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, ...

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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.”

With an ever increasing rise in the use of employment testing, certification testing and need to get a degree, I thought I would write this basic guide on how to study for exams.  Although it was originally written with the college student in mind, the fundamentals still apply to all of us in the workforce.

There are few things that strike terror into the hearts of students more than exam day, particularly if they have inadequate study skills. Perhaps these students study for hours and hours, only to discover that by exam time they've forgotten everything they've read. Below are a few study tips to help struggling students remember the information they've reviewed for their exams. 

-Use memory tricks. There are a number of memory tricks that you can use to help you remember large amounts of information. For example, the use of acronyms (such as Roy G Biv to remember the colors of the rainbow) can be very helpful. In addition, you can use visualization techniques, similes, and songs to assist you in recalling your study material.

-Don't cram. Your brain requires time to absorb facts. If you know about a test in advance, start studying right away for a little bit every day, ramping up your efforts as the exam approaches.

-Take frequent breaks while studying. It may seem counter-intuitive that spending less time studying might actually help you remember more of what you've read. But taking appropriately timed study breaks will keep your mind fresh and make sure you don't stress too much.

-Write it out. For many people, writing information down as they read it is the best way to learn it. Don't just write exactly what you read, however; by rewording the information or even drawing a picture or diagram you commit it to your memory in more than one way, allowing you to remember it easier later.

-Teach it to a friend. To remember information, you have to understand it. And in order to teach information, you need to understand it as well. Nothing tests your ability to recall facts better than teaching them to another person. Find a friend unfamiliar with your study material and teach them a lesson in the subject.

-Get plenty of sleep the night before the exam. Finally, be sure to get a good night's rest the night before you take the exam. Falling asleep at your desk will accomplish nothing. This will help you be more alert while you are taking your test, and will allow you to retain more information.

 

Being treated like a twelve year old at work by a Tasmanian-devil-manager and not sure what to do about it? It is simply a well-known fact that no one likes to be micro managed. Not only do they not like to be micro managed, but tend to quit for this very reason. Unfortunately the percentage of people leaving their jobs for this reason is higher that you would imagine. Recently, an employee retention report conducted by TINYpulse, an employee engagement firm, surveyed 400 full-time U.S. employees concluded that, "supervisors can make or break employee retention."

As companies mature, their ability to manage can be significant to their bottom line as employee morale, high staff turnover and the cost of training new employees can easily reduce productivity and consequently client satisfaction.  In many cases, there is a thin line between effective managing and micro managing practices. Most managers avoid micro managing their employees. However, a decent percentage of them have yet to find effective ways to get the most of their co-workers.  They trap themselves by disempowering people's ability to do their work when they hover over them and create an unpleasant working environment. This behavior may come in the form of incessant emailing, everything having to be done a certain way (their way), desk hovering, and a need to control every part of an enterprise, no matter how small.

Superimpose the micro manager into the popular practice of Agile-SCRUM methodology and you can imagine the creative ways they can monitor everything in a team, situation, or place. Although, not always a bad thing, excessive control, can lead to burnout of managers and teams alike.  As predicted, agile project management has become increasingly popular in the last couple of decades in project planning, particularly in software development.  Agile methodology when put into practice, especially in IT, can mean releasing faster functional software than with the traditional development methods. When done right, it enables users to get some of the business benefits of the new software faster as well as enabling the software team to get rapid feedback on the software's scope and direction.

Despite its advantages, most organizations have not been able to go “all agile” at once. Rather, some experiment with their own interpretation of agile when transitioning.  A purist approach for instance, can lead to an unnecessarily high agile project failure, especially for those that rely on tight controls, rigid structures and cost-benefit analysis.  As an example, a premature and rather rapid replacement of traditional development without fully understating the implications of the changeover process or job roles within the project results in failure for many organizations.  

As part of our Java Tutorials program, we will list a number of interview questions to aid in a better understaing of Java and J2EE and, hopefully, provide a greater likelihood of getting a job.  Let us begin with the basics:

1. What is meant by J2EE?

J2EE is an abreviation for Java 2 Platform Enterprise Edition

2.  What is the purpose of J2EE?

The purpose of J2EE is to provide a component based platform in a multitier application model with transaction management, web services and reusable component support.

3.  What is the tier structure of the typical J2EE application?

A typical J2EE application consists of the following tiers/machines:  the client machine (browser/non-browser application), the J2EE server (an application server such as Oracle, JBoss, GlassFish, Tomcat) and a database.

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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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