Apache spark with Python Training Objectives
- Certainly Yes, the spark is worth learning because of its huge demand for spark professionals and its salaries. The usage of Spark for their big data processing is increasing at a very fast speed compared to other tools of big data.
- The average salary of a Spark professional is over $75,000 per year.
- Future is all about big data and spark provides a rich set of tools to handle real-time the large size of data
- Its lighting fast speed, fault tolerance, and efficient in-memory processing make Spark a future technology.
- Certainly Yes. Even the recruiters know the knowledge we get in colleges is not enough to do a software job. They will see how confident you are. However they will train you according to their requirement once you get into the company.
- Be confident with your basics that's enough You to get tons of Jobs opportunity by learning Apache spark with Python programming language.
- Deep practical knowledge and Hands-on lab.
- Real-time project use cases and scenarios from the various Industries.
- Mock Tests and discussing various questions.
- LearnoVita has been actively involved in 100% Job Placement Assistance as a value-added service in the Technical Program. With the backup of an advanced training curriculum and real-time business projects, we have a very consistent and growing Job Placement and Track Record.
- Market entry to various countries and jobs in major corporate.
- Immediate job opportunities after Completion of training.
- Active Coordination with students from the stage of preparing a professional CV/Resume to attend Interviews and securing a Job.
- Preliminary Preparation ensures that our students are able to perform confidently in Interviews even it was their First Interview.
- The prerequisites are you must have minimum knowledge in Scala.you can learn Scala If you know any programming language like C, C++, core java, php, python, or any other language , you can easily learn Scala language
- Mostly Yes, But having a minimum knowledge in programming language is enough to learn Apache spark with Python
- Describe the limitations of MapReduce in Hadoop
- Compare batch vs. real-time analytics
- Describe the application of stream processing and in-memory processing.
- Explain the features and benefits of Spark
- Explain how to install Spark as a standalone user,
- Compare Spark vs. Hadoop Eco-system
- Software developers
- Web designers
- Programming enthusiasts
- Engineering graduates
- Students who all want to become Apache spark with Python developers
- Apache Spark is a fascinating platform for data scientists with use cases spanning across investigative and operational analytics.
- Data scientists are exhibiting interest in working with Spark because of its ability to store data resident in memory that helps speed up machine learning workloads unlike Hadoop MapReduce.
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Top Skills You Will Gain
- Spark DataFrames
- Pandas Foundations
- RDD actions and transformations
- work with Spark in Python
- cache or persist RDDs
- best practices in Spark
- Spark Performance
- logging for PySpark
Online Classroom Batches Preferred
No Interest Financing start at ₹ 5000 / month
Corporate Training
- Customized Learning
- Enterprise Grade Learning Management System (LMS)
- 24x7 Support
- Enterprise Grade Reporting
Apache Spark with Python Course Curriculam
Trainers Profile
Trainers are certified professionals with 13+ years of experience in their respective domains as well as they are currently working with Top MNCs. As all Trainers from Apache Spark with Python Online Training course are respective domain working professionals so they are having many live projects, trainers will use these projects during training sessions.
Pre-requisites
There are no such prerequisites to learn Python but having a basic knowledge of any programming language concepts like what is a loop, what if and else does, how operators are used, etc. will be helpful.
Syllabus of Apache Spark with Python Online Course Download syllabus
- 1. Introduction to the Module
- 2. What is PySpark
- 3. PySpark in Industry
- 4. Why to go for Python
- 1. Big Data Overview
- 2. Facts about Big Data
- 3. Big Data Scenarios
- 4. Apache Hadoop Framework
- 5. Top Hadoop Users
- 6. Difference between RDBMS and Hadoop
- 7. Cluster Modes in Hadoop
- 8. Hadoop Ecosystem
- 9. HDFS Daemons and Mapreduce daemons
- 10. Top Reasons Why you should Learn Hadoop
- 11. Hadoop distributions and compatibilities
- 12. Hadoop Ecosystem in Detail
- 13. Hadoop Distributed File System
- 14. HDFS Files and Blocks
- 15. HDFS components and architecture
- 16. HDFS File Read and Write
- 1. Batch and Real Time Analytics
- 2. Why Spark when Hadoop is Already there
- 3. Introduction to Apache Spark
- 4. Features of Apache Spark
- 5. Users and Use Cases of Apache Spark
- 6. Job Execution Flow and Spark Execution
- 7. Spark Unified Stack
- 8. Complete Picture of Apache Spark
- 9. Apache spark Architecture
- 10. Top Companies Using Spark
- 1. Getting Started with Python
- 2. Introduction to Python
- 3. Advantages and facts about python
- 4. First python program
- 5. Program execution and python IDE
- 6. Built in types in python
- 7. Numbers Data Type in Python
- 8. String and List Data Type
- 9. Dictionary, Tuples and Sets
- 10. Variables and assignment
- 1. Downloading and Installing Enthought Canopy
- 2. Downloading and Installing jdk
- 3. Downloading and Installing Spark
- 4. Downloading and Setup of winutils
- 5. Setting up Environment Variables
- 6. Running the first Spark Program
- 7. Downloading and Extracting movie ratings datasets
- 8. Running Ratings Counter Spark Program
- 9. Understanding key value pairs with an example
- 10. Filtering RDD using an example
- 11. Finding maximum temperature by location
- 12. Map vs FlatMap
- 13. Understanding FlatMap using Word Count example
- 14. Sorting the word count results
- 15. Total Amount Spent Example
- 16. Sorting the Total Amount Spent Example result
- 1. Most popular movie example
- 2. Understanding Broadcast Variables with an example
- 3. Finding Similar Movies Example
- 4. Finding Most Popular Superhero example
- 1. Executing SQL commands
- 2. Using SQL style functions instead of queries
- 3. Using DataFrames instead of RDD
- 1. Using MLlib to produce movie recommendations
- 2. Using Dataframe with MLlib using an example
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Phone (For Voice Call):
+91 89258 75257
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+91 89258 75257
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Request more informations
Phone (For Voice Call):
+91 89258 75257
WhatsApp (For Call & Chat):
+91 89258 75257
Exam & Certification
- Participate and Complete One batch of Apache spark with Python Training Course
- Successful completion and evaluation of any one of the given projects
- Complete 85% of the Apache spark with Python Certification course
- Successful completion and evaluation of any one of the given projects
- Oracle Certified Associate (OCA)
- Oracle Certified Professional (OCP)
- Oracle Certified Expert (OCE)
- Oracle Certified Master (OCM)
- Learn About the Certification Paths.
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Apache spark with Python Course FAQ's
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- All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.
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