AI Training Classes in Appleton, Wisconsin
Learn AI in Appleton, Wisconsin 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 AI related training offerings in Appleton, Wisconsin: AI Training
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16 June, 2025 - 20 June, 2025 - RED HAT ENTERPRISE LINUX SYSTEMS ADMIN II
18 August, 2025 - 21 August, 2025 - VMware vSphere 8.0 Skill Up
18 August, 2025 - 22 August, 2025 - LINUX SHELL SCRIPTING
30 June, 2025 - 1 July, 2025 - Python for Scientists
4 August, 2025 - 8 August, 2025 - See our complete public course listing
Blog Entries publications that: entertain, make you think, offer insight
I’ve been a technical recruiter for several years, let’s just say a long time. I’ll never forget how my first deal went bad and the lesson I learned from that experience. I was new to recruiting but had been a very good sales person in my previous position. I was about to place my first contractor on an assignment. I thought everything was fine. I nurtured and guided my candidate through the interview process with constant communication throughout. The candidate was very responsive throughout the process. From my initial contact with him, to the phone interview all went well and now he was completing his onsite interview with the hiring manager.
Shortly thereafter, I received the call from the hiring manager that my candidate was the chosen one for the contract position, I was thrilled. All my hard work had paid off. I was going to be a success at this new game! The entire office was thrilled for me, including my co-workers and my bosses. I made a good win-win deal. It was good pay for my candidate and a good margin for my recruiting firm. Everyone was happy.
I left a voicemail message for my candidate so I could deliver the good news. He had agreed to call me immediately after the interview so I could get his assessment of how well it went. Although, I heard from the hiring manager, there was no word from him. While waiting for his call back, I received a call from a Mercedes dealership to verify his employment for a car he was trying to lease. Technically he wasn’t working for us as he had not signed the contract yet…. nor, had he discussed this topic with me. I told the Mercedes office that I would get back to them. Still not having heard back from the candidate, I left him another message and mentioned the call I just received. Eventually he called back. He wanted more money.
I told him that would be impossible as he and I had previously agreed on his hourly rate and it was fine with him. I asked him what had changed since that agreement. He said he made had made much more money in doing the same thing when he lived in California. I reminded him this is a less costly marketplace than where he was living in California. I told him if he signed the deal I would be able to call the car dealership back and confirm that he was employed with us. He agreed to sign the deal.
Another blanket article about the pros and cons of Direct to Consumer (D2C) isn’t needed, I know. By now, we all know the rules for how this model enters a market: its disruption fights any given sector’s established sales model, a fuzzy compromise is temporarily met, and the lean innovator always wins out in the end.
That’s exactly how it played out in the music industry when Apple and record companies created a digital storefront in iTunes to usher music sales into the online era. What now appears to have been a stopgap compromise, iTunes was the standard model for 5-6 years until consumers realized there was no point in purchasing and owning digital media when internet speeds increased and they could listen to it for free through a music streaming service. In 2013, streaming models are the new music consumption standard. Netflix is nearly parallel in the film and TV world, though they’ve done a better job keeping it all under one roof. Apple mastered retail sales so well that the majority of Apple products, when bought in-person, are bought at an Apple store. That’s even more impressive when you consider how few Apple stores there are in the U.S. (253) compared to big box electronics stores that sell Apple products like Best Buy (1,100) Yet while some industries have implemented a D2C approach to great success, others haven’t even dipped a toe in the D2C pool, most notably the auto industry.
What got me thinking about this topic is the recent flurry of attention Tesla Motors has received for its D2C model. It all came to a head at the beginning of July when a petition on whitehouse.gov to allow Tesla to sell directly to consumers in all 50 states reached the 100,000 signatures required for administration comment. As you might imagine, many powerful car dealership owners armed with lobbyists have made a big stink about Elon Musk, Tesla’s CEO and Product Architect, choosing to sidestep the traditional supply chain and instead opting to sell directly to their customers through their website. These dealership owners say that they’re against the idea because they want to protect consumers, but the real motive is that they want to defend their right to exist (and who wouldn’t?). They essentially have a monopoly at their position in the sales process, and they want to keep it that way. More frightening for the dealerships is the possibility that once Tesla starts selling directly to consumers, so will the big three automakers, and they fear that would be the end of the road for their business. Interestingly enough, the big three flirted with the idea of D2C in the early 90’s before they were met with fierce backlash from dealerships. I’m sure the dealership community has no interest in mounting a fight like that again.
To say that the laws preventing Tesla from selling online are peripherally relevant would be a compliment. By and large, the laws the dealerships point to fall under the umbrella of “Franchise Laws” that were put in place at the dawn of car sales to protect franchisees against manufacturers opening their own stores and undercutting the franchise that had invested so much to sell the manufacturer’s cars. There’s certainly a need for those laws to exist, because no owner of a dealership selling Jeeps wants Chrysler to open their own dealership next door and sell them for substantially less. However, because Tesla is independently owned and isn’t currently selling their cars through any third party dealership, this law doesn’t really apply to them. Until their cars are sold through independent dealerships, they’re incapable of undercutting anyone by implementing D2C structure.
You may use the camera application on a regular basis. Taking photos of family gatherings, of the scenery around you, or just a self-photo with you and your friends. But, as you may find out, pressing that picture button on the screen is not the easiest thing to do. You may not hit it when you attempt to press it, or you aren’t sure if you pressed it at all.
In a recent update by Apple, the iPhone can now take photos without the use of that button. Although you may continue to use it, an easier method to take photos would definitely be pressing your volume buttons. When you have everyone situated, and ready to take a picture, you don’t have to move your finger over to the camera button. Just put your finger on one of the volume keys on the left hand side of your phone, and press it, and your iPhone should take the picture! It’s just that easy.
Writing Python in Java syntax is possible with a semi-automatic tool. Programming code translation tools pick up about 75% of dynamically typed language. Conversion of Python to a statically typed language like Java requires some manual translation. The modern Java IDE can be used to infer local variable type definitions for each class attribute and local variable.
Translation of Syntax
Both Python and Java are OO imperative languages with sizable syntax constructs. Python is larger, and more competent for functional programming concepts. Using the source translator tool, parsing of the original Python source language will allow for construction of an Abstract Source Tree (AST), followed by conversion of the AST to Java.
Python will parse itself. This capability is exhibited in the ast module, which includes skeleton classes. The latter can be expanded to parse and source each node of an AST. Extension of the ast.NodeVisitor class enables python syntax constructs to be customized using translate.py and parser.py coding structure.
The Concrete Syntax Tree (CST) for Java is based on visit to the AST. Java string templates can be output at AST nodes with visitor.py code. Comment blocks are not retained by the Python ast Parser. Conversion of Python to multi-line string constructs with the translator reduces time to script.
Scripting Python Type Inference in Java
Programmers using Python source know that the language does not contain type information. The fact that Python is a dynamic type language means object type is determined at run time. Python is also not enforced at compile time, as the source is not specified. Runtime type information of an object can be determined by inspecting the __class__.__name__ attribute.
Python’s inspect module is used for constructing profilers and debugging.
Implementation of def traceit (frame, event, arg) method in Python, and connecting it to the interpreter with sys.settrace (traceit) allows for integration of multiple events during application runtime.
Method call events prompt inspect and indexing of runtime type. Inspection of all method arguments can be conducted. By running the application profiler and exercising the code, captured trace files for each source file can be modified with the translator. Generating method syntax can be done with the translator by search and addition of type information. Results in set or returned variables disseminate the dynamic code in static taxonomy.
The final step in the Python to Java scrip integration is to administer unsupported concepts such as value object creation. There is also the task of porting library client code, for reproduction in Java equivalents. Java API stubs can be created to account for Python APIs. Once converted to Java the final clean-up of the script is far easier.
Related:
What Are The 10 Most Famous Software Programs Written in Python?
Tech Life in Wisconsin
Company Name | City | Industry | Secondary Industry |
---|---|---|---|
We Energies | Milwaukee | Energy and Utilities | Gas and Electric Utilities |
Bemis Company, Inc. | Neenah | Manufacturing | Plastics and Rubber Manufacturing |
Regal Beloit Corporation | Beloit | Manufacturing | Tools, Hardware and Light Machinery |
Manitowoc Company, Inc | Manitowoc | Manufacturing | Heavy Machinery |
Briggs and Stratton Corporation | Milwaukee | Manufacturing | Tools, Hardware and Light Machinery |
Mortgage Guaranty Insurance Corporation (MGIC) | Milwaukee | Financial Services | Lending and Mortgage |
A.O. Smith Corporation | Milwaukee | Manufacturing | Tools, Hardware and Light Machinery |
Sentry Insurance | Stevens Point | Financial Services | Insurance and Risk Management |
Rockwell Automation, Inc. | Milwaukee | Manufacturing | Tools, Hardware and Light Machinery |
Bucyrus International, Inc. | South Milwaukee | Manufacturing | Heavy Machinery |
Diversey, Inc. | Sturtevant | Manufacturing | Chemicals and Petrochemicals |
Alliant Energy Corporation | Madison | Energy and Utilities | Gas and Electric Utilities |
Plexus Corp. | Neenah | Manufacturing | Manufacturing Other |
Spectrum Brands Holdings, Inc. | Madison | Manufacturing | Tools, Hardware and Light Machinery |
Kohl's Corporation | Menomonee Falls | Retail | Department Stores |
Snap-on Tools, Inc. | Kenosha | Manufacturing | Tools, Hardware and Light Machinery |
Fiserv, Inc. | Brookfield | Software and Internet | Data Analytics, Management and Storage |
CUNA Mutual Group | Madison | Financial Services | Insurance and Risk Management |
Oshkosh Corporation | Oshkosh | Manufacturing | Heavy Machinery |
Modine Manufacturing Company | Racine | Manufacturing | Manufacturing Other |
Northwestern Mutual Life Insurance Company | Milwaukee | Financial Services | Insurance and Risk Management |
Joy Global Inc. | Milwaukee | Manufacturing | Heavy Machinery |
Harley-Davidson, Inc. | Milwaukee | Manufacturing | Automobiles, Boats and Motor Vehicles |
American Family Insurance | Madison | Financial Services | Insurance and Risk Management |
Johnson Controls, Inc. | Milwaukee | Manufacturing | Heavy Machinery |
ManpowerGroup | Milwaukee | Business Services | HR and Recruiting Services |
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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.
- We have provided software development and other IT related training to many major corporations in Wisconsin since 2002.
- 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 AI programming
- Get your questions answered by easy to follow, organized AI experts
- Get up to speed with vital AI 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…