Python Programming Training Classes in Kent, Washington
Training Suggestions from the Experts
An Experienced Python developer must have
... an understanding of the following topics: Map, Reduce and Filter, Numpy, Pandas, MatplotLib, File handling and Database integration. All of these requirements assume a solid grasp of Python Idioms that include iterators, enumerators, generators and list comprehensions.
To quickly get up to speed, we suggest you enroll in the following classes: Beginning Python and Advanced Python 3
Call for Details: 303.377.6176
Learn Python Programming in Kent, Washington 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 Python Programming related training offerings in Kent, Washington: Python Programming Training
Python Programming Training Catalog
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- DOCKER WITH KUBERNETES ADMINISTRATION
6 May, 2024 - 10 May, 2024 - Linux Fundaments GL120
15 April, 2024 - 19 April, 2024 - Introduction to Python 3.x
29 April, 2024 - 2 May, 2024 - ASP.NET Core MVC, Rev. 6.0
22 April, 2024 - 23 April, 2024 - LINUX SHELL SCRIPTING
29 May, 2024 - 30 May, 2024 - See our complete public course listing
Blog Entries publications that: entertain, make you think, offer insight
Python and Ruby, each with roots going back into the 1990s, are two of the most popular interpreted programming languages today. Ruby is most widely known as the language in which the ubiquitous Ruby on Rails web application framework is written, but it also has legions of fans that use it for things that have nothing to do with the web. Python is a big hit in the numerical and scientific computing communities at the present time, rapidly displacing such longtime stalwarts as R when it comes to these applications. It too, however, is also put to a myriad of other uses, and the two languages probably vie for the title when it comes to how flexible their users find them.
A Matter of Personality...
That isn't to say that there aren't some major, immediately noticeable, differences between the two programming tongues. Ruby is famous for its flexibility and eagerness to please; it is seen by many as a cleaned-up continuation of Perl's "Do What I Mean" philosophy, whereby the interpreter does its best to figure out the meaning of evening non-canonical syntactic constructs. In fact, the language's creator, Yukihiro Matsumoto, chose his brainchild's name in homage to that earlier language's gemstone-inspired moniker.
Python, on the other hand, takes a very different tact. In a famous Python Enhancement Proposal called "The Zen of Python," longtime Pythonista Tim Peters declared it to be preferable that there should only be a single obvious way to do anything. Python enthusiasts and programmers, then, generally prize unanimity of style over syntactic flexibility compared to those who choose Ruby, and this shows in the code they create. Even Python's whitespace-sensitive parsing has a feel of lending clarity through syntactical enforcement that is very much at odds with the much fuzzier style of typical Ruby code.
For example, Python's much-admired list comprehension feature serves as the most obvious way to build up certain kinds of lists according to initial conditions:
a = [x**3 for x in range(10,20)]
b = [y for y in a if y % 2 == 0]
first builds up a list of the cubes of all of the numbers between 10 and 19 (yes, 19), assigning the result to 'a'. A second list of those elements in 'a' which are even is then stored in 'b'. One natural way to do this in Ruby is probably:
a = (10..19).map {|x| x ** 3}
b = a.select {|y| y.even?}
but there are a number of obvious alternatives, such as:
a = (10..19).collect do |x|
x ** 3
end
b = a.find_all do |y|
y % 2 == 0
end
It tends to be a little easier to come up with equally viable, but syntactically distinct, solutions in Ruby compared to Python, even for relatively simple tasks like the above. That is not to say that Ruby is a messy language, either; it is merely that it is somewhat freer and more forgiving than Python is, and many consider Python's relative purity in this regard a real advantage when it comes to writing clear, easily understandable code.
And Somewhat One of Performance
Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied. For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.
In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.
Panelist, Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”
Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”
Since its foundation, HSG has been a leader in Business Rule Management Systems Training and Consulting services by way of the Blaze Advisor Rule Engine. Over the years we have provided such services to many of the worlds largest corporations and government institutions whose respective backgrounds include credit card processing, banking, insurance, health and medicine and more, much more. Such training and consulting services have included:
Create a wrapper object model in either Java, .NET or XML
Identify and catalog business rules
Develop a rule architecture within Blaze Advisor that isolates rule repositories as they relate to functionality and corporate policies
Configure, develop and implement a variety of interfaces to the rule engine from disparate systems ranging from mainframe applications written in Cobol to UNIX/Windows applications using Enterprise Java Beans, Windows Services, Web Services, Fat Clients, Java Messaging Services and Web Applications.
Review and update code to boost efficiency either by way of
Removing functions calls within conditional statements
Ensuring that database calls are essential or can be rearchitected in some other manner
Employing the rete algorithm where necessary
Paring down extensively large class models
Deploying such appliations in multi-threaded systems
· ...
Call us if you:
are in need of Blaze Advisor Expertise
are developing SMEs in Blaze
want to speak directly with an expert (no placement agencies)
want an affordable alternative to FICO
want to work with an industry leader
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 Washington
Company Name | City | Industry | Secondary Industry |
---|---|---|---|
Symetra Financial Corporation | Bellevue | Financial Services | Insurance and Risk Management |
Alaska Air Group, Inc. | Seattle | Travel, Recreation and Leisure | Passenger Airlines |
Expedia, Inc. | Bellevue | Travel, Recreation and Leisure | Travel Agents & Services |
Itron, Inc. | Liberty Lake | Computers and Electronics | Instruments and Controls |
PACCAR Inc. | Bellevue | Manufacturing | Automobiles, Boats and Motor Vehicles |
Puget Sound Energy Inc | Bellevue | Energy and Utilities | Gas and Electric Utilities |
Expeditors International of Washington, Inc. | Seattle | Transportation and Storage | Freight Hauling (Rail and Truck) |
Costco Wholesale Corporation | Issaquah | Retail | Grocery and Specialty Food Stores |
Starbucks Corporation | Seattle | Retail | Restaurants and Bars |
Nordstrom, Inc. | Seattle | Retail | Department Stores |
Weyerhaeuser Company | Federal Way | Manufacturing | Paper and Paper Products |
Microsoft Corporation | Redmond | Software and Internet | Software |
Amazon.com, Inc. | Seattle | Retail | Sporting Goods, Hobby, Book, and Music Stores |
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 Washington 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 Python Programming programming
- Get your questions answered by easy to follow, organized Python Programming experts
- Get up to speed with vital Python 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…