Python Programming Training Classes in Training/Chicago,

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/Chicago 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/Chicago: Python Programming Training

We offer private customized training for groups of 3 or more attendees.
Upcoming Instructor Led Online and Public Python Programming Training Classes
Python for Scientists Training/Class 4 August, 2025 - 8 August, 2025 $1750
HSG Training Center 1312 17th Street, Unit #2502
Denver, CO 80203 (303)377-6176
Hartmann Software Group Training Registration

Python Programming Training Catalog

cost: $ 3length: 1390 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: $ 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: $ 1750length: 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: $ 1750length: 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, ...

Course Directory [training on all levels]

Upcoming Classes
Gain insight and ideas from students with different perspectives and experiences.

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

What are the three most important things non-programmers should know about programming?
 
Written by Brian Knapp, credit and reprint CodeCareerGenius
 
 
Since you asked for the three most important things that non-programmers should know about, and I’ve spent most of my career working with more non-programmers than programmers, I have a few interesting things that would help.
 
Number One - It Is Impossible To Accurately Estimate Software Projects
 
No matter what is tried. No matter what tool, agile approach, or magic fairy dust people try to apply to creating software… accurately predicting software project timelines is basically impossible.
 
There are many good reasons for this. Usually, requirements and feature ideas change on a daily/weekly basis. Often it is impossible to know what needs to be done without actually digging into the code itself. Debugging and QA can take an extraordinary amount of time.
 
And worst of all…
 
Project Managers are always pushing for shorter timelines. They largely have no respect for reality. So, at some point they are given estimates just to make them feel better about planning.
 
No matter how much planning and estimation you do, it will be wrong. At best it will be directionally correct +/- 300% of what you estimated. So, a one year project could actually take anywhere between 0 and 5 years, maybe even 10 years.
 
If you think I’m joking, look at how many major ERP projects that go over time and over budget by many years and many hundreds of millions of dollars. Look at the F-35 fighter jet software issues.
 
Or in the small, you can find many cases where a “simple bug fix” can take days when you thought it was hours.
 
All estimates are lies made up to make everyone feel better. I’ve never met a developer or manager who could accurately estimate software projects even as well as the local weatherman(or woman) predicts the weather.
 
Number Two - Productivity Is Unevenly Distributed
 
What if I told you that in the average eight hour work day the majority of the work will get done in a 30 minute timeframe? Sound crazy?
 
Well, for most programmers there is a 30–90 minute window where you are extraordinarily productive. We call this the flow state.
 
Being in the flow state is wonderful and amazing. It often is where the “magic” of building software happens.
 
Getting into flow can be difficult. It’s akin to meditation in that you have to have a period of uninterrupted focus of say 30 minutes to “get in” the flow, but a tiny interruption can pull you right out.
 
Now consider the modern workplace environment. Programmers work in open office environments where they are invited to distract each other constantly.
 
Most people need a 1–2 hour uninterrupted block to get 30–90 minutes of flow.
 
Take the 8 hour day and break it in half with a lunch break, and then pile in a few meetings and all of a sudden you are lucky to get one decent flow state session in place.
 
That is why I say that most of the work that gets done happens in a 30 minute timeframe. The other 7–8 hours are spent being distracted, answering email, going to meetings, hanging around the water cooler, going to the bathroom, and trying to remember what you were working on before all these distractions.
 
Ironically, writers, musicians, and other creative professionals have their own version of this problem and largely work alone and away from other people when they are creating new things.
 
Someday the programming world might catch on, but I doubt it.
 
Even if this became obvious, it doesn’t sit well with most companies to think that programmers would be paid for an 8 hour day and only be cranking out code for a few hours on a good day. Some corporate middle manager would probably get the bright idea to have mandatory flow state training where a guru came in and then there would be a corporate policy from a pointy haired boss mandating that programmers are now required to spend 8 hours a day in flow state and they must fill out forms to track their time and notify their superiors of their flow state activities, otherwise there would be more meetings about the current flow state reports not being filed correctly and that programmers were spending too much time “zoning out” instead of being in flow.
 
Thus, programmers would spent 7–8 hours a day pretending to be in flow state, reporting on their progress, and getting all their work done in 30 minutes of accidental flow state somewhere in the middle of all that flow state reporting.
 
If you think I’m joking about this, I’m not. I promise you this is what would happen to any company of more than 2 employees. (Even the ones run by programmers.)
 
Number Three - It Will Cost 10x What You Think
 
Being a programmer, I get a lot of non-programmers telling me about their brilliant app ideas. Usually they want me to build something for free and are so generous as to pay me up to 5% of the profits for doing 100% of the work.
 
Their ideas are just that good.
 
Now, I gently tell them that I’m not interested in building anything for free.
 
At that point they get angry, but a few ask how much it will cost. I give them a reasonable (and very incorrect) estimate of what it would cost to create the incredibly simple version of their app idea.
 
Let’s say it’s some number like $25,000.
 
They look at me like I’m a lunatic, and so I explain how much it costs to hire a contract programmer and how long it will actually take. For example’s sake let’s say it is $100/hr for 250 hours.
 
To be clear, these are made up numbers and bad estimates (See Number One for details…)
 
In actuality, to build the actual thing they want might cost $250,000, or even $2,500,000 when it’s all said and done.
 
Building software can be incredibly complex and expensive. What most people can’t wrap their head around is the fact that a company like Google, Apple, or Microsoft has spent BILLIONS of dollars to create something that looks so simple to the end user.
 
Somehow, the assumption is that something that looks simple is cheap and fast to build.
 
Building something simple and easy for the end user is time consuming and expensive. Most people just can’t do it.
 
So, the average person with a brilliant app idea thinks it will cost a few hundred or maybe a few thousand dollars to make and it will be done in a weekend is so off the mark it’s not worth considering their ideas.
 
And programmers are too eager to play along with these bad ideas (by making bad estimates and under charging for their time) that this notion is perpetuated to the average non-programmer.
 
So, a good rule of thumb is that software will cost 10 times as much as you think and take 10 times as long to finish.
 
And that leads to a bonus point…
 
BONUS - Software Is Never Done
 
Programmers never complete a software project, they only stop working on it. Software is never done.
 
I’ve worked at many software companies and I’ve never seen a software project “completed”.
 
Sure, software gets released and used. But, it is always changing, being updated, bugs get fixed, and there are always new customer requests for features.
 
Look at your favorite software and you’ll quickly realize how true this is. Facebook, Instagram, Google Search, Google Maps, GMail, iOS, Android, Windows, and now even most video games are never done.
 
There are small armies of developers just trying to keep all the software you use every day stable and bug free. Add on the fact that there are always feature requests, small changes, and new platforms to deal with, it’s a treadmill.
 
So, the only way out of the game is to stop working on software. At that point, the software begins to decay until it is no longer secure or supported.
 
Think about old Windows 3.1 software or maybe old Nintendo Cartridge video games. The current computers and video game consoles don’t even attempt to run that software anymore.
 
You can’t put an old video game in your new Nintendo Switch and have it “just work”. That is what happens when you think software is done.
 
When programmers stop working on software the software starts to die. The code itself is probably fine, but all the other software keeps moving forward until your software is no longer compatible with the current technology.
 
So, those are the four most important things that non-programmers should know about programming. I know you asked for only three, so I hope the bonus was valuable to you as well.

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.

In programming, memory leaks are a common issue, and it occurs when a computer uses memory but does not give it back to the operating system. Experienced programmers have the ability to diagnose a leak based on the symptoms. Some believe every undesired increase in memory usage is a memory leak, but this is not an accurate representation of a leak. Certain leaks only run for a short time and are virtually undetectable.

Memory Leak Consequences

Applications that suffer severe memory leaks will eventually exceed the memory resulting in a severe slowdown or a termination of the application.

How to Protect Code from Memory Leaks?

Preventing memory leaks in the first place is more convenient than trying to locate the leak later. To do this, you can use defensive programming techniques such as smart pointers for C++.  A smart pointer is safer than a raw pointer because it provides augmented behavior that raw pointers do not have. This includes garbage collection and checking for nulls.

If you are going to use a raw pointer, avoid operations that are dangerous for specific contexts. This means pointer arithmetic and pointer copying. Smart pointers use a reference count for the object being referred to. Once the reference count reaches zero, the excess goes into garbage collection. The most commonly used smart pointer is shared_ptr from the TR1 extensions of the C++ standard library.

Static Analysis

The second approach to memory leaks is referred to as static analysis and attempts to detect errors in your source-code. CodeSonar is one of the effective tools for detection. It provides checkers for the Power of Ten coding rules, and it is especially competent at procedural analysis. However, some might find it lagging for bigger code bases.

How to Handle a Memory Leak

For some memory leaks, the only solution is to read through the code to find and correct the error. Another one of the common approaches to C++ is to use RAII, which an acronym for Resource Acquisition Is Initialization. This approach means associating scoped objects using the acquired resources, which automatically releases the resources when the objects are no longer within scope. RAII has the advantage of knowing when objects exist and when they do not. This gives it a distinct advantage over garbage collection. Regardless, RAII is not always recommended because some situations require ordinary pointers to manage raw memory and increase performance. Use it with caution.

The Most Serious Leaks

Urgency of a leak depends on the situation, and where the leak has occurred in the operating system. Additionally, it becomes more urgent if the leak occurs where the memory is limited such as in embedded systems and portable devices.

To protect code from memory leaks, people have to stay vigilant and avoid codes that could result in a leak. Memory leaks continue until someone turns the system off, which makes the memory available again, but the slow process of a leak can eventually prejudice a machine that normally runs correctly.

 

Related:

The Five Principles of Performance

In Demand IT Skills

One of the most significant developments of mankind has been the art of writing. The earliest type of writing was in the form of graffiti and paintings on rocks and walls of caves. The first people who engaged in writing are reported to have been Sumerians and the Egyptians around 3500-3200 BC.[i] Early writing of this type was in the form of cuneiform and hieroglyphics. After that, writing emerged in different styles and form per the different societies and differences in expression.

Words are magical. They have preserved records of civilizations. They express desires and dreams and thoughts. But why write at all? What was or is the motive for writing? People write for different reasons. Some write because they have something to say; something to share with others, to inform. Others write to share their feelings.

George Orwell claimed there are four main reasons why people write as depicted below:

·         Sheer Egoism: According to this concept, people write because they want to be talked about; they want to reveal their cleverness. People who are motivated by sheer egoism desire to be counted among the top crust of humanity such as scientists, artists, politicians, lawyers and successful businessmen who are always putting their thoughts in print.

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…
learn more
page tags
what brought you to visit us
Training/Chicago,  Python Programming Training , Training/Chicago,  Python Programming Training Classes, Training/Chicago,  Python Programming Training Courses, Training/Chicago,  Python Programming Training Course, Training/Chicago,  Python Programming Training Seminar

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