XML Training Classes in Madison, Wisconsin

Learn XML in Madison, Wisconsin 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 XML related training offerings in Madison, Wisconsin: XML Training

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XML Training Catalog

cost: $ 790length: 2 day(s)
cost: $ 1750length: 3 day(s)
cost: $ 1290length: 3 day(s)
cost: $ 1190length: 3 day(s)
cost: $ 1190length: 3 day(s)
cost: $ 1750length: 5 day(s)
cost: $ 790length: 2 day(s)
cost: $ 1590length: 4 day(s)
cost: $ 1750length: 3 day(s)
cost: $ 790length: 2 day(s)
cost: $ 390length: 1 day(s)
cost: $ 790length: 2 day(s)

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Python and Ruby, each with roots going back into the 1990s, are two of the most popular interpreted programming languages today. Ruby is most widely known as the language in which the ubiquitous Ruby on Rails web application framework is written, but it also has legions of fans that use it for things that have nothing to do with the web. Python is a big hit in the numerical and scientific computing communities at the present time, rapidly displacing such longtime stalwarts as R when it comes to these applications. It too, however, is also put to a myriad of other uses, and the two languages probably vie for the title when it comes to how flexible their users find them.

A Matter of Personality...


That isn't to say that there aren't some major, immediately noticeable, differences between the two programming tongues. Ruby is famous for its flexibility and eagerness to please; it is seen by many as a cleaned-up continuation of Perl's "Do What I Mean" philosophy, whereby the interpreter does its best to figure out the meaning of evening non-canonical syntactic constructs. In fact, the language's creator, Yukihiro Matsumoto, chose his brainchild's name in homage to that earlier language's gemstone-inspired moniker.

Python, on the other hand, takes a very different tact. In a famous Python Enhancement Proposal called "The Zen of Python," longtime Pythonista Tim Peters declared it to be preferable that there should only be a single obvious way to do anything. Python enthusiasts and programmers, then, generally prize unanimity of style over syntactic flexibility compared to those who choose Ruby, and this shows in the code they create. Even Python's whitespace-sensitive parsing has a feel of lending clarity through syntactical enforcement that is very much at odds with the much fuzzier style of typical Ruby code.

For example, Python's much-admired list comprehension feature serves as the most obvious way to build up certain kinds of lists according to initial conditions:

a = [x**3 for x in range(10,20)]
b = [y for y in a if y % 2 == 0]

first builds up a list of the cubes of all of the numbers between 10 and 19 (yes, 19), assigning the result to 'a'. A second list of those elements in 'a' which are even is then stored in 'b'. One natural way to do this in Ruby is probably:

a = (10..19).map {|x| x ** 3}
b = a.select {|y| y.even?}

but there are a number of obvious alternatives, such as:

a = (10..19).collect do |x|
x ** 3
end

b = a.find_all do |y|
y % 2 == 0
end

It tends to be a little easier to come up with equally viable, but syntactically distinct, solutions in Ruby compared to Python, even for relatively simple tasks like the above. That is not to say that Ruby is a messy language, either; it is merely that it is somewhat freer and more forgiving than Python is, and many consider Python's relative purity in this regard a real advantage when it comes to writing clear, easily understandable code.

And Somewhat One of Performance

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.

Java still has its place in the world of software development, but is it quickly becoming obsolete by the more dynamically enabled Python programming language? The issue is hotly contested by both sides of the debate. Java experts point out that Java is still being developed with more programmer friendly updates. Python users swear that Java can take up to ten times longer to develop. Managers that need to make the best decision for a company need concrete information so that an informed and rational decision can be made.

First, Java is a static typed language while Python is dynamically typed. Static typed languages require that each variable name must be tied to both a type and an object. Dynamically typed languages only require that a variable name only gets bound to an object. Immediately, this puts Python ahead of the game in terms of productivity since a static typed language requires several elements and can make errors in coding more likely.

Python uses a concise language while Java uses verbose language. Concise language, as the name suggests, gets straight to the point without extra words. Removing additional syntax can greatly reduce the amount of time required to program.  A simple call in Java, such as the ever notorious "Hello, World" requires three several lines of coding while Python requires a single sentence. Java requires the use of checked exceptions. If the exceptions are not caught or thrown out then the code fails to compile. In terms of language, Python certainly has surpassed Java in terms of brevity.

Additionally, while Java's string handling capabilities have improved they haven't yet matched the sophistication of Python's. Web applications rely upon fast load times and extraneous code can increase user wait time. Python optimizes code in ways that Java doesn't, and this can make Python a more efficient language. However, Java does run faster than Python and this can be a significant advantage for programmers using Java. When you factor in the need for a compiler for Java applications the speed factor cancels itself out leaving Python and Java at an impasse.

While a programmer will continue to argue for the language that makes it easiest based on the programmer's current level of knowledge, new software compiled with Python takes less time and provides a simplified coding language that reduces the chance for errors. When things go right, Java works well and there are no problems. However, when errors get introduced into the code, it can become extremely time consuming to locate and correct those errors. Python generally uses less code to begin with and makes it easier and more efficient to work with.

Ultimately, both languages have their own strengths and weaknesses. For creating simple applications, Python provides a simpler and more effective application. Larger applications can benefit from Java and the verbosity of the code actually makes it more compatible with future versions. Python code has been known to break with new releases. Ultimately, Python works best as a type of connecting language to conduct quick and dirty work that would be too intensive when using Java alone. In this sense, Java is a low-level implementation language. While both languages are continuing to develop, it's unlikely that one language will surpass the other for all programming needs in the near future.

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)
 Jump to top
 

Tech Life in Wisconsin

Fun Facts and stats: • Wisconsin’s nickname is the Badger State. • In 1882 the first hydroelectric plant in the United States was built at Fox River. • The first practical typewriter was designed in Milwaukee in 1867. • The nation's first kindergarten was established in Watertown in 1856. Its first students were local German-speaking youngsters. • The Republican Party was founded in Ripon in 1854.
...You can't unlearn something, even if you want to. You know what you know. Sarah Dessen
other Learning Options
Software developers near Madison 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 Wisconsin that offer opportunities for XML developers
Company Name City Industry Secondary Industry
We Energies Milwaukee Energy and Utilities Gas and Electric Utilities
Bemis Company, Inc. Neenah Manufacturing Plastics and Rubber Manufacturing
Regal Beloit Corporation Beloit Manufacturing Tools, Hardware and Light Machinery
Manitowoc Company, Inc Manitowoc Manufacturing Heavy Machinery
Briggs and Stratton Corporation Milwaukee Manufacturing Tools, Hardware and Light Machinery
Mortgage Guaranty Insurance Corporation (MGIC) Milwaukee Financial Services Lending and Mortgage
A.O. Smith Corporation Milwaukee Manufacturing Tools, Hardware and Light Machinery
Sentry Insurance Stevens Point Financial Services Insurance and Risk Management
Rockwell Automation, Inc. Milwaukee Manufacturing Tools, Hardware and Light Machinery
Bucyrus International, Inc. South Milwaukee Manufacturing Heavy Machinery
Diversey, Inc. Sturtevant Manufacturing Chemicals and Petrochemicals
Alliant Energy Corporation Madison Energy and Utilities Gas and Electric Utilities
Plexus Corp. Neenah Manufacturing Manufacturing Other
Spectrum Brands Holdings, Inc. Madison Manufacturing Tools, Hardware and Light Machinery
Kohl's Corporation Menomonee Falls Retail Department Stores
Snap-on Tools, Inc. Kenosha Manufacturing Tools, Hardware and Light Machinery
Fiserv, Inc. Brookfield Software and Internet Data Analytics, Management and Storage
CUNA Mutual Group Madison Financial Services Insurance and Risk Management
Oshkosh Corporation Oshkosh Manufacturing Heavy Machinery
Modine Manufacturing Company Racine Manufacturing Manufacturing Other
Northwestern Mutual Life Insurance Company Milwaukee Financial Services Insurance and Risk Management
Joy Global Inc. Milwaukee Manufacturing Heavy Machinery
Harley-Davidson, Inc. Milwaukee Manufacturing Automobiles, Boats and Motor Vehicles
American Family Insurance Madison Financial Services Insurance and Risk Management
Johnson Controls, Inc. Milwaukee Manufacturing Heavy Machinery
ManpowerGroup Milwaukee Business Services HR and Recruiting Services

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the hartmann software group advantage
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 Wisconsin 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 XML programming
  • Get your questions answered by easy to follow, organized XML experts
  • Get up to speed with vital XML 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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