IT Infrastructure Library Training Classes in San Antonio, Texas

Learn IT Infrastructure Library in San Antonio, Texas and surrounding areas via our hands-on, expert led courses. All of our classes either are offered on an onsite, online or public instructor led basis. Here is a list of our current IT Infrastructure Library related training offerings in San Antonio, Texas: IT Infrastructure Library Training

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IT Infrastructure Library Training Catalog

cost: $ 1,690length: 3 day(s)
cost: $ 1290length: 4 day(s)
cost: $ 2,690length: 5 day(s)
cost: $ 1,690length: 5 day(s)
cost: $ 1,690length: 5 day(s)
cost: $ 1,690length: 5 day(s)
cost: $ 1,690length: 5 day(s)
cost: $ 1670length: 3 day(s)
cost: $ 570length: 1 day(s)

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Unlike Java, Python does not have a string contains method.  Instead, use the in operator or the find method.  The in operator finds treats the string as a word list whereas the find method looks for substrings.  In the example shown below, 'is' is a substring of this but not a word by itself.  Therefore, find recoginizes 'is' in this while the in operator does not.

 

s = "This be a string"
if s.find("is") == -1:
    print "No 'is' here!"
else:
    print "Found 'is' in the string."
    
if "is" in s:
    print "No 'is' here!"
else:
    print "Found 'is' in the string."

#prints out the following:
Found 'is' in the string
No 'is' here!

Machine learning systems are equipped with artificial intelligence engines that provide these systems with the capability of learning by themselves without having to write programs to do so. They adjust and change programs as a result of being exposed to big data sets. The process of doing so is similar to the data mining concept where the data set is searched for patterns. The difference is in how those patterns are used. Data mining's purpose is to enhance human comprehension and understanding. Machine learning's algorithms purpose is to adjust some program's action without human supervision, learning from past searches and also continuously forward as it's exposed to new data.

The News Feed service in Facebook is an example, automatically personalizing a user's feed from his interaction with his or her friend's posts. The "machine" uses statistical and predictive analysis that identify interaction patterns (skipped, like, read, comment) and uses the results to adjust the News Feed output continuously without human intervention. 

Impact on Existing and Emerging Markets

The NBA is using machine analytics created by a California-based startup to create predictive models that allow coaches to better discern a player's ability. Fed with many seasons of data, the machine can make predictions of a player's abilities. Players can have good days and bad days, get sick or lose motivation, but over time a good player will be good and a bad player can be spotted. By examining big data sets of individual performance over many seasons, the machine develops predictive models that feed into the coach’s decision-making process when faced with certain teams or particular situations. 

General Electric, who has been around for 119 years is spending millions of dollars in artificial intelligence learning systems. Its many years of data from oil exploration and jet engine research is being fed to an IBM-developed system to reduce maintenance costs, optimize performance and anticipate breakdowns.

Over a dozen banks in Europe replaced their human-based statistical modeling processes with machines. The new engines create recommendations for low-profit customers such as retail clients, small and medium-sized companies. The lower-cost, faster results approach allows the bank to create micro-target models for forecasting service cancellations and loan defaults and then how to act under those potential situations. As a result of these new models and inputs into decision making some banks have experienced new product sales increases of 10 percent, lower capital expenses and increased collections by 20 percent. 

Emerging markets and industries

By now we have seen how cell phones and emerging and developing economies go together. This relationship has generated big data sets that hold information about behaviors and mobility patterns. Machine learning examines and analyzes the data to extract information in usage patterns for these new and little understood emergent economies. Both private and public policymakers can use this information to assess technology-based programs proposed by public officials and technology companies can use it to focus on developing personalized services and investment decisions.

Machine learning service providers targeting emerging economies in this example focus on evaluating demographic and socio-economic indicators and its impact on the way people use mobile technologies. The socioeconomic status of an individual or a population can be used to understand its access and expectations on education, housing, health and vital utilities such as water and electricity. Predictive models can then be created around customer's purchasing power and marketing campaigns created to offer new products. Instead of relying exclusively on phone interviews, focus groups or other kinds of person-to-person interactions, auto-learning algorithms can also be applied to the huge amounts of data collected by other entities such as Google and Facebook.

A warning

Traditional industries trying to profit from emerging markets will see a slowdown unless they adapt to new competitive forces unleashed in part by new technologies such as artificial intelligence that offer unprecedented capabilities at a lower entry and support cost than before. But small high-tech based companies are introducing new flexible, adaptable business models more suitable to new high-risk markets. Digital platforms rely on algorithms to host at a low cost and with quality services thousands of small and mid-size enterprises in countries such as China, India, Central America and Asia. These collaborations based on new technologies and tools gives the emerging market enterprises the reach and resources needed to challenge traditional business model companies.

Wondering why Cisco is teaching network engineers Python in addition to their core expertise?
 
Yes, arguably there are many other tools available to use to automate the network without writing any code. It is also true that when code is absolutely necessary, in most companies software developers will write the code for the network engineers. However, networks are getting progressively more sophisticated and the ability for network engineers to keep up with the rate of change, scale of networks, and processing of requirements is becoming more of a challenge with traditional methodologies. 
 
Does that mean that all network engineers have to become programmers in the future? Not completely, but having certain tools in your tool belt may be the deciding factor in new or greater career opportunities. The fact is that current changes in the industry will require Cisco engineers to become proficient in programming, and the most common programming language for this new environment is the Python programming language. Already there are more opportunities for those who can understand programming and can also apply it to traditional networking practices. 
 
Cisco’s current job boards include a search for a Sr. Network Test Engineer and for several Network Consulting Engineers, each with  "competitive knowledge" desired Python and Perl skills. Without a doubt, the most efficient network engineers in the future will be the ones who will be able to script their automated network-related tasks, create their own services directly in the network, and continuously modify their scripts. 
 
Whether you are forced to attend or are genuinely interested in workshops or courses that cover the importance of learning topics related to programmable networks such as Python, the learning curve at the very least will provide you with an understanding of Python scripts and the ability to be able to use them instead of the CLI commands and the copy and paste options commonly used.  Those that plan to cling to their CLI will soon find themselves obsolete.
 
As with anything new, learning a programming language and using new APIs for automation will require engineers to learn and master the skills before deploying widely across their network. The burning question is where to start and which steps to take next? 
 
In How Do I Get Started Learning Network Programmability?  Hank Preston – on the Cisco blog page suggest a three phase approach to diving into network programmability.
 
“Phase 1: Programming Basics
In this first phase you need to build a basic foundation in the programmability skills, topics, and technologies that will be instrumental in being successful in this journey.  This includes learning basic programming skills like variables, operations, conditionals, loops, etc.  And there really is no better language for network engineers to leverage today than Python.  Along with Python, you should explore APIs (particularly REST APIs), data formats like JSON, XML, and YAML. And if you don’t have one already, sign up for a GitHub account and learn how to clone, pull, and push to repos.
 
Phase 2: Platform Topics
Once you have the programming fundamentals squared away (or at least working on squaring them away) the time comes to explore the new platforms of Linux, Docker, and “the Cloud.”  As applications are moving from x86 virtualization to micro services, and now serverless, the networks you build will be extending into these new areas and outside of traditional physical network boxes.  And before you can intelligently design or engineer the networks for those environments, you need to understand how they basically work.  The goal isn’t to become a big bushy beard wearing Unix admin, but rather to become comfortable working in these areas.
 
Phase 3: Networking for Today and Tomorrow
Now you are ready to explore the details of networking in these new environments.  In phase three you will dive deep into Linux, container/Docker, cloud, and micro service networking.  You have built the foundation of knowledge needed to take a hard look at how networking works inside these new environments.  Explore all the new technologies, software, and strategies for implementing and segmenting critical applications in the “cloud native” age and add value to the application projects.”
 
Community resources: 
GitHub’s, PYPL Popularity of Programming Language lists Python as having grown 13.2% in demand in the last 5 years. 
Python in the  June 2018 TIOBE Index ranks as the fourth most popular language behind Java, C and C++. 
 
Despite the learning curve, having Python in your tool belt is without a question a must have tool.

On March 6 of this year, Microsoft's .NET Foundation released its third preview release of .NET Core 3 — which is its free and open-source framework for developing apps on Windows, MacOS and Linux — with an official release scheduled for later this year. This release brings a wealth of new features and enhancements. This includes the following: 
 
1. Windows Desktop Support
 
One of the biggest additions to version 3.0 of the framework is the ability to develop Windows desktop applications. The new Windows Desktop component lets you build applications using either the Windows Presentation Foundation (WPF) graphical subsystem or the Windows Forms graphical class library. You can also use Windows UI XAML Library (WinUI) controls in your applications. 
 
The Windows Desktop component is only supported and included on Windows installs. 
 
2. Support for C# 8
 
The new framework has support for C# 8, which includes not only the ability to create asynchronous steams but features such as: 
 
Index and Range data types
Using declarations
Switch expressions
 
The Index and Range data types make array manipulation easier, while Using declarations ensure that your objects get disposed once they are out of scope. Finally, Switch expressions extend Switch statements by allowing you to return a value. 
 
3. IEEE Floating-Point Improvements
 
The new framework includes floating point APIs that comply with IEEE 754-2008. This includes fixes to both formatting and parsing as well as new Math APIs such as: 
 
BitIncrement/BitDecrement
MaxMagnitude/MinMagnitude
ILogB
ScaleB
Log2
FusedMultiplyAdd
CopySign
 
4. Support for Performance-Oriented CPU Instructions
 
The new framework includes support for both SIMD and Bit Manipulation instruction sets, which can create significant performance boosts in certain situations, such as when you are processing data in parallel. 
 
5. Default Executables
 
With the new framework, you can now produce framework-dependent executables by default without having to use self-contained deployments. 
 
6. Local dotnet Tools
 
In the previous version of the framework, there was support for global dotnet tools. But the current version adds support for local tools as well. These tools are associated with a specific disk location, and this allows you to enable per-repository and per-project tooling. 
 
7. Support for MSIX Deployments
 
The new framework supports MSIX, which is a Windows app package format that you can use when deploying Windows desktop applications. 
 
8. Built-In and Fast JSON Support
 
In prior versions of the framework, you had to use Json.NET if you wanted JSON support in your application. The framework, though, now has built-in support that is not only fast but also has low allocation requirements. It also adds 3 new JSON types, which include: 
 
Utf8JsonReader
Utf8JsonWriter
JsonDocument
 
9. Cryptography Support
 
The new framework supports AES-GCM and AES-CCM ciphers. It also supports the importing and exporting of asymmetric public and private keys from a variety of formats without the need of an X.509 certificate. 
 
Platform Support
 
.NET Core 3 supports the following operating systems: 
 
Alpine: 3.8+
Debian: 9+
Fedora: 26+
macOS: 10.12+
openSUSE: 42.3+
RHEL: 6+
SLES: 12+
Ubuntu: 16.04+
Windows Clients: 7, 8.1, 10 (1607+)
Windows Servers: 2012 R2 SP1+
 
The framework further supports the following chips: 
 
x64 (Windows, macOS and Linux)
x86 (Windows)
ARM32 (Windows and Linux)
ARM64 (Linux)
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Tech Life in Texas

Austin may be considered the live music capital of the world but the field of technology is becoming the new norm in the The Lone Star State. Home to Dell and Compaq computers, there is a reason why central Texas is often referred to as the Silicon Valley of the south. It?s rated third on the charts of the top computer places in the United States with a social learning and training IT atmosphere. Adding the fact that Austin offers fairly inexpensive living costs for students, software developers may take note as they look to relocate.
I had discovered that learning something, no matter how complex, wasn't hard when I had a reason to want to know it. Homer H. Hickman
other Learning Options
Software developers near San Antonio have ample opportunities to meet like minded techie individuals, collaborate and expend their career choices by participating in Meet-Up Groups. The following is a list of Technology Groups in the area.
Fortune 500 and 1000 companies in Texas that offer opportunities for IT Infrastructure Library developers
Company Name City Industry Secondary Industry
Dr Pepper Snapple Group Plano Manufacturing Nonalcoholic Beverages
Western Refining, Inc. El Paso Energy and Utilities Gasoline and Oil Refineries
Frontier Oil Corporation Dallas Manufacturing Chemicals and Petrochemicals
ConocoPhillips Houston Energy and Utilities Gasoline and Oil Refineries
Dell Inc Round Rock Computers and Electronics Computers, Parts and Repair
Enbridge Energy Partners, L.P. Houston Transportation and Storage Transportation & Storage Other
GameStop Corp. Grapevine Retail Retail Other
Fluor Corporation Irving Business Services Management Consulting
Kimberly-Clark Corporation Irving Manufacturing Paper and Paper Products
Exxon Mobil Corporation Irving Energy and Utilities Gasoline and Oil Refineries
Plains All American Pipeline, L.P. Houston Energy and Utilities Gasoline and Oil Refineries
Cameron International Corporation Houston Energy and Utilities Energy and Utilities Other
Celanese Corporation Irving Manufacturing Chemicals and Petrochemicals
HollyFrontier Corporation Dallas Energy and Utilities Gasoline and Oil Refineries
Kinder Morgan, Inc. Houston Energy and Utilities Gas and Electric Utilities
Marathon Oil Corporation Houston Energy and Utilities Gasoline and Oil Refineries
United Services Automobile Association San Antonio Financial Services Personal Financial Planning and Private Banking
J. C. Penney Company, Inc. Plano Retail Department Stores
Energy Transfer Partners, L.P. Dallas Energy and Utilities Energy and Utilities Other
Atmos Energy Corporation Dallas Energy and Utilities Alternative Energy Sources
National Oilwell Varco Inc. Houston Manufacturing Manufacturing Other
Tesoro Corporation San Antonio Manufacturing Chemicals and Petrochemicals
Halliburton Company Houston Energy and Utilities Energy and Utilities Other
Flowserve Corporation Irving Manufacturing Tools, Hardware and Light Machinery
Commercial Metals Company Irving Manufacturing Metals Manufacturing
EOG Resources, Inc. Houston Energy and Utilities Gasoline and Oil Refineries
Whole Foods Market, Inc. Austin Retail Grocery and Specialty Food Stores
Waste Management, Inc. Houston Energy and Utilities Waste Management and Recycling
CenterPoint Energy, Inc. Houston Energy and Utilities Gas and Electric Utilities
Valero Energy Corporation San Antonio Manufacturing Chemicals and Petrochemicals
FMC Technologies, Inc. Houston Energy and Utilities Alternative Energy Sources
Calpine Corporation Houston Energy and Utilities Gas and Electric Utilities
Texas Instruments Incorporated Dallas Computers and Electronics Semiconductor and Microchip Manufacturing
SYSCO Corporation Houston Wholesale and Distribution Grocery and Food Wholesalers
BNSF Railway Company Fort Worth Transportation and Storage Freight Hauling (Rail and Truck)
Affiliated Computer Services, Incorporated (ACS), a Xerox Company Dallas Software and Internet E-commerce and Internet Businesses
Tenet Healthcare Corporation Dallas Healthcare, Pharmaceuticals and Biotech Hospitals
XTO Energy Inc. Fort Worth Energy and Utilities Gasoline and Oil Refineries
Group 1 Automotive Houston Retail Automobile Dealers
ATandT Dallas Telecommunications Telephone Service Providers and Carriers
Anadarko Petroleum Corporation Spring Energy and Utilities Gasoline and Oil Refineries
Apache Corporation Houston Energy and Utilities Gasoline and Oil Refineries
Dean Foods Company Dallas Manufacturing Food and Dairy Product Manufacturing and Packaging
American Airlines Fort Worth Travel, Recreation and Leisure Passenger Airlines
Baker Hughes Incorporated Houston Energy and Utilities Gasoline and Oil Refineries
Continental Airlines, Inc. Houston Travel, Recreation and Leisure Passenger Airlines
RadioShack Corporation Fort Worth Computers and Electronics Consumer Electronics, Parts and Repair
KBR, Inc. Houston Government International Bodies and Organizations
Spectra Energy Partners, L.P. Houston Energy and Utilities Gas and Electric Utilities
Energy Future Holdings Dallas Energy and Utilities Energy and Utilities Other
Southwest Airlines Corporation Dallas Transportation and Storage Air Couriers and Cargo Services

training details locations, tags and why hsg

A successful career as a software developer or other IT professional requires a solid understanding of software development processes, design patterns, enterprise application architectures, web services, security, networking and much more. The progression from novice to expert can be a daunting endeavor; this is especially true when traversing the learning curve without expert guidance. A common experience is that too much time and money is wasted on a career plan or application due to misinformation.

The Hartmann Software Group understands these issues and addresses them and others during any training engagement. Although no IT educational institution can guarantee career or application development success, HSG can get you closer to your goals at a far faster rate than self paced learning and, arguably, than the competition. Here are the reasons why we are so successful at teaching:

  • Learn from the experts.
    1. We have provided software development and other IT related training to many major corporations in Texas since 2002.
    2. Our educators have years of consulting and training experience; moreover, we require each trainer to have cross-discipline expertise i.e. be Java and .NET experts so that you get a broad understanding of how industry wide experts work and think.
  • Discover tips and tricks about IT Infrastructure Library programming
  • Get your questions answered by easy to follow, organized IT Infrastructure Library experts
  • Get up to speed with vital IT Infrastructure Library programming tools
  • Save on travel expenses by learning right from your desk or home office. Enroll in an online instructor led class. Nearly all of our classes are offered in this way.
  • Prepare to hit the ground running for a new job or a new position
  • See the big picture and have the instructor fill in the gaps
  • We teach with sophisticated learning tools and provide excellent supporting course material
  • Books and course material are provided in advance
  • Get a book of your choice from the HSG Store as a gift from us when you register for a class
  • Gain a lot of practical skills in a short amount of time
  • We teach what we know…software
  • We care…
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