Apache Spark - Exeliq

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Exeliq provides Apache Spark implementation services. We highly recommend Spark to enterprises worldwide. The framework offers great performance benefits and versatility. Enterprises are faced with a high volume and velocity of data coming from web and mobile apps. To stay ahead of the curve, it is critical that the speed of data processing and analysis should support the Big Data apps. Spark gives your business that advantage. It also offers multiple analytics options such as machine learning, streaming analytics and graph analytics.

Experienced teachers

Learn from The Exeliq’s experienced data science instructors who are dedicated to teaching data analytics.

Jumpstart your career

Learn the most sought-after tools and techniques in the industry to help jumpstart your data analyst career.

Working As professionals

This course was designed for the busy lives of working professionals with a part-time schedule and recorded lectures.

Build a series of miniprojects

Gain hands-on experience applying the tools employers value to real-world data sets. All powered by a 100-node cluster.

Live lectures

Live lectures allow you to ask your instructor questions and interact with your classmates. Registered students can find their demo live lectures.

Small class sizes

Small class sizes ensure you have plenty of access to your instructor and can receive personalized feedback on your progress.

CURRICULUM

Prerequisites:

Intermediate Python and Spark/Scala
Azure/AWS (S3, Redshift, Azure Blob Storage, Azure Data Lake Storage, Azure SQL Data warehouse)
Hadoop/Hive

Target Audience:

This class is for you if:
Programmers, Developers, Technical Leads, Architects
Developers/Business Analysts aspiring to be a ‘Machine Learning Engineer'
Data Scientists/Data Analysts who want to gain expertise in Predictive Analytics
'Python' professionals who want to design automatic predictive models

Learning Outcomes:

Upon completion of this course, you will be able to:
Learn how to use Databricks for Python/Spark/R/Spark-SQL development
Setup job for Notebook, Setup Spark cluster
Setup BI Tool with Databricks
Intergrate CMD CLI with Databricks
Use Databrick Rest API
Use Databrick for Data Visulazation
Learn how to use the Databricks for ML/GraphX/Predictive models.

Spark Overview

Basic Spark Components


Spark Architecture


Low Level API – RDD & RDD Operation
(Trasformation and Actions)


Discributed Variable – Broadcast Variable & Accumulator


RDD – Partitions and Shuffling

Spark SQL and DataFrames

Reading from CSV, JSON, Parquet Files, JDBC


Writing Data in CSV, JSON, Parquet Files, JDBC


Use of DataFrames


Use of DataSets


Spark SQL


SQL Joins with DataFrames


Broadcast Join


Aggregations


UDF


Catalyst Query Optimization(Theory )

Spark Internals

Jobs, Stages and Tasks (Theory )


Partitions and Shuffling

Structured Streaming

Streaming Sources and Sinks


Structured Streaming APIs


Windowing and Aggregation


Checkpointing


Watermarking


Reliability and Fault Tolerance (Theory)

Machine Learning

Basic of Spark ML


Liner and Logistic Regression ML Algo

Graph Processing with GraphFrames

Basic GraphFrames API

Contact us

Contact us for the Data Science Foundations Online Course



The next Data Science Foundations Online Course will run from 2019-03-05 to 2019-04-25. Classes are generally held on Tuesdays and Thursdays from 6:30-9:30 PM ET / 3:30-6:30 PM PT, with some exceptions for holidays. The deadline for registration is 2019-02-22. The course tuition is $3495 with early-bird discounts available. The exact dates for the next session will be: 3/5, 3/7, 3/12, 3/14, 3/19, 3/21, 3/25, 3/28, 4/2, 4/4, 4/9, 4/11, 4/16, 4/18, 4/23, 4/25
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