Agile/Scrum Training Classes in Raleigh, North Carolina

Learn Agile/Scrum in Raleigh, NorthCarolina 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 Agile/Scrum related training offerings in Raleigh, North Carolina: Agile/Scrum Training

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Raleigh  Upcoming Instructor Led Online and Public Agile/Scrum Training Classes
Certified Scrum Master (CSM) Training/Class 26 August, 2019 - 27 August, 2019 $1190
HSG Training Center
Raleigh, North Carolina
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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.

Companies have been collecting and analyzing data forever, pretty much.” So what’s really new here? What’s driving the data-analytics revolution and what does it mean for those that choose to postpone or ignore the pivotal role big-data is currently having on productivity and competition globally?

General Electric chairman and CEO Jeff Immelt explains it best when stating that “industrial companies are now in the information business—whether they like it or not.”  Likewise, digital data is now everywhere, it’s in every industry, in every economy, in every organization and according to the McKinsey Global Institute (MGI), this topic might once have concerned only a few data geeks, but big data is now relevant for leaders across every sector as well as consumers of products and services.

In light of the new data-driven global landscape and rapid technological advances, the question for senior leaders in companies now is how to integrate new capabilities into their operations and strategies—and position themselves globally where analytics can influence entire industries. An interesting discussion with six of theses senior leaders is covered in MGI’s article, “How companies are using big data and analytics,” providing us with a glimpse into a real-time decision making processes.

 

Once again theTIOBE Programming Community has calculated the trends in popular programming languages on the web. Evaluating the updates in the index allows developers to assess the direction of certain programming skills that are rising or faltering in their field.  According to the November 2013 report, three out of four languages currently ranking in the top twenty are languages defined by Microsoft. These are C#, SQL Server language Transact-SQL and Visual Basic.NET.  Not surprising though, the top two languages that remain steady in the number one and two spots are Java and C.

How are the calculations measured?  The information is gathered from five major search engines: Google, Bing, Yahoo!, Wikipedia, Amazon, YouTube and Baidu.

Top 20 Programming Languages: as of November 2013


  1.  C
  2.  Java
  3.  Objective-C 
  4.  C++
  5.  C#
  6.  PHP
  7. (Visual) Basic
  8.  Python
  9. Transact-SQL
  10. Java Script
  11. Visual Basic.NET
  12. Perl
  13.  Ruby
  14. Pascal
  15. Lisp
  16. MATLAB
  17. Delphi/Object Pascal
  18. PL/SQL
  19. COBOL
  20. Assembly

Although the index is an important itemized guide of what people are searching for on the internet, it’s arguable that certain languages getting recognition is a direct result of early adopters posting tutorials and filling up discussion boards on current trends. Additionally, popular tech blogs pick up on technological shifts and broadcast related versions of the same themes.

When does the popularity of a software language matter?

  1. If you want marketable skills, knowing what employers are looking for is beneficial. As an example, languages such as Java and Objective C are highly coveted in the smart-phone apps businesses.
  2. A consistently shrinking language in usage is an indicator not only that employers are apt to pass on those skills but fall in danger of being obsolete.
  3. Focusing on languages that are compatible with other developers increases your chances to participate on projects that companies are working on.

 

Welcome to the career field of Business Intelligence. Business Intelligence is a concept that involves a certain level of interaction within an organism, analytically and dynamically, to come to business solutions which implement better, more effective and timely decision making. These solutions are reached by establishing an understanding of the right kinds of user data: what is going well, what is going wrong, taking and monitoring certain actions, previously unknown trends, and patterns, and improved collaboration. When all of this data is taken into account, the entire decision-making process, within a business, will inevitably improve. As an Oracle BI developer, there are specific skills which will drastically make your job easier and results more effective. As time goes on and technology changes, the list is constantly being updated. The following are skills an Oracle Business Intelligence Developer might need to know or learn in 2019.

 

Communication

Tech Life in North Carolina

The University of North Carolina Chapel Hill is the oldest State University in the United States. There are significant ?firsts? in this state one being, the first state to own an art museum and second was to vote in the first African-American member, Hiram Rhoades Revels, into the United States Congress. Higher education is a given with a total of 2,425 public schools in the state, including 99 charter schools.
Success is the result of perfection, hard work, learning from failure, loyalty, and persistence. Colin Powell
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Software developers near Raleigh 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 North Carolina that offer opportunities for Agile/Scrum developers
Company Name City Industry Secondary Industry
Branch Banking and Trust / BBandT Winston Salem Financial Services Banks
UTC Aerospace Systems Charlotte Manufacturing Aerospace and Defense
R.J. Reynolds Tobacco Company Winston Salem Manufacturing Manufacturing Other
Family Dollar Stores, Inc. Matthews Retail Department Stores
Duke Energy Corporation Charlotte Energy and Utilities Gas and Electric Utilities
Lowe's Companies, Inc. Mooresville Retail Hardware and Building Material Dealers
Nucor Corporation Charlotte Manufacturing Metals Manufacturing
VF Corporation Greensboro Manufacturing Textiles, Apparel and Accessories
Bank of America Charlotte Financial Services Banks
Laboratory Corporation of America Burlington Healthcare, Pharmaceuticals and Biotech Diagnostic Laboratories
Sonic Automotive, Inc. Charlotte Retail Automobile Dealers
SPX Corporation Charlotte Manufacturing Tools, Hardware and Light Machinery
The Pantry, Inc. Cary Retail Gasoline Stations

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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 North Carolina 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 Agile/Scrum programming
  • Get your questions answered by easy to follow, organized Agile/Scrum experts
  • Get up to speed with vital Agile/Scrum 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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