About this course: This course is for novice programmers or business people who would like to understand the core tools used to wrangle and analyze big data. With no prior experience, you will have the opportunity to walk through hands-on examples with Hadoop and Spark frameworks, two of the most common in the industry. You will be comfortable explaining the specific components and basic processes of the Hadoop architecture, software stack, and execution environment. In the assignments you will be guided in how data scientists apply the important concepts and techniques such as Map-Reduce that are used to solve fundamental problems in big data. You'll feel empowered to have conversations about big data and the data analysis process.
Created by: University of California, San Diego
Taught by: Natasha Balac, Director, Predictive Analytics Center of Excellence (PACE)
San Diego Supercomputer Center
Taught by: Paul Rodriguez, Research Programmer
San Diego Supercomputer Center (SDSC)
Taught by: Andrea Zonca, HPC Applications Specialist
San Diego Supercomputer Center (SDSC)
| Commitment | 5 weeks of study, 1-2 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
Syllabus
WEEK 1
Hadoop Basics
Welcome to the first module of the Big Data Platform course. This first module will provide insight into Big Data Hype, its technologies opportunities and challenges. We will take a deeper look into the Hadoop stack and tool and technologies associated with B...
7 videos, 4 readings
Graded: Basic Hadoop Stack
WEEK 2
Introduction to the Hadoop Stack
In this module we will take a detailed look at the Hadoop stack ranging from the basic HDFS components, to application execution frameworks, and languages, services.
10 videos, 6 readings
Graded: Overview of Hadoop Stack
Graded: Hadoop Execution Environment
Graded: Hadoop Applications
WEEK 3
Introduction to Hadoop Distributed File System (HDFS)
In this module we will take a detailed look at the Hadoop Distributed File System (HDFS). We will cover the main design goals of HDFS, understand the read/write process to HDFS, the main configuration parameters that can be tuned to control HDFS performance an...
9 videos, 5 readings
Graded: HDFS Architecture
Graded: HDFS performance,tuning, and robustness
Graded: Accessing HDFS
WEEK 4
Introduction to Map/Reduce
This module will introduce Map/Reduce concepts and practice. You will learn about the big idea of Map/Reduce and you will learn how to design, implement, and execute tasks in the map/reduce framework. You will also learn the trade-offs in map/reduce and how t...
9 videos, 3 readings
Graded: Running Wordcount with Hadoop streaming, using Python code
Graded: Lesson 1 Review
Graded: Joining Data
WEEK 5
Spark
Welcome to module 5, Introduction to Spark, this week we will focus on the Apache Spark cluster computing framework, an important contender of Hadoop MapReduce in the Big Data Arena.
Spark provides great performance advantages over Hadoop MapReduce,especially...
10 videos, 4 readings
Graded: Spark Lesson 1
Graded: Spark Lesson 2
Graded: Simple Join in Spark
Graded: Spark Lesson 3
Graded: Advanced Join in Spark
FAQs
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University of California, San Diego
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
Pricing
| Audit | Purchase Course | |
|---|---|---|
| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
| Receive a final grade | Not available | Available |
| Earn a shareable Course Certificate | Not available | Available |
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