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The Databricks course is designed to equip learners with the knowledge and skills necessary to work with Apache Spark and Databricks. It's beneficial for those aiming to obtain Databricks certification and gain expertise in Analytics-courses">big data processing, Analytics, and machine learning. The course walks through the essentials of Analytics-courses">big data, Spark's various programming languages, and the use of Databricks' unified platform, including its architecture and community edition.
Learners will understand how to implement Databricks on Azure and AWS cloud services, integrate into Data pipelines, and set up their workspaces and clusters. The course also covers Data ingestion, Performing queries, data visualization, and the use of Delta Lake for data reliability. By the end of the course, participants will be well-prepared to take Databricks certification courses and apply their knowledge in real-world scenarios, from Analytics to machine learning projects.
Successfully delivered 6 sessions for over 13 professionals
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USD
View Fees Breakdown
Course Fee | 1,450 |
Exam Fee | 286 |
Total Fees (without exam) |
1,450 (USD) |
USD
View Fees Breakdown
Course Fee | 1,150 |
Exam Fee | 286 |
Total Fees (without exam) |
1,150 (USD) |
USD
View Fees Breakdown
Flexi Video | 16,449 |
Official E-coursebook | |
Exam Voucher (optional) | |
Hands-On-Labs2 | 4,159 |
+ GST 18% | 4,259 |
Total Fees (without exam & Labs) |
22,359 (INR) |
Total Fees (with exam & Labs) |
28,359 (INR) |
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To ensure a successful learning experience in the Databricks course offered by Koenig Solutions, the following minimum prerequisites are recommended:
Basic Understanding of Big Data Concepts: Familiarity with what Big Data is and the challenges it presents is essential, as Databricks is a platform designed to handle large data sets.
Fundamental Knowledge of Apache Spark: Since Databricks is built on top of Apache Spark, having an introductory understanding of Spark's role in big data processing will be beneficial.
Programming Experience: Some experience with at least one of the Spark languages (Scala, Python, R, Java, or SQL) is highly recommended, as these are used for data processing and analysis tasks within Databricks.
Conceptual Knowledge of Data Analytics and Machine Learning: Understanding the basics of data analytics and machine learning will help in comprehending the applications and capabilities of Databricks.
Familiarity with Cloud Platforms: Basic knowledge of cloud services, particularly Microsoft Azure and/or Amazon Web Services (AWS), since the course covers Databricks implementation on these platforms.
Interest in Data Engineering/Science: As Databricks is a tool used predominantly by data engineers and scientists, an interest in these fields will facilitate a more engaging learning experience.
Please note that while these prerequisites are recommended for the best chance at success, Koenig Solutions is committed to helping all students, regardless of their starting skill level. Our courses are designed to be accessible, with expert instructors ready to guide you through each step of your learning journey.
The Databricks course by Koenig Solutions covers Big Data analytics, machine learning, and cloud implementations, targeting IT professionals enhancing data skills.
Target Audience for the Databricks Course:
In this Databricks course, participants will gain comprehensive knowledge of Apache Spark, Databricks, data analytics, machine learning, and cloud implementations, leading to mastery in data engineering and analysis.