Python Programming Training Classes in Training/Houston,

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/Houston 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/Houston: 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

Applications are becoming more and more sophisticated as languages such as Python open the doors to the world of programming for people who have the creative vision but always felt actually writing code was beyond their grasp.

A large part of any programs success is based on how well it can react to the events which it has been programmed to understand and listen for.

A good example of an event would be when the user clicks a button on the applications window. What happens when that button is clicked?

Well, the first thing that happens is the operating system sends out a message to let any listening software know that the button was clicked. Next, your application needs to do something in response to that event.

Unlike Java, Python does not have a string contains method.  Instead, use the in operator or the find method.  The in operator finds treats the string as a word list whereas the find method looks for substrings.  In the example shown below, 'is' is a substring of this but not a word by itself.  Therefore, find recoginizes 'is' in this while the in operator does not.

 

s = "This be a string"
if s.find("is") == -1:
    print "No 'is' here!"
else:
    print "Found 'is' in the string."
    
if "is" in s:
    print "No 'is' here!"
else:
    print "Found 'is' in the string."

#prints out the following:
Found 'is' in the string
No 'is' here!

In the ever changing landscape of software programming, it is not surprising that developers and employees have a different set of preferences for desired skills.  However the number one language that developers want to learn according to a survey of developers by technical recruiter, Hacker Rank is Python. This is not a surprise considering that Python has been in demand for several years and programmers tend to really enjoy this language for clear syntax, good OOP support and great shortcuts. Python, named “the language of the year” in 2007 and 2010 in the TIOBE Index and has climbed to #4 status in May of 2018.

According to the study, employers want developers who:

-  Have problem-solving skills, such as the ability to break down large, complex problems.
- Are proficient in their programming language and debugging.
- Can design systems.
- Can optimize performance.
- Have experience in reviewing and testing code.
- Are proficient in database design

Surprisingly, formal education is not the deciding factor when it comes to what companies care about the most. People with computer degrees or certifications on a resume are not necessarily a first choice for hiring managers. Others that have years of experience even if those individuals are partially self-taught in the field stand to be taken seriously in the field.   For those individuals with a passion to learn and master a skill, there are ample opportunities with smaller to mid-sized companies.

Some interesting FAQ’s from the study:

    On average, developers know 4 languages, and they aspire to learn 4 more.
    Younger developers between 18 and 24 plan to learn 6 languages.
    Folks older than 35 only plan to learn and additional 3 languages.
    The top languages developers said they will learn were, Go, Python, Scala, Kotlin, and Ruby.
    There is a large gap between employers seeking developers that know React than there are folks that can do it.

So, Why Learn Python?
It is now the most popular introductory teaching language in U.S. universities.  Python is easy to use, powerful, and versatile, making it a great choice for beginners and experts alike. It allows you to think like a programmer and not waste time understanding difficult syntax that other programming languages can command. And, because of its rapid growth, many developers contribute to the Python community and share Python libraries making creativity that much more a reality

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