Java Programming Training Classes in Boca Raton, Florida
Training Suggestions from the Experts

An Experienced Java developer must know
... everything or so it can seem. A solid grasp and knowledge of Object Oriented Programming constructs such as inheritance, polymorphism, interfaces and reflection are essential. Next in line is the knowldge to be able to import/export file data, running SQL queries, using regular expressions and, possibly, knowing how to write multi-threaded code and make socket connections. A class that addresses most of these topics is: Fast Track to Java 11 and OO Development.
For the more daring Java enthusiast and especially for those looking to become professional Java developers, knowledge of the Spring Framework is expected. A perfect class for this is: Fast Track to Spring Framework and Spring MVC/Rest. Not only does this course provide students with a great introduction to spring, it goes beyond the basics with a solid delve into Spring and web development.
Another consideration is learning JBoss aka Wildfly, the free Application Server from RedHat. JBoss has become the workhorse of most Java EE applications. Add to that a class on Tomcat, the defacto servlet engine, and the student can be considered 'ready' for employment.
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Learn Java Programming in Boca Raton, Florida 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 Java Programming related training offerings in Boca Raton, Florida: Java Programming Training
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9 June, 2025 - 13 June, 2025 - RED HAT ENTERPRISE LINUX AUTOMATION WITH ANSIBLE
21 April, 2025 - 24 April, 2025 - OpenShift Fundamentals
28 April, 2025 - 30 April, 2025 - Linux Fundaments GL120
2 June, 2025 - 6 June, 2025 - RED HAT ENTERPRISE LINUX SYSTEMS ADMIN I
24 March, 2025 - 28 March, 2025 - See our complete public course listing
Blog Entries publications that: entertain, make you think, offer insight
The original article was posted by Michael Veksler on Quora
A very well known fact is that code is written once, but it is read many times. This means that a good developer, in any language, writes understandable code. Writing understandable code is not always easy, and takes practice. The difficult part, is that you read what you have just written and it makes perfect sense to you, but a year later you curse the idiot who wrote that code, without realizing it was you.
The best way to learn how to write readable code, is to collaborate with others. Other people will spot badly written code, faster than the author. There are plenty of open source projects, which you can start working on and learn from more experienced programmers.
Readability is a tricky thing, and involves several aspects:
- Never surprise the reader of your code, even if it will be you a year from now. For example, don’t call a function max() when sometimes it returns the minimum().
- Be consistent, and use the same conventions throughout your code. Not only the same naming conventions, and the same indentation, but also the same semantics. If, for example, most of your functions return a negative value for failure and a positive for success, then avoid writing functions that return false on failure.
- Write short functions, so that they fit your screen. I hate strict rules, since there are always exceptions, but from my experience you can almost always write functions short enough to fit your screen. Throughout my carrier I had only a few cases when writing short function was either impossible, or resulted in much worse code.
- Use descriptive names, unless this is one of those standard names, such as i or it in a loop. Don’t make the name too long, on one hand, but don’t make it cryptic on the other.
- Define function names by what they do, not by what they are used for or how they are implemented. If you name functions by what they do, then code will be much more readable, and much more reusable.
- Avoid global state as much as you can. Global variables, and sometimes attributes in an object, are difficult to reason about. It is difficult to understand why such global state changes, when it does, and requires a lot of debugging.
- As Donald Knuth wrote in one of his papers: “Early optimization is the root of all evil”. Meaning, write for readability first, optimize later.
- The opposite of the previous rule: if you have an alternative which has similar readability, but lower complexity, use it. Also, if you have a polynomial alternative to your exponential algorithm (when N > 10), you should use that.
Use standard library whenever it makes your code shorter; don’t implement everything yourself. External libraries are more problematic, and are both good and bad. With external libraries, such as boost, you can save a lot of work. You should really learn boost, with the added benefit that the c++ standard gets more and more form boost. The negative with boost is that it changes over time, and code that works today may break tomorrow. Also, if you try to combine a third-party library, which uses a specific version of boost, it may break with your current version of boost. This does not happen often, but it may.
Don’t blindly use C++ standard library without understanding what it does - learn it. You look at
documentation at it tells you that its complexity is O(1), amortized. What does that mean? How does it work? What are benefits and what are the costs? Same with std::vector::push_back()
, and with std::map
. Knowing the difference between these two maps, you’d know when to use each one of them.std::unordered_map
Never call
or new
directly, use delete
and [cost c++]std::make_shared[/code] instead. Try to implement std::make_unique
yourself, in order to understand what they actually do. People do dumb things with these types, since they don’t understand what these pointers are.usique_ptr, shared_ptr, weak_ptr
Every time you look at a new class or function, in boost or in std, ask yourself “why is it done this way and not another?”. It will help you understand trade-offs in software development, and will help you use the right tool for your job. Don’t be afraid to peek into the source of boost and the std, and try to understand how it works. It will not be easy, at first, but you will learn a lot.
Know what complexity is, and how to calculate it. Avoid exponential and cubic complexity, unless you know your N is very low, and will always stay low.
Learn data-structures and algorithms, and know them. Many people think that it is simply a wasted time, since all data-structures are implemented in standard libraries, but this is not as simple as that. By understanding data-structures, you’d find it easier to pick the right library. Also, believe it or now, after 25 years since I learned data-structures, I still use this knowledge. Half a year ago I had to implemented a hash table, since I needed fast serialization capability which the available libraries did not provide. Now I am writing some sort of interval-btree, since using std::map, for the same purpose, turned up to be very very slow, and the performance bottleneck of my code.
Notice that you can’t just find interval-btree on Wikipedia, or stack-overflow. The closest thing you can find is Interval tree, but it has some performance drawbacks. So how can you implement an interval-btree, unless you know what a btree is and what an interval-tree is? I strongly suggest, again, that you learn and remember data-structures.
These are the most important things, which will make you a better programmer. The other things will follow.
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.
A career in the field of software development remains immensely popular due to various factors. Chief among them of course is the higher compensation and lucrative pay scale in the IT industry when compared to other career options. In addition, the flexibility of work hours and the sheer sense of achievement experienced by one while creating new programs are unsurpassed by any other job.
Popularity and reach of Software Programs
Software programming has become a quintessential part of our day to day life, right from the smartphones in your pocket, to video gaming, and everything in between. The opportunities in this field are truly astounding. The niches for specializing are also diverse, from creating operating systems, to mobile app development, or web app development to name a few.
There are various ways in which you can distinguish yourself in the market for the much coveted title of software programmer. Here, we focus on some of them.
It is said that spoken languages shape thoughts by their inclusion and exclusion of concepts, and by structuring them in different ways. Similarly, programming languages shape solutions by making some tasks easier and others less aesthetic. Using F# instead of C# reshapes software projects in ways that prefer certain development styles and outcomes, changing what is possible and how it is achieved.
F# is a functional language from Microsoft's research division. While once relegated to the land of impractical academia, the principles espoused by functional programming are beginning to garner mainstream appeal.
As its name implies, functions are first-class citizens in functional programming. Blocks of code can be stored in variables, passed to other functions, and infinitely composed into higher-order functions, encouraging cleaner abstractions and easier testing. While it has long been possible to store and pass code, F#'s clean syntax for higher-order functions encourages them as a solution to any problem seeking an abstraction.
F# also encourages immutability. Instead of maintaining state in variables, functional programming with F# models programs as a series of functions converting inputs to outputs. While this introduces complications for those used to imperative styles, the benefits of immutability mesh well with many current developments best practices.
For instance, if functions are pure, handling only immutable data and exhibiting no side effects, then testing is vastly simplified. It is very easy to test that a specific block of code always returns the same value given the same inputs, and by modeling code as a series of immutable functions, it becomes possible to gain a deep and highly precise set of guarantees that software will behave exactly as written.
Further, if execution flow is exclusively a matter of routing function inputs to outputs, then concurrency is vastly simplified. By shifting away from mutable state to immutable functions, the need for locks and semaphores is vastly reduced if not entirely eliminated, and multi-processor development is almost effortless in many cases.
Type inference is another powerful feature of many functional languages. It is often unnecessary to specify argument and return types, since any modern compiler can infer them automatically. F# brings this feature to most areas of the language, making F# feel less like a statically-typed language and more like Ruby or Python. F# also eliminates noise like braces, explicit returns, and other bits of ceremony that make languages feel cumbersome.
Functional programming with F# makes it possible to write concise, easily testable code that is simpler to parallelize and reason about. However, strict functional styles often require imperative developers to learn new ways of thinking that are not as intuitive. Fortunately, F# makes it possible to incrementally change habits over time. Thanks to its hybrid object-oriented and functional nature, and its clean interoperability with the .net platform, F# developers can gradually shift to a more functional mindset while still using the algorithms and libraries with which they are most familiar.
Related F# Resources:
Tech Life in Florida
Company Name | City | Industry | Secondary Industry |
---|---|---|---|
Lender Processing Services, Inc. (LPS) | Jacksonville | Software and Internet | Data Analytics, Management and Storage |
World Fuel Services Corporation | Miami | Energy and Utilities | Gasoline and Oil Refineries |
SEACOR Holdings Inc. | Fort Lauderdale | Transportation and Storage | Marine and Inland Shipping |
MasTec, Inc. | Miami | Business Services | Security Services |
Health Management Associates, Inc. | Naples | Healthcare, Pharmaceuticals and Biotech | Hospitals |
B/E Aerospace, Inc. | Wellington | Manufacturing | Aerospace and Defense |
Roper Industries, Inc. | Sarasota | Manufacturing | Manufacturing Other |
AutoNation | Fort Lauderdale | Retail | Automobile Dealers |
Watsco, Inc. | Miami | Wholesale and Distribution | Wholesale and Distribution Other |
SFN Group | Fort Lauderdale | Business Services | HR and Recruiting Services |
Tupperware Corporation | Orlando | Manufacturing | Plastics and Rubber Manufacturing |
AirTran Holdings, Inc. | Orlando | Travel, Recreation and Leisure | Passenger Airlines |
WellCare Health Plans, Inc. | Tampa | Healthcare, Pharmaceuticals and Biotech | Healthcare, Pharmaceuticals, and Biotech Other |
Lennar Corporation | Miami | Real Estate and Construction | Real Estate Agents and Appraisers |
HSN, Inc. | Saint Petersburg | Retail | Retail Other |
Certegy | Saint Petersburg | Business Services | Business Services Other |
Raymond James Financial, Inc. | Saint Petersburg | Financial Services | Trust, Fiduciary, and Custody Activities |
Winn-Dixie Stores, Inc. | Jacksonville | Retail | Grocery and Specialty Food Stores |
Jabil Circuit, Inc. | Saint Petersburg | Computers and Electronics | Semiconductor and Microchip Manufacturing |
CSX Corporation | Jacksonville | Transportation and Storage | Freight Hauling (Rail and Truck) |
Fidelity National Financial, Inc. | Jacksonville | Financial Services | Insurance and Risk Management |
Tech Data Corporation | Clearwater | Consumer Services | Automotive Repair & Maintenance |
TECO Energy, Inc. | Tampa | Manufacturing | Chemicals and Petrochemicals |
Lincare Holdings Inc | Clearwater | Healthcare, Pharmaceuticals and Biotech | Medical Supplies and Equipment |
Chico's FAS Inc. | Fort Myers | Retail | Clothing and Shoes Stores |
Burger King Corporation LLC | Miami | Retail | Restaurants and Bars |
Publix Super Markets, Inc. | Lakeland | Retail | Grocery and Specialty Food Stores |
Florida Power and Light Company | Juno Beach | Energy and Utilities | Gas and Electric Utilities |
Ryder System, Inc. | Miami | Transportation and Storage | Freight Hauling (Rail and Truck) |
Citrix Systems, Inc. | Fort Lauderdale | Software and Internet | Software and Internet Other |
Harris Corporation | Melbourne | Telecommunications | Wireless and Mobile |
Office Depot, Inc. | Boca Raton | Computers and Electronics | Audio, Video and Photography |
Landstar System, Inc. | Jacksonville | Transportation and Storage | Freight Hauling (Rail and Truck) |
Darden Restaurants, Inc. | Orlando | Retail | Restaurants and Bars |
PSS World Medical, Inc. | Jacksonville | Healthcare, Pharmaceuticals and Biotech | Medical Supplies and Equipment |
training details locations, tags and why hsg
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.
- We have provided software development and other IT related training to many major corporations in Florida since 2002.
- 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 Java Programming programming
- Get your questions answered by easy to follow, organized Java Programming experts
- Get up to speed with vital Java 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…