
Qualification prerequisite
The qualified candidates should have –
- have a basic understanding of automation.
- have an understanding of network infrastructure and security including network security, Azure cloud concepts, and workspace deployment.
- have an intermediate understanding of cluster usage.
- have a complete understanding of identity and access configurations including identity management, workspace access control, data access control, and fine-grained security employing SOL.
Exam Preparation
The following data bricks self-paced courses mention below should assist you to prepare for this exam
- Azure Databricks Identity and Access Management.
- Azure Databricks Cluster Usage Management.
- Azure Databricks Security Fundamentals.
- Azure Databricks Data Access Management.
Exam details are the same like I mentioned in the Databricks Certified Professional Data Scientist certification exam.
4. Databricks Certified Professional Data Engineer
The Databricks platform and its tools can be effectively assessed and evaluated by it. The ability to build data pipeline modeling, data processing pipelines, the ability to make data pipelines secure, the ability to monitor and log activity on data pipelines, and understanding the practices for testing, managing, and deploying code.
Qualification prerequisite
The qualified candidates should have –
- build data processing pipelines utilizing Spark and Delta Lake APIs.
- Understand the benefits of the data bricks platform and its tools and how to operate it.
- Model data management solutions including Lakehouse and General data modeling concepts.
- Follow best practices for managing, testing, and deploying code including scheduling jobs, creating unit tests, managing dependencies, creating integration tests, etc, and many more.
Exam Preparation
The following Databricks courses mentioned below should assist you to prepare for this exam
- Apache Spark Programming with Databricks.
- Optimizing Apache Spark on Databricks.
- Data Engineering with Databricks.
- Exam details are the same.
Conclusion
To summarize the above work we can conclude that data bricks provide an open platform for your whole data. It basically empowers data engineers, data analysts, and data scientists with a collaborative environment to run interactive and scheduled data analysis workloads.