Requirements: This course assumes that you have basic knowledge of Python. If you want to attend the session, but don't yet know Python please try sections 1-9 of the Codeacademy Python tutorial here.

Topics Covered:

Part I (Morning):

Jupyter Notebook Overview
Input/Output in Python
Basic Math
Indexing/Array Operations
Plotting
Fitting Plots

Part II (Afternoon):

Some Basic Statistics
Signal Processing
Ordinary Differential Equations
Pandas Crash Course
Gotchas and Optmization

Required Materials are one of the following:

Download and run a pre-built virtual machine. This requires ~7 GB of disk space total, but is easier for beginners. VirtualBox Virtual machine

A Python installation that includes: Anaconda or Miniconda is highly recommended Python Packages: NumPy, SciPy, Matplotlib, pandas, hdf5, pytables and jupyter notebook Course materials

PACE Big Data Training Workshop¶

Part One: Introduction to Hadoop and Spark [register here]

Time: Sept 28 08:30am-12:30pm

Location: Marcus Nano Rm 1116

Capacity: 30 people

The session will focus on introducing Hadoop and Spark cluster to beginner, the topic includes:

basic concepts used in MapReduce programming model
major components of a Hadoop cluster
how to get started with Hadoop on your own computer and with computing resources at TACC
introduce Spark programming models and how Spark can work with a Hadoop cluster
different ways to use Hadoop and Spark for analysis

Participants do not need have any particular programming background, but working knowledge of Linux operating system is preferred. Class includes 3 hours lecture and 1 hour hands-on.

No show fee $25.00 applies if you don't show up in the session without cancelling it 5 days before the class.

Part Two: Developing a scalable application with Spark [register here]

Time: Sept 28 1:30pm-5:30pm

Location: Marcus Nano Rm 1116

Capacity: 30 people

This session will focus on how to develop a scalable application with Spark programming model, the topic includes:

review Spark programming model
basic introduction to the Scala programming language
how to run a Spark application
keys features to make scalable application
how to get started development using Spark after the class

Participant is expected to have prior knowledge on the concept of Hadoop and Spark cluster, knowledge of any programming language is preferred but not required.Class includes 3 hours lecture and 1 hour hands-on.

No show fee $25.00 applies if you don't show up in the session without cancelling it 5 days before the class.

Part Three: Common Practices on Hadoop and Spark Ecosystem [register here]

Time: Sept 29 08:30am-12:30pm

Location: Marcus Nano Rm 1116

Capacity: 30 people

This session will focus on general practices for practical analysis problem, the topics include:

running batch jobs with different cluster deployment mode
running interactive jobs
explore existing libraries and applications including Hadoop streaming, MLlib, SparkSQL and Graph X
Using Hadoop/Spark with R and Python

Participants should have basic knowledge, experience and are comfortable with coding with knowledge of the Hadoop system, concepts of parallelism. Class includes 3 hours lecture and 1 hour hands-on.

No show fee $25.00 applies if you don't show up in the session without cancelling it 5 days before the class.

Part Four: Advanced Topic on Big Data Analysis [register here]

Time: Sept 29 01:30pm-05:30pm

Location: Marcus Nano Rm 1116

Capacity: 30 people

This session will cover more algorithm details and also provides a hands-on consultation for GT researchers' application, we will collect the use cases before the session, and walk through the selected use cases in details to demonstrate how to resolve the real world problem more efficiently.

Free MATLAB Optimization and Advanced Techniques¶

Develop your MATLAB skills by joining a MathWorks engineer for complimentary seminars to be held on Tuesday, August 19, 2014 in the Bill Moore Student Success Center, press room A. Register in advance here.

Location: Bill Moore Student Success Center, (behind Highland Bakery, next to the football stadium), second ‘R’ floor, press room A - August 19, 2014

Session 1: Optimizing and Accelerating your MATLAB Code 10:00 AM – 12:30 PM

In this session, we will demonstrate simple ways to improve and optimize your code that can boost execution speed. We will also address common pitfalls in writing MATLAB code, explore the use of the MATLAB Profiler to find bottlenecks, and introduce programming constructs to solve computationally and data-intensive problems on multicore computers, clusters and GPUs.

Leveraging the power of vector and matrix operations in MATLAB
Identifying and addressing bottlenecks in your code
Utilizing additional processing power available in multicore machines, clusters, and grids

Session 2: Advanced Programming Techniques in MATLAB 1:00 PM – 3:00 PM

This advanced class covers two important MATLAB topics:

How to handle memory efficiently
How to choose among the rich set of function types

Introduction to Parallel Programming with MPI and Open MPI¶

Location: Clough 325

Date: July 22, 2014

Time: 10am-2pm with 1 hour for lunch

How to register: trainsweb.gatech.edu/courses/searchupcoming#view-12498

Link to Slides

Link to Hands-On Activity

Introduction to Parallel Application Debugging and Profiling¶

Location: Clough 131

Date: June 17, 2014

Time: 10am-2pm with 1 hour for lunch

How to register: trainsweb.gatech.edu/courses/searchupcoming#view-12495

Link to Slides

Link to Hands-On Activity

A Quick Introduction to Python¶

Location: Clough 131

Date: June 24, 2014

Time: 10am-2pm with 1 hour for lunch

How to register: trainsweb.gatech.edu/courses/searchupcoming#view-12496

Materials: * For Windows * For MacOSX or Linux * Both files contain the same information. Each contains all of the examples covered in the class, plus some extras.

Notes:

This is a hands-on class, and is heavily example-based. Every concept introduced will be driven by examples that are executed. So, students are encouraged to bring laptops with
This class assumes some basic familiarity with programming concepts. Students should know the terms "variable", "function", "call a function", "argument", "string", and "integer" before coming to class.
This class will use the Canopy environment from Enthought for all examples.
- Canopy is free for academic users and can be downloaded here

Python for Scientific Computing¶

Location: Clough Undergraduate Learning Commons room 131 Date: July 8, 2014 Time: 10am-2pm with 1 hour for lunch Type: Hands-on, example driven How to register: trainsweb.gatech.edu/courses/searchupcoming#view-12497

Requirements: This course assumes that you have basic knowledge of Python. If you want to attend the session, but don't yet know Python try sections 1-9 of the Codecademy Python tutorial here.

Software Required: A full featured Python installation that includes NumPy, SciPy, Matplotlib, Pandas, and IPython. The Enthought Canopy product is recommended. Enthought Canopy is free for Academic Users.

Topics Covered:

Why use Python for Scientific Computing?
NumPy arrays - creation, slicing, transforming
Input and Output with Numpy
Basic NumPy Functionality
- Basic mathematics over NumPy arrays
- Basic Linear Algebra
Introduction to SciPy
- Curve Fitting
- ODE solving
- Statistics

Materials:

Python For Scientific Computing (Linux or Mac OSX)
Python For Scientific Computing (Windows)
Python For Basic Visualization (Linux or Mac OSX)
Python For Basic Visualization (Windows)

Linux 101¶

Location: Clough Undergraduate Learning Commons room 325

Date: July 10th, 2013

Time: 9:30am-11:30am

Location: Clough Undergraduate Learning Commons room 236

Date: Jan 10th, 2014

Time: 9:30am-11:30am

Location: Clough Undergraduate Learning Commons room 325

Date: Aug 1th, 2014

Time: 9:30am-11:30am

Location: Clough Undergraduate Learning Commons room 262

Date: Nov 14th, 2014

Time: 10:00am-12:00pm

Location: Clough Undergraduate Learning Commons room 278

Date: Jan 30th, 2015

Time: 10:00am-12:00pm

Requirements: This is introduction course on Linux, and its target audience is who without or with little Linux experience and need to start use PACE cluster for their research.

Topics Covered:

What is Linux?
Why use Linux?
Access to Linux
Common Commands on Linux
Editors
Shell Scripting
How to use man page
Linux Usage Tips

Materials: Link to Slides

Linux 102¶

Location: Clough Undergraduate Learning Commons room 127

Date: Nov 24th, 2015

Time: 10:00am-12:00pm

This is an intermediate level Linux course, the students are expected to have basic Linux knowledge, and students are welcome to check out introduction to Linux material here before attending this course.

The topic covers including:

How to setup Linux environment
Advance commands
Shell scripting
Simple package build

Link to Slides

Python for Data Analysis and Visualization¶

Location: Clough Undergraduate Learning Commons room 152

Date: July 24, 2013

Time: 9:30am-12:00pm

Requirements: This course assumes that you have basic knowledge of Python. If you want to attend the session, but don't yet know Python try sections 1-9 of the Codecademy Python tutorial here

Software Required: A full featured Python installation that includes NumPy, SciPy, Matplotlib and IPython. The Enthought Canopy product is recommended.Enthought Canopy is free for Academic Users.

Topics Covered:

Why use Python for Data Analysis?
Real world example US Baby Names 1880-2012
Data Manipulating skills:
Data loading, storage
Data Processing using Lists
Data Aggregation and Grouping
Plotting and visualization

Materials: Link to Slides

Data Analysis and Visualization with MATLAB¶

Date: August 7, 2013

Time: 9:00am - 11:00 am

Location: Stamps Student Center Theater

Registration: www.mathworks.com/seminars/GATech2013

Materials and Demo files (available on campus only): Matlab Demonstration Files (700MB)

Handling Large Data Sets in MATLAB¶

Date: August 7, 2013

Time: 12:00pm - 1:30 pm

Location: Stamps Student Center Theater

Registration: www.mathworks.com/seminars/GATech2013

Materials and Demo files (available on campus only): Matlab Demonstration Files (700MB)