Summer Experience

Big Data Analytics Summer Experience

Big data illustration

Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately society itself. Big Data analytics represents a new era of computing, where data in any format maybe processed and exploited to extract insights for industries and organizations to make informed decisions, whether that data is in-place, in motion or at-rest, in large volume, structured or unstructured.

This course will introduce several key Big Data processing and analytics technologies and teach practical skills and practices using Amazon Elastic MapReduce Web services and other valuable resources to bridge the gap between classroom learning and the real world.

A certificate is issued upon completion of the program.

2018 Big Data Analytics Summer School

July 8-29, 2018

Course Prerequisites: Basic knowledge of Linux and programming languages.

Topics include:

  • Introduction to Big Data, Big Data technologies, and Data Science
  • Hadoop, an open-source software framework supporting data-intensive distributed applications
  • MapReduce, a programming model for big data processing
  • Apache Spark, a fast and general engine for large-scale data processing
  • Mining Big Data with Spark MLlib, scalable machine learning and data mining libraries
  • Exploratory data analysis, clustering and summarization, recommender systems, predictive analytics
  • Classification with deep learning

Download the brochure for details 2018 Big Data Analytics Summer School 2018.

Visa information is available for international students.

University of Missouri Department of Electrical Engineering and Computer Science

2018 Big Data Analytics Summer School

July 8 – 29, 2018

Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately society itself. Big Data analytics represents a new era of computing, where data in any format maybe processed and exploited to extract insights for industries and organizations to make informed decisions, whether that data is in-place, in motion or at-rest, in large volume, structured or unstructured. This course will introduce several key Big Data processing and analytics technologies and teach practical skills and practices using Amazon Elastic MapReduce Web services and other valuable resources to bridge the gap between classroom learning and the real world. A certificate is issued upon completion of the program.

Prerequisites:

Basic knowledge of Linux and programming languages.

Topics

  • Introduction to Big Data, Big Data technologies, and Data Science
  • Hadoop, an open-source software framework supporting data-intensive distributed applications
  • MapReduce, a programming model for big data processing
  • Apache Spark, a fast and general engine for large-scale data processing
  • Mining Big Data with Spark MLlib, scalable machine learning and data mining libraries
  • Exploratory data analysis, clustering and summarization, recommender systems, predictiveanalytics
  • Classification with deep learning

Tentative Schedule

Lectures: 9am – 12pm

Labs/projects: 1:30pm – 4:30pm

Date Topic
July 9 Overview: Big Data Analytics, Big Data platforms, career paths
July 10-11 Hadoop overview; Hadoop Distributed File System (HDFS); Apache Spark overview; Amazon Web Services (AWS)
July 12-13 Introduction to Data Science; MapReduce; Amazon Elastic MapReduce (EMR)
July 16-17 Spark essentials; Spark MLlib for machine learning and data mining
July 18-19 Exploratory data analysis; Clustering and Summarization
July 20, 23 Recommender systems; Predictive Analytics
July 24-25 Classification with Deep Learning
July 26-27 Final project, presentation

Big Data Analytics Program Cost

The program will last three weeks (July 8-29, 2018).

Registration deadline: June 15, 2018.

OPTION 1:

This option includes the cost of the program/lab fees, administrative fees, housing in a campus residential hall, meals, transportation to/from Columbia airport, local trips, and social activities.

= $3,950 per student

Group Discounts

For a group of five or more students enrolled in the program, the cost of Option 1 is reduced to $3,800 per person in the group.

OPTION 2:

This option includes the cost of the program/lab fees, administrative fees, local trips, and social activities. For this option, the student would be responsible for their own transportation, housing, and meals.

= $2,900 per student

Please note: Neither option includes the cost of airfare.

Big Data Analytics Professors

This learning experience will be jointly instructed by Professors Yi Shang and Dong Xu of the MU Electrical Engineering and Computer Science Department.

Dr. Yi Shang

Yi Shang Headshot.Dr. Shang is a Professor, Associate Chair, and Director of Graduate Studies in the EECS Department. He has published more than 180 refereed papers in international journals and conferences in the fields of artificial intelligence, mobile and distributed computing, bioinformatics, and wireless sensor networks, and holds 6 U.S. patents. He has worked as a researcher at the University of Illinois at Urbana-Champaign and the renowned Xerox Palo Alto Research Center (PARC), Palo Alto, CA.  He has received research funding from the National Science Foundation, National Institutes of Health, the U.S. Army, DARPA, Microsoft, and Raytheon. Shang received his bachelor’s degree from the University of Science and Technology of China, master’s degree from the Chinese Academy of Sciences, and doctorate from University of Illinois at Urbana-Champaign in 1997. He is a lifetime member of the Association for Computing Machinery and senior member of the Institute of Electrical and Electronics Engineers.

Dr. Dong Xu

Dong Xu PortraitDong Xu is James C. Dowell Professor of the EECS Department, Director of Information Technology Program, with appointments in the Christopher S. Bond Life Sciences Center and the Informatics Institute at the University of Missouri-Columbia. He obtained his PhD from the University of Illinois, Urbana-Champaign in 1995 and did two years of postdoctoral work at the US National Cancer Institute. He was a Staff Scientist at Oak Ridge National Laboratory until 2003 before joining the University of Missouri, where he served as Department Chair of Computer Science during 2007-2016. He has published about 300 papers. He is Associate Editor-in-Chief of “IEEE/ACM Transactions on Computational Biology and Bioinformatics.” He was elected to the rank of American Association for the Advancement of Science (AAAS) Fellow in 2015.

Big Data Analytics Registration

Visa information for international students:

Students attending MU College of Engineering’s summer programs may enter the United States on a B-2 visa, so long as these courses do not count toward a degree. MU will not issue a summer student with an I-20 unless he or she is matriculating into the academic school year for Spring 2018. In that case, the I-20 paperwork will be issued through the MU International Center. A visitor visa (B-2) is sufficient to participate in our program. The classwork is deemed recreational because no credit is given for the program’s courses.

To enroll in MU College of Engineering’s Summer Programs, please submit:

  1. A completed Registration Form
  2. Payment

Students are admitted on a first-come, first-serve basis. To reserve your place in this program, please complete all paperwork. You will then be notified if you have been accepted into the program, and must submit payment by the end of the day on June 30.

To apply, email a completed registration form to Dr. Shang by the application deadline.

For questions, please call or email:

Yi Shang
Director of Graduate Studies
Electrical Engineering & Computer Science Department
207 Naka Hall
Dr. Yi Shang: 573-884-7794
University of Missouri, Columbia, MO 65211

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