Git, Jira, Wicket, Gradle, Tableau Training Classes in Boston, Massachusetts

Learn Git, Jira, Wicket, Gradle, Tableau in Boston, Massachusetts 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 Git, Jira, Wicket, Gradle, Tableau related training offerings in Boston, Massachusetts: Git, Jira, Wicket, Gradle, Tableau Training

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Toshiba has released a new line of solid-state drives (SSD) using 19 nanometers, which is currently the industry’s smallest lithography process.

 

The lineup will include mini-SATA and 2.5-inch form factors along with drives in 7mm and 9.5mm heights. All drives will use the most current serial ATA 6Gbps interface protocol.

 

Checking to see if a directory exists and then creating it if it is not present requires a few lines of code.  Isn't Python great. enlightened  Begin by importing the os module and use the exists and makedirs functions.

 

import os

if os.path.exists(somedirectory):
   os.makedirs(somedirectory)



I will begin our blog on Java Tutorial with an incredibly important aspect of java development:  memory management.  The importance of this topic should not be minimized as an application's performance and footprint size are at stake.

From the outset, the Java Virtual Machine (JVM) manages memory via a mechanism known as Garbage Collection (GC).  The Garbage collector

  • Manages the heap memory.   All obects are stored on the heap; therefore, all objects are managed.  The keyword, new, allocates the requisite memory to instantiate an object and places the newly allocated memory on the heap.  This object is marked as live until it is no longer being reference.
  • Deallocates or reclaims those objects that are no longer being referened. 
  • Traditionally, employs a Mark and Sweep algorithm.  In the mark phase, the collector identifies which objects are still alive.  The sweep phase identifies objects that are no longer alive.
  • Deallocates the memory of objects that are not marked as live.
  • Is automatically run by the JVM and not explicitely called by the Java developer.  Unlike languages such as C++, the Java developer has no explict control over memory management.
  • Does not manage the stack.  Local primitive types and local object references are not managed by the GC.

So if the Java developer has no control over memory management, why even worry about the GC?  It turns out that memory management is an integral part of an application's performance, all things being equal.  The more memory that is required for the application to run, the greater the likelihood that computational efficiency suffers. To that end, the developer has to take into account the amount of memory being allocated when writing code.  This translates into the amount of heap memory being consumed.

Memory is split into two types:  stack and heap.  Stack memory is memory set aside for a thread of execution e.g. a function.  When a function is called, a block of memory is reserved for those variables local to the function, provided that they are either a type of Java primitive or an object reference.  Upon runtime completion of the function call, the reserved memory block is now available for the next thread of execution.  Heap memory, on the otherhand, is dynamically allocated.  That is, there is no set pattern for allocating or deallocating this memory.  Therefore, keeping track or managing this type of memory is a complicated process. In Java, such memory is allocated when instantiating an object:

String s = new String();  // new operator being employed
String m = "A String";    /* object instantiated by the JVM and then being set to a value.  The JVM
calls the new operator */

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 Massachusetts

It?s no wonder that Massachusetts is a hub of major activity in information technology with a collection of 121 institutions for higher education. In 2007 Mass. impressively scored the highest of all the states in math on the National Assessments of Educational Progress. Some fun facts about Massachusest: - The first U.S.Postal zip code in Massachusetts is 01001 at Agawam. - The Boston University Bridge on Commonwealth Avenue in Boston is the only place in the world where a boat can sail under a train driving under a car driving under an airplane.
I was just pursuing what I enjoyed doing. I mean, I was pursuing my passion. Pierre Omidyar, eBay founder
other Learning Options
Software developers near Boston 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 Massachusetts that offer opportunities for Git, Jira, Wicket, Gradle, Tableau developers
Company Name City Industry Secondary Industry
Cabot Corporation Boston Telecommunications Telephone Service Providers and Carriers
LPL Financial Boston Financial Services Personal Financial Planning and Private Banking
NSTAR Gas and Electric Company Westwood Energy and Utilities Gas and Electric Utilities
Cabot Corporation Boston Manufacturing Plastics and Rubber Manufacturing
BJ's Wholesale Club, Inc. Westborough Retail Department Stores
American Tower Corporation Boston Telecommunications Telecommunications Equipment and Accessories
Hologic, Inc. Bedford Healthcare, Pharmaceuticals and Biotech Medical Devices
Global Partners LP Waltham Retail Gasoline Stations
Northeast Utilities Boston Energy and Utilities Gas and Electric Utilities
Liberty Mutual Holding Company Boston Financial Services Insurance and Risk Management
Staples Inc. Framingham Computers and Electronics Office Machinery and Equipment
Thermo Fisher Scientific Inc. Waltham Healthcare, Pharmaceuticals and Biotech Medical Devices
Hanover Insurance Group, Inc. Worcester Financial Services Insurance and Risk Management
The TJX Companies, Inc. Framingham Retail Department Stores
Iron Mountain, Inc. Boston Software and Internet Data Analytics, Management and Storage
Massachusetts Mutual Financial Group Springfield Financial Services Insurance and Risk Management
Beacon Roofing Supply, Inc. Peabody Manufacturing Concrete, Glass, and Building Materials
Raytheon Company Waltham Software and Internet Software
Analog Devices, Inc. Norwood Computers and Electronics Consumer Electronics, Parts and Repair
Biogen Idec Inc. Weston Healthcare, Pharmaceuticals and Biotech Biotechnology
Boston Scientific Corporation Natick Healthcare, Pharmaceuticals and Biotech Medical Supplies and Equipment
PerkinElmer, Inc. Waltham Computers and Electronics Instruments and Controls
State Street Corporation Boston Financial Services Trust, Fiduciary, and Custody Activities
EMC Corporation Hopkinton Computers and Electronics Networking Equipment and Systems

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 Massachusetts 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 Git, Jira, Wicket, Gradle, Tableau programming
  • Get your questions answered by easy to follow, organized Git, Jira, Wicket, Gradle, Tableau experts
  • Get up to speed with vital Git, Jira, Wicket, Gradle, Tableau 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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