Microsoft Development Training Classes in Charleston, West Virginia

Learn Microsoft Development in Charleston, WestVirginia 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 Microsoft Development related training offerings in Charleston, West Virginia: Microsoft Development Training

We offer private customized training for groups of 3 or more attendees.

Microsoft Development Training Catalog

cost: $ 790length: 2 day(s)
cost: $ 2600length: 6 day(s)
cost: $ 1685length: 4 day(s)

.NET Classes

Azure Classes

cost: $ 1290length: 3 day(s)
cost: $ 825length: 2 day(s)

BizTalk Server Classes

cost: $ 2090length: 3 day(s)
cost: $ 2090length: 3 day(s)

Cloud Classes

Foundations of Web Design & Web Authoring Classes

JavaScript Classes

System Center Classes

cost: $ 890length: 2 day(s)

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In programming, memory leaks are a common issue, and it occurs when a computer uses memory but does not give it back to the operating system. Experienced programmers have the ability to diagnose a leak based on the symptoms. Some believe every undesired increase in memory usage is a memory leak, but this is not an accurate representation of a leak. Certain leaks only run for a short time and are virtually undetectable.

Memory Leak Consequences

Applications that suffer severe memory leaks will eventually exceed the memory resulting in a severe slowdown or a termination of the application.

How to Protect Code from Memory Leaks?

Preventing memory leaks in the first place is more convenient than trying to locate the leak later. To do this, you can use defensive programming techniques such as smart pointers for C++.  A smart pointer is safer than a raw pointer because it provides augmented behavior that raw pointers do not have. This includes garbage collection and checking for nulls.

If you are going to use a raw pointer, avoid operations that are dangerous for specific contexts. This means pointer arithmetic and pointer copying. Smart pointers use a reference count for the object being referred to. Once the reference count reaches zero, the excess goes into garbage collection. The most commonly used smart pointer is shared_ptr from the TR1 extensions of the C++ standard library.

Static Analysis

The second approach to memory leaks is referred to as static analysis and attempts to detect errors in your source-code. CodeSonar is one of the effective tools for detection. It provides checkers for the Power of Ten coding rules, and it is especially competent at procedural analysis. However, some might find it lagging for bigger code bases.

How to Handle a Memory Leak

For some memory leaks, the only solution is to read through the code to find and correct the error. Another one of the common approaches to C++ is to use RAII, which an acronym for Resource Acquisition Is Initialization. This approach means associating scoped objects using the acquired resources, which automatically releases the resources when the objects are no longer within scope. RAII has the advantage of knowing when objects exist and when they do not. This gives it a distinct advantage over garbage collection. Regardless, RAII is not always recommended because some situations require ordinary pointers to manage raw memory and increase performance. Use it with caution.

The Most Serious Leaks

Urgency of a leak depends on the situation, and where the leak has occurred in the operating system. Additionally, it becomes more urgent if the leak occurs where the memory is limited such as in embedded systems and portable devices.

To protect code from memory leaks, people have to stay vigilant and avoid codes that could result in a leak. Memory leaks continue until someone turns the system off, which makes the memory available again, but the slow process of a leak can eventually prejudice a machine that normally runs correctly.

 

Related:

The Five Principles of Performance

In Demand IT Skills

The future looks just as bright for information technology as it did ten years ago when this career field started growing in huge numbers due to major internet technological advances and the popularity of mobile devices such as the smartphone and eReaders like Amazon’s Kindle.  In classrooms and libraries across the nation, information technology has become instrumental in the way students learn and the way teachers give lessons, and thanks to online education more adults have access to a better education without incurring a lot of debt. Needles to say, the need for qualified workers in information technology will continue in times to come. Some of the technological careers that are rapidly growing in popularity in the last decade are a direct reflection of current trends.

 

Information Technology Managers

The information technology manager is responsible for handling all computer activities for a business and performs upgrades on computer software and hardware, installs new security features on computers, creates budgets and goals for the IT department, supervises other IT employees and troubleshoots computers when needed. According to the Bureau of Labor Statistics, there were 332,700 information technology management jobs filled in 2012 and a majority of these positions were in the computer systems sector. Most information technology managers hold a bachelor's degree in computer science or information technology, and a growing number of employers prefer a graduate degree. The job growth is expected to grow at 15% between now and 2022.

Mobile Application Developers

This job will grow by leaps and bounds as millions of people continue to purchase mobile devices and download apps for business and entertainment purposes. It creates expanded opportunities for those who want to become mobile application developers. A mobile application developer often works with other developers to create mobile-friendly apps or mobile-friendly versions of business websites for consumers. The developer may have his own firm or he may be employed with a larger company, and he will need to understand the basics of web design and different kinds of codes to succeed in this career. The Bureau of Labor Statistics states that the job growth is expected to be at 28% by 2020.

Health Information Technology

Another fast growing sector within information technology is health information technology and there are various jobs to choose from. You can work with health insurance providers and your duties would include processing patients' insurance claims and managing patients' insurance information using a computer database. Another option is to work as a medical biller in a doctor's office preparing patient’s invoices. The good thing about these jobs is that you do not need a four-year degree to get the training; you can obtain a two-year associates degree or a certificate in health information technology.

Search Engine Optimization Consultant

This is an important information technology career because most businesses have websites and if these websites are going to receive high traffic from visitors and earn profit, proper search engine optimization is necessary. The SEO consultant's job is to ensure that a business website gets high rankings on the major search engines and plenty of traffic from visitors. A good SEO consultant at a minimum will know how to research keywords effectively and implement these into the website's content based on the website's theme and he would utilize web analytics as part of the job. An SEO consultant may work on a freelance basis or be employed with an advertising company as an example.

Best Cities for Technology Careers

If you're thinking about relocating for your career, here are some of the best cities currently for information technology jobs listed in Forbes

 

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.

Tech Life in West Virginia

The state is noted for its mountains and diverse topography, which may be the reason for resident?s median age of forty which is the oldest population of any state. West Virginia's nickname is the Mountain State and its motto is "Mountaineers Are Always Free." It was the first state to have a sales tax that became effective in July of 1921. The largest private employers in this state is Walmart, West Virginia United Health System, Charleston Area Medical Center, Kroger, Consol Energy, Mylan Pharmaceuticals, and Lowe?s
You are drowning in information but starved for knowledge. ~ John Naisbitt

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 West Virginia 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 Microsoft Development programming
  • Get your questions answered by easy to follow, organized Microsoft Development experts
  • Get up to speed with vital Microsoft Development 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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