C# Training Classes in Lansing, Michigan

Hartmann Software Group C# Training

Learn C# in Lansing, Michigan and surrounding areas via our hands-on, expert led courses. All of our classes are offered on an onsite, online and public instructor led basis. Here is a list of our current C# related training offerings in Lansing, Michigan: C# Training

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Lansing  Upcoming Instructor Led Online and Public C# Training Classes
20483: Programming in C# Training/Class 7 October, 2019 - 11 October, 2019 $2090
HSG Training Center
Lansing, Michigan
Hartmann Software Group Training Registration
ASP.NET Core MVC Training/Class 30 September, 2019 - 1 October, 2019 $790
HSG Training Center
Lansing, Michigan
Hartmann Software Group Training Registration

C# Training Catalog

cost: $ 2090length: 5 day(s)
cost: $ 790length: 2 day(s)

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Attempting to create an intelligent entry about Linux for such a wide ranging audience is a bit like trying to compare a presentation on quantum mechanics for physicists while being readable by somebody with a junior high school education.

If you are a *NIX expert, then I suggest you keep on reading so you know how to explain this world to mere mortals.

I called it *nix for a reason. It represents a family of thinking. It is not unlike the difference between the language C and C++. Are there differences between the two? Certainly. And it is not like the difference between COBOL and C.

Years ago when I ran my own vo-tech school I would teach the students there are only two things in life. MS and *NIX. A friend of mine, a genius developer in her own right was aghast.

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.

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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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

Tech Life in Michigan

Home of the Ford Motor Company and many other Fortune 500 and Fortune 1000 Companies, Michigan has a list of famous people that have made their mark on society. Famous Michiganians: Francis Ford Coppola film director; Henry Ford industrialist, Earvin Magic Johnson basketball player; Charles A. Lindbergh aviator; Madonna singer; Stevie Wonder singer; John T. Parsons inventor and William R. Hewlett inventor.
You cannot teach beginners top-down programming, because they don't know which end is up. C.A.R. Hoare  
other Learning Options
Software developers near Lansing 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 Michigan that offer opportunities for C# developers
Company Name City Industry Secondary Industry
Lear Corporation Southfield Manufacturing Automobiles, Boats and Motor Vehicles
TRW Automotive Holdings Corp. Livonia Manufacturing Automobiles, Boats and Motor Vehicles
Spartan Stores, Inc. Byron Center Retail Grocery and Specialty Food Stores
Steelcase Inc. Grand Rapids Manufacturing Furniture Manufacturing
Valassis Communications, Inc. Livonia Business Services Advertising, Marketing and PR
Autoliv, Inc. Auburn Hills Manufacturing Automobiles, Boats and Motor Vehicles
Cooper-Standard Automotive Group Novi Manufacturing Automobiles, Boats and Motor Vehicles
Penske Automotive Group, Inc. Bloomfield Hills Retail Automobile Dealers
Con-Way Inc. Ann Arbor Transportation and Storage Freight Hauling (Rail and Truck)
Meritor, Inc. Troy Manufacturing Automobiles, Boats and Motor Vehicles
Visteon Corporation Van Buren Twp Manufacturing Automobiles, Boats and Motor Vehicles
Affinia Group, Inc. Ann Arbor Manufacturing Automobiles, Boats and Motor Vehicles
Perrigo Company Allegan Healthcare, Pharmaceuticals and Biotech Pharmaceuticals
BorgWarner Inc. Auburn Hills Manufacturing Automobiles, Boats and Motor Vehicles
Auto-Owners Insurance Lansing Financial Services Insurance and Risk Management
DTE Energy Company Detroit Energy and Utilities Gas and Electric Utilities
Whirlpool Corporation Benton Harbor Manufacturing Tools, Hardware and Light Machinery
Herman Miller, Inc. Zeeland Manufacturing Furniture Manufacturing
Universal Forest Products Grand Rapids Manufacturing Furniture Manufacturing
Masco Corporation Inc. Taylor Manufacturing Concrete, Glass, and Building Materials
PULTEGROUP, INC. Bloomfield Hills Real Estate and Construction Real Estate & Construction Other
CMS Energy Corporation Jackson Energy and Utilities Energy and Utilities Other
Stryker Corporation Portage Healthcare, Pharmaceuticals and Biotech Medical Devices
General Motors Company (GM) Detroit Manufacturing Automobiles, Boats and Motor Vehicles
Kellogg Company Battle Creek Manufacturing Food and Dairy Product Manufacturing and Packaging
The Dow Chemical Company Midland Manufacturing Chemicals and Petrochemicals
Kelly Services, Inc. Troy Business Services HR and Recruiting Services
Ford Motor Company Dearborn Manufacturing Automobiles, Boats and Motor Vehicles

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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 Michigan 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 C# programming
  • Get your questions answered by easy to follow, organized C# experts
  • Get up to speed with vital C# 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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