Python Programming Training Classes in Training/San Jose,

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 Training/San Jose 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 Training/San Jose: Python Programming Training

We offer private customized training for groups of 3 or more attendees.

Python Programming Training Catalog

subcategories

cost: $ 1390length: 3 day(s)
Python continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses. Python is useful for developing custom software tools, applications, web services, and cloud applications. In this course, you'll build upon your basic Python skills, learning more advanced topics such as object-ori ...
cost: $ 1290length: 3 day(s)
The focus will be on advanced data processing and the use of scientific libraries (e.g. numPy, Panda, SciPy, Jupyter Notebooks, etc.) ...
cost: $ 1190length: 3 day(s)
In this Python training course, students already familiar with Python programming will learn advanced Python techniques such as: IPython Notebook; the Collections module; mapping and filtering; lamba functions; advanced sorting; working with regular expressions; working with databases, CSV files, JSON and XML; writing object-oriented code; testing and debugging; and learning about Unicode and ...
cost: $ 1290length: 4 day(s)
In this Python training course, students already familiar with Python programming will learn advanced Python techniques such as IPython Notebook, the Collections module, mapping and filtering, lamba functions, advanced sorting, writing object-oriented code, testing and debugging, NumPy, pandas, matplotlib, regular expressions, Unicode, text encoding and working with databases, CSV files, JSON and ...
cost: $ 1190length: 3 day(s)
This three-day course provides the student with the knowledge to create and run Python scripts that include Python-specific data structures, function, modules, and classes. ...
cost: $ 1190length: 3 day(s)
This course provides an overview of the basic to advanced features of the R programming language. It is presented as a combination of lectures and hands-on exercises. Course Topics: ... Data Science Basics ... R Language Basics ... Intermediate R ... Charting and Graphing ... Statistical Processing ... Introduction to Text Analytics and the tm Package ... Introduction to Collaborative Filtering .. ...
cost: $ 1290length: 4 day(s)
This 4 day course picks up where Introduction to Python 3 leaves off, covering some topics in more detail, and adding many new ones, with a focus on enterprise development. This is a hands-on programming class. All concepts are reinforced by informal practice during the lecture followed by lab exercises. Many labs build on earlier labs, which helps students retain the earlier material. ...
cost: $ 1250length: 2 day(s)
This course employs many advanced Python libraries to provide the student with a solid foundation of Machine Learning concepts and practices. ...
cost: $ 1290length: 4 day(s)
This four day course leads the student from the basics of writing and running Python scripts to more advanced features such as file operations, regular expressions, working with binary data, and using the extensive functionality of Python modules. Extra emphasis is placed on features unique to Python, such as tuples, array slices, and output formatting. This is a hands-on programming class. All ...
cost: $ 1890length: 4 day(s)
This course introduces the Apache Spark distributed computing engine, and is suitable for developers, data analysts, ...
cost: $ 1090length: 3 day(s)
This course introduces the Apache Spark distributed computing engine, and is suitable for developers, data analysts, ...
cost: $ 1790length: 3 day(s)
This class employs the Python modules Matplotlib, Scipy and Numpy, Pandas, Sklearn and the IPython to explore a variety of different Machine Learning algorithms. Students will gain an in depth knowledge of Advanced Python constructs and a basic understanding of Machine Learning. ...
cost: $ 790length: 2 day(s)
This is a rapid introduction to NumPy, pandas and matplotlib for experienced Python programmers who are new to those libraries. Students will learn to use NumPy to work with arrays and matrices of numbers; learn to work with pandas to analyze data; and learn to work with matplotlib from within pandas. ...
cost: $ 1690length: 4 day(s)
This is a 4 - day course that provides a ramp - up to using Python for scientific and mathematical computing. Starting with the basics, it progresses to the most important Python modules for working with data, from arrays, to statistics, to plotting result s. The material is geared ...
cost: $ 2250length: 5 day(s)
This is a 5 - day course that provides a ramp - up to using Python for data science/machine learning. Starting with the basics, it progresses to the most important Python modules for working with data, from arrays, to statistics, to plotting results. The material is geared towards data scientists and engineers. This is an intense, hands - on, programming class. All concepts are reinforced by ...
cost: $ 1290length: 4 day(s)
This course begins with an abbreviated primer on Python (language syntax, data structures, basic data processing, Python functions, modules and classes). The remainder of the course covers open source Python tools relevant to solving your day-to-day financial programming problems. Specific topics addressed include: array computation and mathematics with NumPy; statistical computation with SciPy; ...
cost: $ 2250length: 5 day(s)
This is a 5 - day course that provides a ramp - up to using Python for scientific and mathematical computing. Starting with the basics, it progresses to the most important Python modules for working with data, from arrays, to statistics, to plotting result s. The material is geared towards scientists and engineers. This is an intense, hands - on, programming class. All concepts are reinforced by ...
cost: $ 1290length: 4 day(s)
This four day course leads the student from the basics of writing and running Python scripts to more advanced features such as file operations, regular expressions, working with binary data, and using the extensive functionality of Python modules. Extra emphasis is placed on features unique to Python, such as tuples, array slices, and output formatting. This is a hands-on programming class. All ...
cost: $ 790length: 2 day(s)
This two day course covers a handful of various Python advanced topics including high level data structures, network programming, writing GUI's in Python, and CGI programming. This course is particularly well suited for programmers who are building application frameworks, integrating Python with other software, or using Python for distributed computing. ...
cost: $ 1290length: 4 day(s)
This 4 day course picks up where Python I leaves off, covering some topics in more detail, and adding many new ones, with a focus on enterprise development. This is a hands-on programming class. All concepts are reinforced by informal practice during the lecture followed by lab exercises. Many labs build on earlier labs, which helps students retain the earlier material. Audience: Advanced users, ...
cost: $ 990length: 2 day(s)
More and more organizations are turning to data science to help guide business decisions. Regardless of industry, the ability to extract knowledge from data is crucial for a modern business to stay competitive. One of the tools at the forefront of data science is the Python® programming language. Python's robust libraries have given data scientists the ability to load, analyze, ...

Web Development Classes

cost: $ 1390length: 3 day(s)
This Advanced ...
cost: $ 1690length: 4 day(s)
This course ...

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As part of our C++ Tutorials series, here is a tutorial on the tricks of the trade for using C++ I/O.  Keep in mind that an application without I/O is just a black box; no communcation is taking place.  wink

Tricks and Tips for using C++ I/O

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:

F# Programming Essentials Training

The Zen of Python, by Tim Peters has been adopted by many as a model summary manual of python's philosophy.  Though these statements should be considered more as guideline and not mandatory rules, developers worldwide find the poem to be on a solid guiding ground.


Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!

What are some of the software development headaches associated with iPhone vs Android development?

The Boss (hereafter referred to as TB), handed me this research assignment. Hey, I finally got a little bit of one ups man ship on TB.

This is a significant moment in my life. Like me, TB isn't really human. I know because neither of us seem to indulge in that luxury known as sleep. That makes it extremely difficult to have any sort of 'gotcha'. I'm dancing. I got one.

In the warp speed development cycles we are now facing, TB must have gone to sleep, which in human terms is known as a wink. (About a 40th of the second).
18 June 2012 Monday, 3:30 PM (15:30 HRS) UTC -8, in Los Angeles Microsoft is making a major tablet announcement, revealing its own hardware that is tablet-based. Do not be surprised if it entails a Hollywood Inc. focus.

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 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 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…
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Interesting Reads Take a class with us and receive a book of your choosing for 50% off MSRP.