Linux Unix Training Classes in Winnipeg, Canada

Learn Linux Unix in Winnipeg, Canada 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 Linux Unix related training offerings in Winnipeg, Canada: Linux Unix Training

We offer private customized training for groups of 3 or more attendees.
Winnipeg  Upcoming Instructor Led Online and Public Linux Unix Training Classes
ANSIBLE Training/Class 18 May, 2020 - 20 May, 2020 $1990
HSG Training Center
Winnipeg, Canada
Hartmann Software Group Training Registration
Linux Troubleshooting Training/Class 18 May, 2020 - 22 May, 2020 $2290
HSG Training Center
Winnipeg, Canada
Hartmann Software Group Training Registration
Enterprise Linux System Administration Training/Class 20 April, 2020 - 24 April, 2020 $2190
HSG Training Center
Winnipeg, Canada
Hartmann Software Group Training Registration
Docker Training/Class 27 April, 2020 - 29 April, 2020 $1690
HSG Training Center
Winnipeg, Canada
Hartmann Software Group Training Registration
LINUX PERFORMANCE TUNING AND ANALYSIS Training/Class 1 June, 2020 - 4 June, 2020 $2490
HSG Training Center
Winnipeg, Canada
Hartmann Software Group Training Registration
DOCKER WITH KUBERNETES ADMINISTRATION Training/Class 13 April, 2020 - 17 April, 2020 $2490
HSG Training Center
Winnipeg, Canada
Hartmann Software Group Training Registration
RED HAT SATELLITE V6 (FOREMAN/KATELLO) ADMINISTRATION Training/Class 6 July, 2020 - 9 July, 2020 $2590
HSG Training Center
Winnipeg, Canada
Hartmann Software Group Training Registration
ENTERPRISE LINUX HIGH AVAILABILITY CLUSTERING Training/Class 3 August, 2020 - 6 August, 2020 $2590
HSG Training Center
Winnipeg, Canada
Hartmann Software Group Training Registration
HADOOP FOR SYSTEMS ADMINISTRATORS Training/Class 16 November, 2020 - 18 November, 2020 $1890
HSG Training Center
Winnipeg, Canada
Hartmann Software Group Training Registration
LINUX SHELL SCRIPTING Training/Class 28 May, 2020 - 29 May, 2020 $990
HSG Training Center
Winnipeg, Canada
Hartmann Software Group Training Registration

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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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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.

Being treated like a twelve year old at work by a Tasmanian-devil-manager and not sure what to do about it? It is simply a well-known fact that no one likes to be micro managed. Not only do they not like to be micro managed, but tend to quit for this very reason. Unfortunately the percentage of people leaving their jobs for this reason is higher that you would imagine. Recently, an employee retention report conducted by TINYpulse, an employee engagement firm, surveyed 400 full-time U.S. employees concluded that, "supervisors can make or break employee retention."

As companies mature, their ability to manage can be significant to their bottom line as employee morale, high staff turnover and the cost of training new employees can easily reduce productivity and consequently client satisfaction.  In many cases, there is a thin line between effective managing and micro managing practices. Most managers avoid micro managing their employees. However, a decent percentage of them have yet to find effective ways to get the most of their co-workers.  They trap themselves by disempowering people's ability to do their work when they hover over them and create an unpleasant working environment. This behavior may come in the form of incessant emailing, everything having to be done a certain way (their way), desk hovering, and a need to control every part of an enterprise, no matter how small.

Superimpose the micro manager into the popular practice of Agile-SCRUM methodology and you can imagine the creative ways they can monitor everything in a team, situation, or place. Although, not always a bad thing, excessive control, can lead to burnout of managers and teams alike.  As predicted, agile project management has become increasingly popular in the last couple of decades in project planning, particularly in software development.  Agile methodology when put into practice, especially in IT, can mean releasing faster functional software than with the traditional development methods. When done right, it enables users to get some of the business benefits of the new software faster as well as enabling the software team to get rapid feedback on the software's scope and direction.

Despite its advantages, most organizations have not been able to go “all agile” at once. Rather, some experiment with their own interpretation of agile when transitioning.  A purist approach for instance, can lead to an unnecessarily high agile project failure, especially for those that rely on tight controls, rigid structures and cost-benefit analysis.  As an example, a premature and rather rapid replacement of traditional development without fully understating the implications of the changeover process or job roles within the project results in failure for many organizations.  

With the rise of the smart phone, many people who have long seen themselves as non-gamers have began to download and play to occupy themselves throughout the day. If you're a game developer who has a history of writing your code in C#, then perhaps this still emerging market is something you should consider taking advantage of. This, however, will require the familiarization with other programming languages.

One option for moving away from the C# language is to learn Java. Java is the programming used for apps on the android platform, billions of phones run on this programming language.

If you want to break into the android market, then learning Java is an absolute must.

There are both some pros and some cons to learning java. Firstly, if you already know C# or other languages and understand how they work, then java will be relatively easy to learn due to having similar, but quite simplified, syntax to C-based languages, the class library is large and standardized, but also very well written, and you might find that it will improve the performance and portability of your creations. Not to mention, learning java opens you up to the entirety of the android app and game market, a very large and still growing market that would otherwise stay closed off to you. That's too much ad and sale money to risk missing out on.

The few cons that come with learning the language is that, when coming from other languages, the syntax may take some getting used to. This is true for most languages. The other problem is that you must be careful with the specifics of how you write your code. While java can be written in a very streamlined fashion, it's also possible to write working, but bulky, code that will slow down your programs. Practice makes perfect, and the knowledge to avoid such pitfalls within the language.

If you wish to develop for the iOS on the other hand, knowledge of Objective C is required. The most compelling reason to learn Objective C is the market that it will open you up to. According to the website AndroidAuthority.com, in the article "Google play vs. Apple app store", users of iPhones and other iOS devices are much more likely to spend money on apps rather than downloading free ones.

Though learning Objective C might be a far jump from someone who currently writes in C#, it's certainly learn-able with a little bit of practice.

 

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What are a few unique pieces of career advice that nobody ever mentions?

Good non-programmer jobs for people with software developer experience

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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 Canada 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 Linux Unix programming
  • Get your questions answered by easy to follow, organized Linux Unix experts
  • Get up to speed with vital Linux Unix 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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