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Big Data Engineering Certification in Apache Spark and Scala Certification
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Updated at : September 30, 2024
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Universities
1
Duration
3 - 12 Months
Eligibility info
10+2 Pass out/ Diploma/ Graduation
Apache Spark & Scala is an integral part of Big Data & Hadoop system. Online certification in the same will help you gain expertise in the field with hands-on training on related tools. This program is designed by industry experts who hold 10+ years of experience.
The online availability of this program had made it accessible to working professionals & even for students who were unable to upskill before due to commute/relocation issues. An in-depth understanding of Spark, a fast-growing tool, will help IT professionals to mark their place in this domain of the industry.
The curriculum of this technical certification program is designed by industry experts to bridge the gap between conceptual understanding of topics & their implementations to solve the real challenges of the industry. The technical training services offered in this program will make you learn new techniques in the field that would help you explore promising career opportunities around the globe.
The curriculum of this online program is quite technical & helps you gain beginner to advanced-level knowledge of Big Data, Spark, & Scala. The core topics are listed below with some of their sub-topics to give you an overview of this online program’s syllabus.
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The common eligibility criteria for this online certification course are as follows:
The duration of this online instructor-led certification program ranges between 6-8 weeks on opting for a weekend batch. This duration is even shorter when offered in the weekday batch. Being institution-specific criteria, the exact period invested in this course can be confirmed after finalizing the institution & batch for this program.
The admission procedure for this online certification course can be completed by following the below-mentioned steps:
Step 1: Visit the official website of the institution offering this program & fill out the online application form with the necessary personal and educational information.
Step 2: Upload the mandatory documents as asked by the institution for your background verification.
Step 3: Pay the course fee using the stated online payment methods. You can choose the EMI facility, if available.
Step 4: Download the confirmation slip & keep your login information or access details safe to access the LMS portal.
With a 360-degree knowledge of big data analytics, explore promising career opportunities in banking, retail, finance, healthcare, manufacturing, and government sectors. Online certification in Apache Spark & Scala fulfills the rising demand of the industry after equipping professionals with the right skills & training.
There is an abundance of jobs with handsome salaries after completion of this certification course. Some of them are listed here to help you understand the career prospect of this course.
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An online Apache Spark & Scala certification course equips you with the details of Big Data, Hadoop, HDFS (Hadoop Distributed File System), and YARN (Yet Another Resource Negotiator), many other related topics. It makes you become a certified Spark Developer.
The duration of an online certification in Apache Spark & Scala varies with the choice of institution. Although, generally 6-8 weeks are required to complete this course.
Access to Cloud Labs is provided to learners to execute their practicals, demos, etc. in an Apache Spark & Scala certification course to make them understand the implementation process of the concepts learned in this program.
The pay scale after an online certification in Apache Spark & Scala is between 4-18 LPA with an average of 9 LPA. This range varies as per the skills & experience of the individuals.
The fee range for the online Apache Spark & Scala certification course lies between 19,000 INR to 22,000 INR.
An online Apache Spark & Scala certification course holds approval from NASSCOM, thus, is recognized in the industry for job placements & by institutions for higher studies in the related domain.
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