C# Programming Training Classes in Albany, New York

Learn C# Programming in Albany, NewYork 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 C# Programming related training offerings in Albany, New York: C# Programming Training

We offer private customized training for groups of 3 or more attendees.
Albany  Upcoming Instructor Led Online and Public C# Programming Training Classes
Object-Oriented Programming in C# Rev. 6.1 Training/Class 15 September, 2025 - 19 September, 2025 $2090
HSG Training Center instructor led online
Albany, New York
Hartmann Software Group Training Registration

C# Programming Training Catalog

cost: $ 1190length: 3 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 1190length: 3 day(s)
cost: $ 890length: 2 day(s)
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cost: $ 2090length: 5 day(s)

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One of the biggest challenges faced by senior IT professionals in organizations is the choice of the right software vendor. In the highly competitive enterprise software industry, there are lot of vendors who claim to offer the best software for the problem and it can be really daunting to narrow down the best choice. Additionally, enterprise software costs can often run into millions of dollars thereby leaving very little margin of error. The real cost of choosing a wrong software can often result into losses much more than the cost of the software itself as highlighted by software disasters experienced by leading companies like HP, Nike etc. In such a scenario, senior IT professionals despite years of expertise can find it very difficult to choose the right business software vendor for their organization.

Here are some of the proven ways of short-listing and selecting the right business software vendor for your organization,

·         Understand and Define The Exact Need First: Before embarking on a journey to select the software vendor, it is critical to understand and define the exact problem you want the software to solve. The paramount question to be asked is what business objective does the software need to solve. Is the software required to “reduce costs” or is it to “improve productivity”? Extracting and defining this fundamental question is the bare minimum but necessary step to go searching for the right vendor. It will then form the basis of comparing multiple vendors on this very need that your organization has and will help drive the selection process going forward. The detailed approach involves creating a set of parameters that the software needs to meet in order to be considered. In fact, consider categorizing these parameters further in “must-haves”, “good to have” etc. which will help you assign relevant weights to these parameter and how the software’s fare on each of these parameters

·         Building The List of Vendors Who Meet The Need: Once you have defined your need and distilled that need into various parameters, it’s time to built the list of vendors who you think will meet the need. This is akin to a lead generation model wherein you want to identify a large enough pool and then filters your list down to the best ones. There are multiple ways of building a list of vendors and more often than not, you must use a combination of these methods to build a good enough list.

o   Use Industry Reports: We discussed the IT intelligence offered by leading industry firms Gartner and Forrester in How To Keep On Top Of Latest Trends In Information Technology. These firms based on their access to leading software vendors and CIO network publish vendor comparison research reports across specific verticals as well as specific technologies. Gartner’s Magic Quadrant and Forrester’s Wave are a very good starting point to get an insight into the best software vendors. For example, if you were looking for a CRM solution, you could look for Gartner’s Magic Quadrant for CRM and look at the vendors that make the list. These reports can be pricey but well worth the money if you are going to invest hundreds of thousands in the software. Having said that, you don’t have to trust these report blindly because how these firms define the best software may not match how you define the best software for your organization

o   Competitive Intelligence: If you are a smart professional, you are already keeping tabs of your competition. Chances are that if you are a big organization, you might see a Press Release either from your competitor or their vendor announcing the implementation of new software. Extrapolate that across 5-10 key competitors of yours and you might discover the vendors that your competitors are choosing. This gives you a good indicator that the vendors used by your competitors must be offering something right.

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

Communication is one of the main objectives that an organization needs to have in place to stay efficient and productive. A breakdown in accurate and efficient communication between departments at any point in the organization can result in conflict or loss of business.  Sadly, the efficiency between different departments in an organization becomes most evident when communication breaks down. As an example, David Grossman reported in “The Cost of Poor Communications” that a survey of 400 companies with 100,000 employees each cited an average loss per company of $62.4 million per year because of inadequate communication to and between employees.

With the dawning of the big-data era and the global competition that Machine Learning algorithms has sparked, it’s more vital than ever for companies of all sizes to prioritize departmental communication mishaps. Perhaps, today, as a result of the many emerging markets, the most essential of these connections are between IT and the business units. CMO’s and CIO’s are becoming natural partners in the sense that CMO’s, in order to capture revenue opportunities, are expected to master not just the art of strategy and creativity but also the science of analytics. The CIO, on the other hand, is accountable for using technical groundwork to enable and accelerate revenue growth. Since business and technology people speak very different languages, there’s a need on both sides to start sharing the vocabulary or understanding of what is expected in order to avoid gridlock.

In the McKinsey article, Getting the CMO and CIO to work as partners, the author speaks to five prerequisite steps that the CMO and the CIO can take in order to be successful in their new roles.

--- Be clear on decision governance
Teams should define when decisions are needed, what must be decided, and who is responsible for making them.

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.

Tech Life in New York

City The Big Apple is home of two of the world’s largest stock market exchanges, the New York Stock Exchange and NASDAQ. As a leading business center in the United States, New York has more Fortune 500 headquartered companies than any other city. Technology is blossoming in the Big Apple as major internet conglomerates like Google move their offices into “telecom hotels” such as the 311,000 square feet office space downtown. As in any other city there are pros and cons of living in New York City. For instance, there is so much to do, it’s easy to get around with the transit system, it’s safe, convenient, and has plenty of job opportunities. On the other hand, it can be overwhelmingly expensive, overcrowded, a bit impersonal and fast paced. New Yorkers enjoy Central Park, multi cultural activities and food, theatre, film festivals, farmers markets, fashion and anything else they could possibly think of...it’s all there.
A brand for a company is like a reputation for a person. You earn reputation by trying to do hard things well. Jeff Bezos Amazon.com founder
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Software developers near Albany 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 New York that offer opportunities for C# Programming developers
Company Name City Industry Secondary Industry
NYSE Euronext, Inc. New York Financial Services Securities Agents and Brokers
Anderson Instrument Company Inc. Fultonville Manufacturing Tools, Hardware and Light Machinery
News Corporation New York Media and Entertainment Radio and Television Broadcasting
Philip Morris International Inc New York Manufacturing Manufacturing Other
Loews Corporation New York Travel, Recreation and Leisure Hotels, Motels and Lodging
The Guardian Life Insurance Company of America New York Financial Services Insurance and Risk Management
Jarden Corporation Rye Manufacturing Manufacturing Other
Ralph Lauren Corporation New York Retail Clothing and Shoes Stores
Icahn Enterprises, LP New York Financial Services Investment Banking and Venture Capital
Viacom Inc. New York Media and Entertainment Media and Entertainment Other
Omnicom Group Inc. New York Business Services Advertising, Marketing and PR
Henry Schein, Inc. Melville Healthcare, Pharmaceuticals and Biotech Medical Supplies and Equipment
Pfizer Incorporated New York Healthcare, Pharmaceuticals and Biotech Pharmaceuticals
Eastman Kodak Company Rochester Computers and Electronics Audio, Video and Photography
Assurant Inc. New York Business Services Data and Records Management
PepsiCo, Inc. Purchase Manufacturing Nonalcoholic Beverages
Foot Locker, Inc. New York Retail Department Stores
Barnes and Noble, Inc. New York Retail Sporting Goods, Hobby, Book, and Music Stores
Alcoa New York Manufacturing Metals Manufacturing
The Estee Lauder Companies Inc. New York Healthcare, Pharmaceuticals and Biotech Personal Health Care Products
Avon Products, Inc. New York Healthcare, Pharmaceuticals and Biotech Personal Health Care Products
The Bank of New York Mellon Corporation New York Financial Services Banks
Marsh and McLennan Companies New York Financial Services Insurance and Risk Management
Corning Incorporated Corning Manufacturing Concrete, Glass, and Building Materials
CBS Corporation New York Media and Entertainment Radio and Television Broadcasting
Bristol Myers Squibb Company New York Healthcare, Pharmaceuticals and Biotech Biotechnology
Citigroup Incorporated New York Financial Services Banks
Goldman Sachs New York Financial Services Personal Financial Planning and Private Banking
American International Group (AIG) New York Financial Services Insurance and Risk Management
Interpublic Group of Companies, Inc. New York Business Services Advertising, Marketing and PR
BlackRock, Inc. New York Financial Services Securities Agents and Brokers
MetLife Inc. New York Financial Services Insurance and Risk Management
Consolidated Edison Company Of New York, Inc. New York Energy and Utilities Gas and Electric Utilities
Time Warner Cable New York Telecommunications Cable Television Providers
Morgan Stanley New York Financial Services Investment Banking and Venture Capital
American Express Company New York Financial Services Credit Cards and Related Services
International Business Machines Corporation Armonk Computers and Electronics Computers, Parts and Repair
TIAA-CREF New York Financial Services Securities Agents and Brokers
JPMorgan Chase and Co. New York Financial Services Investment Banking and Venture Capital
The McGraw-Hill Companies, Inc. New York Media and Entertainment Newspapers, Books and Periodicals
L-3 Communications Inc. New York Manufacturing Aerospace and Defense
Colgate-Palmolive Company New York Consumer Services Personal Care
New York Life Insurance Company New York Financial Services Insurance and Risk Management
Time Warner Inc. New York Media and Entertainment Media and Entertainment Other
Cablevision Systems Corp. Bethpage Media and Entertainment Radio and Television Broadcasting
CA Technologies, Inc. Islandia Software and Internet Software
Verizon Communications Inc. New York Telecommunications Telephone Service Providers and Carriers
Hess Corporation New York Energy and Utilities Gasoline and Oil Refineries

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