Linux Unix Training Classes in Saginaw, Michigan

Learn Linux Unix in Saginaw, Michigan 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 Linux Unix related training offerings in Saginaw, Michigan: Linux Unix Training

We offer private customized training for groups of 3 or more attendees.
Saginaw  Upcoming Instructor Led Online and Public Linux Unix Training Classes
ANSIBLE Training/Class 24 August, 2020 - 26 August, 2020 $1990
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
Linux Troubleshooting Training/Class 20 July, 2020 - 24 July, 2020 $2290
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
Enterprise Linux System Administration Training/Class 27 July, 2020 - 31 July, 2020 $2190
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
Docker Training/Class 10 August, 2020 - 12 August, 2020 $1690
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
LINUX PERFORMANCE TUNING AND ANALYSIS Training/Class 31 August, 2020 - 3 September, 2020 $2490
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
DOCKER WITH KUBERNETES ADMINISTRATION Training/Class 27 July, 2020 - 31 July, 2020 $2490
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
ENTERPRISE LINUX HIGH AVAILABILITY CLUSTERING Training/Class 3 August, 2020 - 6 August, 2020 $2590
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
HADOOP FOR SYSTEMS ADMINISTRATORS Training/Class 16 November, 2020 - 18 November, 2020 $1890
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
LINUX SHELL SCRIPTING Training/Class 17 September, 2020 - 18 September, 2020 $990
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
Introduction to Linux for Developers (LFD211) Training/Class 13 July, 2020 - 14 July, 2020 $930
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
Developing Applications For Linux (LFD401) Training/Class 13 July, 2020 - 16 July, 2020 $2800
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
Embedded Linux Development with Yocto Project (LFD460) Training/Class 20 July, 2020 - 23 July, 2020 $2800
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
Linux Kernel Debugging and Security (LFD440) Training/Class 10 August, 2020 - 13 August, 2020 $2800
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
Linux Kernel Internals and Development (LFD420) Training/Class 27 July, 2020 - 30 July, 2020 $2800
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
Linux System Administration (LFS301) Training/Class 3 August, 2020 - 6 August, 2020 $2800
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
Linux Performance Tuning (LFS426) Training/Class 27 July, 2020 - 30 July, 2020 $2800
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration
Developing Linux Device Drivers (LFD430) Training/Class 3 August, 2020 - 6 August, 2020 $2800
HSG Training Center
Saginaw, Michigan
Hartmann Software Group Training Registration

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Linux Unix Training Catalog

cost: $ 1390length: 4 day(s)
cost: $ 1990length: 3 day(s)
cost: $ 1090length: 3 day(s)
cost: $ 2090length: 5 day(s)

DevOps Classes

cost: $ 1690length: 3 day(s)

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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

I will begin our blog on Java Tutorial with an incredibly important aspect of java development:  memory management.  The importance of this topic should not be minimized as an application's performance and footprint size are at stake.

From the outset, the Java Virtual Machine (JVM) manages memory via a mechanism known as Garbage Collection (GC).  The Garbage collector

  • Manages the heap memory.   All obects are stored on the heap; therefore, all objects are managed.  The keyword, new, allocates the requisite memory to instantiate an object and places the newly allocated memory on the heap.  This object is marked as live until it is no longer being reference.
  • Deallocates or reclaims those objects that are no longer being referened. 
  • Traditionally, employs a Mark and Sweep algorithm.  In the mark phase, the collector identifies which objects are still alive.  The sweep phase identifies objects that are no longer alive.
  • Deallocates the memory of objects that are not marked as live.
  • Is automatically run by the JVM and not explicitely called by the Java developer.  Unlike languages such as C++, the Java developer has no explict control over memory management.
  • Does not manage the stack.  Local primitive types and local object references are not managed by the GC.

So if the Java developer has no control over memory management, why even worry about the GC?  It turns out that memory management is an integral part of an application's performance, all things being equal.  The more memory that is required for the application to run, the greater the likelihood that computational efficiency suffers. To that end, the developer has to take into account the amount of memory being allocated when writing code.  This translates into the amount of heap memory being consumed.

Memory is split into two types:  stack and heap.  Stack memory is memory set aside for a thread of execution e.g. a function.  When a function is called, a block of memory is reserved for those variables local to the function, provided that they are either a type of Java primitive or an object reference.  Upon runtime completion of the function call, the reserved memory block is now available for the next thread of execution.  Heap memory, on the otherhand, is dynamically allocated.  That is, there is no set pattern for allocating or deallocating this memory.  Therefore, keeping track or managing this type of memory is a complicated process. In Java, such memory is allocated when instantiating an object:

String s = new String();  // new operator being employed
String m = "A String";    /* object instantiated by the JVM and then being set to a value.  The JVM
calls the new operator */

The short answer is, yes and no. It depends upon who you are. The purpose of this entry is to help you determine, yes or no.

Full disclosure. This entry is created on a Mac mini. And doing so on Windows 8 (Release Preview). If you are a developer, in my humble opinion you need to test on all platforms you expect your app to run or you are not much of a developer.

To be successful you need to leave politics in geographical territory known as Washington DC. My definition of that is: 14 mi.² of real estate surrounded by reality.

Only in politics can we afford to take sides. Those of us in IT, especially developers need to do our best to be all things to all people. Certainly this is a technical impossibility. However in our game we can get some points for at least being serviceable if not outstanding.

Machine learning systems are equipped with artificial intelligence engines that provide these systems with the capability of learning by themselves without having to write programs to do so. They adjust and change programs as a result of being exposed to big data sets. The process of doing so is similar to the data mining concept where the data set is searched for patterns. The difference is in how those patterns are used. Data mining's purpose is to enhance human comprehension and understanding. Machine learning's algorithms purpose is to adjust some program's action without human supervision, learning from past searches and also continuously forward as it's exposed to new data.

The News Feed service in Facebook is an example, automatically personalizing a user's feed from his interaction with his or her friend's posts. The "machine" uses statistical and predictive analysis that identify interaction patterns (skipped, like, read, comment) and uses the results to adjust the News Feed output continuously without human intervention. 

Impact on Existing and Emerging Markets

The NBA is using machine analytics created by a California-based startup to create predictive models that allow coaches to better discern a player's ability. Fed with many seasons of data, the machine can make predictions of a player's abilities. Players can have good days and bad days, get sick or lose motivation, but over time a good player will be good and a bad player can be spotted. By examining big data sets of individual performance over many seasons, the machine develops predictive models that feed into the coach’s decision-making process when faced with certain teams or particular situations. 

General Electric, who has been around for 119 years is spending millions of dollars in artificial intelligence learning systems. Its many years of data from oil exploration and jet engine research is being fed to an IBM-developed system to reduce maintenance costs, optimize performance and anticipate breakdowns.

Over a dozen banks in Europe replaced their human-based statistical modeling processes with machines. The new engines create recommendations for low-profit customers such as retail clients, small and medium-sized companies. The lower-cost, faster results approach allows the bank to create micro-target models for forecasting service cancellations and loan defaults and then how to act under those potential situations. As a result of these new models and inputs into decision making some banks have experienced new product sales increases of 10 percent, lower capital expenses and increased collections by 20 percent. 

Emerging markets and industries

By now we have seen how cell phones and emerging and developing economies go together. This relationship has generated big data sets that hold information about behaviors and mobility patterns. Machine learning examines and analyzes the data to extract information in usage patterns for these new and little understood emergent economies. Both private and public policymakers can use this information to assess technology-based programs proposed by public officials and technology companies can use it to focus on developing personalized services and investment decisions.

Machine learning service providers targeting emerging economies in this example focus on evaluating demographic and socio-economic indicators and its impact on the way people use mobile technologies. The socioeconomic status of an individual or a population can be used to understand its access and expectations on education, housing, health and vital utilities such as water and electricity. Predictive models can then be created around customer's purchasing power and marketing campaigns created to offer new products. Instead of relying exclusively on phone interviews, focus groups or other kinds of person-to-person interactions, auto-learning algorithms can also be applied to the huge amounts of data collected by other entities such as Google and Facebook.

A warning

Traditional industries trying to profit from emerging markets will see a slowdown unless they adapt to new competitive forces unleashed in part by new technologies such as artificial intelligence that offer unprecedented capabilities at a lower entry and support cost than before. But small high-tech based companies are introducing new flexible, adaptable business models more suitable to new high-risk markets. Digital platforms rely on algorithms to host at a low cost and with quality services thousands of small and mid-size enterprises in countries such as China, India, Central America and Asia. These collaborations based on new technologies and tools gives the emerging market enterprises the reach and resources needed to challenge traditional business model companies.

Creating an enum in Python prior to Python 3.4 was accomplished as follows:

 

def enum(**enums)::
      return type('Enum',(),enums)

then use as:

Animals=enum(Dog=1,Cat=2)

and accessed as:

Animals.Dog

The new version can be created as follows:

from enum import Enum

class Animal(Enum):
    Dog=1
    Cat=2

Tech Life in Michigan

Home of the Ford Motor Company and many other Fortune 500 and Fortune 1000 Companies, Michigan has a list of famous people that have made their mark on society. Famous Michiganians: Francis Ford Coppola film director; Henry Ford industrialist, Earvin Magic Johnson basketball player; Charles A. Lindbergh aviator; Madonna singer; Stevie Wonder singer; John T. Parsons inventor and William R. Hewlett inventor.
You can't know too much, but you can say too much.  ~ Calvin Coolidge
other Learning Options
Software developers near Saginaw have ample opportunities to meet like minded techie individuals, collaborate and expend their career choices by participating in Meet-Up Groups. The following is a list of Technology Groups in the area.
Fortune 500 and 1000 companies in Michigan that offer opportunities for Linux Unix developers
Company Name City Industry Secondary Industry
Lear Corporation Southfield Manufacturing Automobiles, Boats and Motor Vehicles
TRW Automotive Holdings Corp. Livonia Manufacturing Automobiles, Boats and Motor Vehicles
Spartan Stores, Inc. Byron Center Retail Grocery and Specialty Food Stores
Steelcase Inc. Grand Rapids Manufacturing Furniture Manufacturing
Valassis Communications, Inc. Livonia Business Services Advertising, Marketing and PR
Autoliv, Inc. Auburn Hills Manufacturing Automobiles, Boats and Motor Vehicles
Cooper-Standard Automotive Group Novi Manufacturing Automobiles, Boats and Motor Vehicles
Penske Automotive Group, Inc. Bloomfield Hills Retail Automobile Dealers
Con-Way Inc. Ann Arbor Transportation and Storage Freight Hauling (Rail and Truck)
Meritor, Inc. Troy Manufacturing Automobiles, Boats and Motor Vehicles
Visteon Corporation Van Buren Twp Manufacturing Automobiles, Boats and Motor Vehicles
Affinia Group, Inc. Ann Arbor Manufacturing Automobiles, Boats and Motor Vehicles
Perrigo Company Allegan Healthcare, Pharmaceuticals and Biotech Pharmaceuticals
BorgWarner Inc. Auburn Hills Manufacturing Automobiles, Boats and Motor Vehicles
Auto-Owners Insurance Lansing Financial Services Insurance and Risk Management
DTE Energy Company Detroit Energy and Utilities Gas and Electric Utilities
Whirlpool Corporation Benton Harbor Manufacturing Tools, Hardware and Light Machinery
Herman Miller, Inc. Zeeland Manufacturing Furniture Manufacturing
Universal Forest Products Grand Rapids Manufacturing Furniture Manufacturing
Masco Corporation Inc. Taylor Manufacturing Concrete, Glass, and Building Materials
PULTEGROUP, INC. Bloomfield Hills Real Estate and Construction Real Estate & Construction Other
CMS Energy Corporation Jackson Energy and Utilities Energy and Utilities Other
Stryker Corporation Portage Healthcare, Pharmaceuticals and Biotech Medical Devices
General Motors Company (GM) Detroit Manufacturing Automobiles, Boats and Motor Vehicles
Kellogg Company Battle Creek Manufacturing Food and Dairy Product Manufacturing and Packaging
The Dow Chemical Company Midland Manufacturing Chemicals and Petrochemicals
Kelly Services, Inc. Troy Business Services HR and Recruiting Services
Ford Motor Company Dearborn Manufacturing Automobiles, Boats and Motor Vehicles

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 in Michigan 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 Linux Unix programming
  • Get your questions answered by easy to follow, organized Linux Unix experts
  • Get up to speed with vital Linux Unix 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.