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: $ 1290length: 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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Gain insight and ideas from students with different perspectives and experiences.

Blog Entries publications that: entertain, make you think, offer insight

In Python, the following list is considered False:

 

False, None, 0, 0.0, "",'',(),{},[]

 

Evolving technologies become fun due to the immense advantages and features they bring with them. Fighting change though is human and while we may initially resist such changes, it is always better to accept them to our advantage.

Switching to HTML 5 is one such change we need to be ready for and there are at least 8 reasons why we should be doing so which are explained later in the article.

Earlier HTML was mainly used only for Web content development. But with the arrival of HTML 5, there would be a radical shift in that it would be used more and more for the development of many of the client side applications as well. The advantages straight away are that CSS as well as JavaScript become free due to the open architecture environment. HTML 5 is also pretty light and has a much easier code to read, making it convenient for devices like smart phones and tablets running on batteries to use the applications.

The 8 reasons mentioned above are as under:

If you're someone who's interested in computer programming, chances are you've considered pursuing a career in it. However, being a computer programmer is definitely not for everyone, as it takes some special characteristics to succeed as a computer programmer.

Good at Math

While you don't have to be a math genius in order to be a good computer programmer, being good at math really does help. In general, as long as you know your trigonometry and advanced high school algebra, you should be set for programming.

However, in a few instances, knowledge of more advanced math ends up being necessary. For example, for shader programming, you should be familiar with integration of multiple variables, matrix algebra, and basic differentiation. You will also require considerable math skills in order to program 3D.

Excellent Problem Solver

To be a successful computer programmer, you definitely need to be an excellent problem solver. It is vital for a computer programmer to break a problem down into small parts. They must then be able to decide the best way to approach individual pieces of the problem. Computer programmers also need to know how to anticipate and prevent potential problems. While problem-solving, they also need to keep in mind things like user experience and performance.

If you're not a good problem solver, knowing a particular language and syntax will be useless if you can't even identify the problem at hand. Therefore, excellent problem solving skills are a critical foundation for computer programming.

Patience

If you are not a patient person, you will quickly become very frustrated with computer programming. Problem-solving is not always easy and fast. In fact, it may take a very long time, especially if you're either inexperienced or working on an especially hard project.

Debugging after the coding process is also very frustrating and tedious. No matter how hard you try, you will always have bugs in your coding, and these bugs, while often easy to fix, tend to be very difficult to detect. Therefore, you will end up spending a lot of your time searching for bugs that take very little time to fix.

Well-Rounded Skills

Generally, computer programmers who are very skilled in one area tend to stick around longer than jack-of-all-trades, as specialized programmers are harder to replace with outsourcing than general programmers. Therefore, it will do you well to specialize in one area of computer programming.

However, while specializing is good, you should still know at least a little about everything, especially skills that relate to the area you specialize in. For example, if you're a core Java programmer, you should know about SQL programming and ideally a scripting language or some regular expressions.

As you can see, not everyone has what it takes to pursue computer programming as a career and succeed at it. In fact, just because you love to program doesn't mean it's a good career choice for you. However, if you feel that you possess all the characteristics listed above, then you should definitely consider computer programming as a career.

Studying a functional programming language is a good way to discover new approaches to problems and different ways of thinking. Although functional programming has much in common with logic and imperative programming, it uses unique abstractions and a different toolset for solving problems. Likewise, many current mainstream languages are beginning to pick up and integrate various techniques and features from functional programming.

Many authorities feel that Haskell is a great introductory language for learning functional programming. However, there are various other possibilities, including Scheme, F#, Scala, Clojure, Erlang and others.

Haskell is widely recognized as a beautiful, concise and high-performing programming language. It is statically typed and supports various cool features that augment language expressivity, including currying and pattern matching. In addition to monads, the language support a type-class system based on methods; this enables higher encapsulation and abstraction. Advanced Haskell will require learning about combinators, lambda calculus and category theory. Haskell allows programmers to create extremely elegant solutions.

Scheme is another good learning language -- it has an extensive history in academia and a vast body of instructional documents. Based on the oldest functional language -- Lisp -- Scheme is actually very small and elegant. Studying Scheme will allow the programmer to master iteration and recursion, lambda functions and first-class functions, closures, and bottom-up design.

Supported by Microsoft and growing in popularity, F# is a multi-paradigm, functional-first programming language that derives from ML and incorporates features from numerous languages, including OCaml, Scala, Haskell and Erlang. F# is described as a functional language that also supports object-oriented and imperative techniques. It is a .NET family member. F# allows the programmer to create succinct, type-safe, expressive and efficient solutions. It excels at parallel I/O and parallel CPU programming, data-oriented programming, and algorithmic development.

Scala is a general-purpose programming and scripting language that is both functional and object-oriented. It has strong static types and supports numerous functional language techniques such as pattern matching, lazy evaluation, currying, algebraic types, immutability and tail recursion. Scala -- from "scalable language" -- enables coders to write extremely concise source code. The code is compiled into Java bytecode and executes on the ubiquitous JVM (Java virtual machine).

Like Scala, Clojure also runs on the Java virtual machine. Because it is based on Lisp, it treats code like data and supports macros. Clojure's immutability features and time-progression constructs enable the creation of robust multithreaded programs.

Erlang is a highly concurrent language and runtime. Initially created by Ericsson to enable real-time, fault-tolerant, distributed applications, Erlang code can be altered without halting the system. The language has a functional subset with single assignment, dynamic typing, and eager evaluation. Erlang has powerful explicit support for concurrent processes.

 

Computer Programming as a Career?

What little habits make you a better software engineer?

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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