PRZEMYSŁAW
SZUFEL, PHD
dr Przemysław Szufel

  pszufe @ gmail.com

Cloud Computing

I participate in several projects related to development of new cloud computing methods and toosl. My special focus is on cost-optimization of data processing and computations in the cloud. As far as technology is concirned I am particularly applying cloud for Machine Learning/Big Data analytics as well as high performance computing (HPC). More details can be found below:

Blog - introduction to cloud computing

I am running a blog where I try to present short introductory tutorials for student and first-time cloud users on how to accomplish basic tasks in the cloud.

Training

I can personally offer several trainings in cloud computing and machine learning. The trainings can be delivered either in Polish or English.

Optimizing cloud computing costs

The goal of the training is to present methods and tools for cost optimization of cloud infrastructure.
During the training mechanism that lead to decreatse in TCO of IT infrstrucure will be discussed. In particular the cloud computing approach will be compared with traditional on-site infrastructure.
It should be noted that the biggest savings can be accomplished by adopting the data processing models and the infrastructure to the cloud computing model. Hence, a large part of the training will focus on optimization of cloud infrastructure design.
The participation in the course is recommended for CIOs as well as persons in charge of IT infrastructure costs.
Duration of training: 6h.
  1. Cloud computing introduction
    • Virtual servers in the cloud
    • Virtual data storage (block and key-value storage)
    • Database management services (SQL and NoSQL)
    • Programmable infrastructure
  2. Cloud computing cost mechanisms
  3. Cloud computing costs optimization
    • Monitoring cloud infrastructure
    • Virtual machines - disposable computing resource in IT infrastructure
    • Infrastructure autoscaling
    • Reserved instances
    • Spot market for cloud computing resources (AWS EC2 spot)

Introduction to cloud computing

An introductory course for cloud computing. The course focuses on designing new cloud infrastructure as well as moving existing on-site infrastructure to the cloud.
Duration of training: 4-8h

Mastering Amazon Web Services API

This is an introductory course on programmable infrastructure in the cloud. Participation in the course is particularly recommended for programmers and system administrators in companies planning to introduce cloud computing architecture.
The course can be based on Python 2/3 (boto library) or Java (AWS SDK for Java) - depending on your company needs.

Duration of training: 6h

Cloud computing with Apache Spark

The goal of the training is to present Apache Spark - a leading big data analytics solutions. During the course technological aspects will be illustrated with several use case scenarios.
The course can be based on Python, Scala or Java (depending on your needs)
Duration of training: 8h

Cloud security

The goal of the training is to present aspects of cloud security along with the best practices. The training is based on Amazon Web Services cloud platform.
Duration of training: 4h

Python & data analytics in the cloud

Duration of training: 2 days.
  1. Python programmer's enviroment – Anaconda/Spyder
  2. Python ABC
    • Data structures - list, dictionaries and tuples
    • Functions
    • Functional programming in Python
  3. Data import and export
    • working with CSV files
    • working with JSON data
    • working with relational databases (Oracle, MS SQL)
    • downloading data from the web
    • Date and time processing
  4. Where the Python language is heading - comparing Python 2 and Python 3
  5. Numerical computing and machine learning
    • Introduction to the numpy package
    • Introduction to the pandas and sci-kit learn packages
    • Data visualisation with matplotlib
    • Regression models
    • Classification models
    • Simulation models
  6. Efficient Python progamming
    • Speed of Python code execution
    • Vector computing with numpy
    • Parallel computing (multiprocessing with Python)
  7. Python in the AWS cloud
    • Python on EC2 instances
    • Introduction to grid-computing with Python
    • Computing clusters with Python - StarCluster

New methods and tools for cloud computing

I am taking part in several projects that lead to dicrease in cloud computing costs while simultaneously increasing accessibility to the cloud technology.

  1. Amazon Web Services EC2 spot instance cost optimization: On optimization of simulation execution on Amazon EC2 spot market

  2. Algorithms for distributed cloud computing: Asynchronous Knowledge Gradient Policy for Ranking and Selection

  3. Moving existing HPC enviroments and toolsets to the cloud: D-MASON in the cloud

  4. Creation of new tools for cloud computing: SOF: Zero Configuration Simulation Optimization Framework on the Cloud