CCA 175 - Spark and Hadoop Developer Certification - Scala
What you'll learn
- Entire curriculum of CCA Spark and Hadoop Developer
- HDFS Commands
- Scala Fundamentals
- Core Spark - Transformations and Actions
- Spark SQL and Data Frames
Requirements
- Basic programming skills
- Cloudera Quickstart VM or valid account for IT Versity Big Data labs or any Hadoop clusters where Hadoop, Hive and Spark are well integrated.
- Minimum memory required based on the environment you are using with 64 bit operating system
Description
CCA 175 Spark and Hadoop Developer is one of the well recognized Big Data certification. This scenario based certification exam demands basic programming using Python or Scala along with Spark and other Big Data technologies.
This comprehensive course covers all aspects of the certification using Scala as programming language.
Scala Fundamentals
Core Spark - Transformations and Actions
Spark SQL and Data Frames
File formats
Flume, Kafka and Spark Streaming
Apache Sqoop
Exercises will be provided to prepare before attending the certification. Intention of the course is to boost the confidence to attend the certification.
All the demos are given on our state of the art Big Data cluster. You can avail one week complementary lab access by filling the form which is provided as part of the welcome message.
Who this course is for:
- Any IT aspirant/professional willing to learn Big Data and give CCA 175 certification
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Course content
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Instructors
13+ years of experience in executing complex projects using vast array of technologies including Big Data and Cloud.
ITVersity, Inc. - a US based organization to provide quality training for IT professionals and we have the track record of training hundreds of thousands of professionals globally.
Building IT career for people with required tools such as high quality material, labs, live support etc to upskill and cross skill is paramount for our organization.
At this time our training offerings are focused on following areas:
* Application Development using Python and SQL
* Big Data and Business Intelligence
* Cloud
* Datawarehousing, Databases
We have built a team to support going forward. If you send messages to this account for our courses, they will be sent to our Helpdesk from where we will be rewriting to our team.
3+ years of IT Experience in the areas of Python using Django as well as Flask, Spark, Linux, SQL using any RDBMS, Java Script, Node JS, Mongo DB etc.
I will be primarily providing support for Python, SQL and other related courses as co-instructor to ITVersity courses.
ITVersity, Inc. - a US based organisation to provide quality training for IT professionals and we have the track record of training hundreds of thousands of professionals globally.
Building IT career for people with required tools such as high quality material, labs, live support etc to up skill and cross skill is paramount for our organisation.
At this time our training offerings are focused on following areas:
* Application Development using Python and SQL
* Big Data and Business Intelligence
* Cloud
* Data Warehousing, Databases
- 4.2 Instructor Rating
- 3,671 Reviews
- 22,992 Students
- 3 Courses
Experienced Data Engineer with a demonstrated history of working in the consumer goods industry. Skilled in Apache Airflow, Apache Kafka, Hive, Apache Spark, and Amazon Web Services (AWS). Strong information technology professional with a Master's degree focused in Analytics from University of Cincinnati.
ITVersity, Inc. is a US-based organisation providing quality training for IT professionals and we have a track record of training hundreds of thousands of professionals globally.
Helping build IT careers of people with high-quality content, Labs, live support etc. to upskill and cross-skill is paramount for our organisation.
I will be overseeing the support for ITVersity courses related to Data Engineering and DevOps Engineering
At this time our training offerings are focused on the following areas:
* Application Development using Python and SQL
* Big Data and Business Intelligence
* Cloud
* Data Warehousing, Databases