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Big Data with Amazon Cloud, Hadoop/Spark and Docker

Big Data with Amazon Cloud, Hadoop/Spark and Docker

This is a 6-week evening program providing a hands-on introduction to the Hadoop and Spark ecosystem of Big Data technologies. The course will cover these key components of Apache Hadoop: HDFS, MapReduce with streaming, Hive, and Spark. Programming will be done in Python. The course will begin with a review of Python concepts needed for our examples. The course format is interactive. Students will need to bring laptops to class. We will do our work on AWS (Amazon Web Services); instructions will be provided ahead of time on how to connect to AWS and obtain an account.

* Tuition paid for part-time courses can be applied to the Data Science Bootcamps if admitted within 9 months.

Course Dates

 
June Session

Jun 23 - Jul 30, 2020
Tuesday, Thursday
7:00-9:30pm

$2990.00
Enroll Now
Earlybird ends on 07/26
August Session

Aug 25 - Oct 1, 2020
Tuesday, Thursday
7:00-9:30pm

$2990.00
$2990.00
$2840.50
Enroll Now
Earlybird ends on 09/27
October Session

Oct 27 - Dec 8, 2020
Tuesday, Thursday
7:00-9:30pm

$2990.00
$2990.00
$2840.50
Enroll Now
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Product Description

Course Overview

This 6-week program provides a hands-on introduction to Apache Hadoop and Spark programming using Python and cloud computing. The key components covered by the course include Hadoop Distributed File Systems, MapReduce using MRJob, Apache Hive, Pig, and Spark. Tools and platforms that are used include Docker, Amazon Web Services and Databricks. In the first half of the program students are required to pull a pre-built Docker image and run most of the exercises locally using docker containers. In the second half students must access their AWS and Databricks accounts to run cloud computing exercises. Students will need to bring their laptops to class. Detailed instructions will be provided ahead of time on: how to pull and run a docker image, how to connect to AWS/Databricks, etc.

Prerequisites

To get the most out of the class, you need to be familiar with Linux file systems, Linux command line interface (CLI) and the basic linux commands such as cd, ls, cp, etc. You also need to have basic programming skills in Python, and are comfortable with functional programming style, for example, how to use map() function to split a list of strings into a nested list. Object oriented programming (OOP) in python is not required.

Certificate

Certificates are awarded at the end of the program at the satisfactory completion of the course. Students are evaluated on a pass/fail basis for their performance on the required homework and final project (where applicable). Students who complete 80% of the homework and attend a minimum of 85% of all classes are eligible for the certificate of completion.

Reviews

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Demo Course

MapReduce using MRJob
Module
MapReduce
Instructor
Jake Bialer
Description
NYC Data Science Academy's Instructor, Jake Bialer, walks through a lecture on MapReduce examples.

Syllabus

Unit 1: Introduction to Hadoop

  • 1. Data Engineering Toolkits
    • Running Linux using Docker containers
    • Linux CLI command and bash scripts
    • Python basics
  • 2. Hadoop and MapReduce
    • Big Data Overview
    • HDFS
    • YARN
    • MapReduce

Unit 2 – MapReduce

  • 3. MapReduce using MRJob 1
    • Protocols for Input & Output
    • Filtering
  • 4. MapReduce using MRJob 2
    • Top n
    • Inverted Index
    • Multi-step Jobs

Unit 3 – Apache Hive

  • 5. Apache Hive 1
    • Databases for Big Data
    • HiveQL and Querying Data
    • Windowing And Analytics Functions
    • MapReduce Scripts
  • 6. Apache Hive 2
    • Tables in Hive
    • Managed Tables and External Tables
    • Storage Formats
    • Partitions and Buckets

Unit 4 – Apache Pig

  • 7. Apache Pig 1
    • Overview
    • Pig Latin: Data Types
    • Pig Latin: Relational Operators
  • 8. Apache Pig 2
    • More Pig Latin: Relational operators
    • More Pig Latin: Functions
    • Compiling Pig to MapReduce
    • The Parallel Clause
    • Join Optimizations

Unit 5 – Apache Spark and AWS

  • 9. Apache Spark – Spark Core
    • Spark Overview
    • Running Spark using Databricks Notebooks
    • Working with PySpark: RDDs
    • Transformations and Actions
  • 10. Apache Spark – Spark SQL
    • Spark DataFrame
    • SQL Operations using Spark SQL
  • 11. Apache Spark – Spark ML
    • ML Pipeline using PySpark
  • 12. Amazon Elastic MapReduce
    • Overview
    • Amazon Web Services: IAM, EC2, S3
    • Creating EMR Cluster
    • Submitting Jobs
    • Intro to AWS CLI

Our Alumni Feedback

I attended the Big Data with Amazon Cloud, Hadoop/Spark and Docker course, hosted and led by NYC Data Science Academy. My objective was two-fold: first, to gain a deeper and practical understanding on emerging 'Big Data' technologies, more so than what academic publications or industry white papers currently provide; and, second, to familiarize myself with the skill set and experience to expect from the new generation statisticians, or Data Scientists. With a background in Business Intelligence, Architecture, Risk Management and Governance on Wall Street, I find that foundational skills remain the same: mathematics and statistics. However, with the commoditizing of data storage and massively parallel computing, Data Scientist today are capable of solving problems reserved for an exclusive few in decades past. The course did not cover configuration of the Hadoop environment, but thanks to the engaging and knowledgeable instructor, clues on challenges and potential pitfalls were generously shared. I highly recommend this course not only to professionals or recent graduates looking to hone data analysis skills, but to anyone with an interest or stake in Big Data.
Sebastian Nordgren
Senior Vice President
Citi
I attended the Big Data with Amazon Cloud, Hadoop/Spark and Docker course, hosted and led by NYC Data Science Academy. My objective was two-fold: first, to gain a deeper and practical understanding on emerging 'Big Data' technologies, more so than what academic publications or industry white papers currently provide; and, second, to familiarize myself with the skill set and experience to expect from the new generation statisticians, or Data Scientists. With a background in Business Intelligence, Architecture, Risk Management and Governance on Wall Street, I find that foundational skills remain the same: mathematics and statistics. However, with the commoditizing of data storage and massively parallel computing, Data Scientist today are capable of solving problems reserved for an exclusive few in decades past. The course did not cover configuration of the Hadoop environment, but thanks to the engaging and knowledgeable instructor, clues on challenges and potential pitfalls were generously shared. I highly recommend this course not only to professionals or recent graduates looking to hone data analysis skills, but to anyone with an interest or stake in Big Data.
Sebastian Nordgren
Senior Vice President
Citi

Campus Location

500 8th Ave #905, New York, NY 10018
500 8th Ave Suite 905, New York, NY 10018
Nearby Subways
1 2 3 34th, Penn Station
A C E 34th, Penn Station
N Q R B D F M 34th, Herald Square

Instructors

Jake Bialer
Jake Bialer
Instructor
Jake Bialer is a full stack developer and data scientist who has spent the last decade immersed in data problems at online media organizations, e-commerce sites, and other web businesses. He currently runs his own consultancy, Bialerology, and teaches web scraping and big data engineering at the NYC Data Science Academy.

Session Schedule

 
June Session

Jun 23 - Jul 30, 2020 Tuesday & Thursday
  • 1June 23, 2020
  • 2June 25, 2020
  • 3June 30, 2020
  • 4July 2, 2020
  • 5July 7, 2020
  • 6July 9, 2020
  • 7July 14, 2020
  • 8July 16, 2020
  • 9July 21, 2020
  • 10July 23, 2020
  • 11July 28, 2020
  • 12July 30, 2020
7:00-9:30pm

$2990.00
Enroll Now
Earlybird ends on 07/26
August Session

Aug 25 - Oct 1, 2020 Tuesday & Thursday
  • 1August 25, 2020
  • 2August 27, 2020
  • 3September 1, 2020
  • 4September 3, 2020
  • 5September 8, 2020
  • 6September 10, 2020
  • 7September 15, 2020
  • 8September 17, 2020
  • 9September 22, 2020
  • 10September 24, 2020
  • 11September 29, 2020
  • 12October 1, 2020
7:00-9:30pm

$2990.00
$2990.00
$2840.50
Enroll Now
Earlybird ends on 09/27
October Session

Oct 27 - Dec 8, 2020 Tuesday & Thursday
  • 1October 27, 2020
  • 2October 29, 2020
  • 3November 3, 2020
  • 4November 5, 2020
  • 5November 10, 2020
  • 6November 12, 2020
  • 7November 17, 2020
  • 8November 19, 2020
  • 9November 24, 2020
  • 10December 1, 2020
  • 11December 3, 2020
  • 12December 8, 2020
7:00-9:30pm

$2990.00
$2990.00
$2840.50
Enroll Now

Save More by Enrolling in a Bundle

Data Science Mastery
Data Science with R: Machine Learning
Data Science with R: Machine Learning
Data Science with Python: Machine Learning
Data Science with Python: Machine Learning
Big Data with Amazon Cloud, Hadoop/Spark and Docker
Big Data with Amazon Cloud, Hadoop/Spark and Docker
$7970.00
Total: $7970.00$7410.00