Microsoft Office Training Classes in Cathedral City, California
Learn Microsoft Office in Cathedral City, California 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 Microsoft Office related training offerings in Cathedral City, California: Microsoft Office Training
Microsoft Office Training Catalog
Course Directory [training on all levels]
- .NET Classes
- Agile/Scrum Classes
- Ajax Classes
- Android and iPhone Programming Classes
- Blaze Advisor Classes
- C Programming Classes
- C# Programming Classes
- C++ Programming Classes
- Cisco Classes
- Cloud Classes
- CompTIA Classes
- Crystal Reports Classes
- Design Patterns Classes
- DevOps Classes
- Foundations of Web Design & Web Authoring Classes
- Git, Jira, Wicket, Gradle, Tableau Classes
- IBM Classes
- Java Programming Classes
- JBoss Administration Classes
- JUnit, TDD, CPTC, Web Penetration Classes
- Linux Unix Classes
- Machine Learning Classes
- Microsoft Classes
- Microsoft Development Classes
- Microsoft SQL Server Classes
- Microsoft Team Foundation Server Classes
- Microsoft Windows Server Classes
- Oracle, MySQL, Cassandra, Hadoop Database Classes
- Perl Programming Classes
- Python Programming Classes
- Ruby Programming Classes
- Security Classes
- SharePoint Classes
- SOA Classes
- Tcl, Awk, Bash, Shell Classes
- UML Classes
- VMWare Classes
- Web Development Classes
- Web Services Classes
- Weblogic Administration Classes
- XML Classes
- Ruby Programming
2 December, 2024 - 4 December, 2024 - Introduction to Spring 5 (2022)
16 December, 2024 - 18 December, 2024 - Ruby on Rails
5 December, 2024 - 6 December, 2024 - Linux Fundaments GL120
9 December, 2024 - 13 December, 2024 - VMware vSphere 8.0 Boot Camp
9 December, 2024 - 13 December, 2024 - See our complete public course listing
Blog Entries publications that: entertain, make you think, offer insight
Here is a list of the organizations that use Python. This list is periodically updated by HSG’s software fans as well as the community at large.
Web Development
1. Yahoo Maps
Yahoo acquired Four11, whose address and mapping lookup services were implemented in Python. Yahoo Maps still uses Python today, as can be seen by examining its URLs.
2. Yahoo Groups
A comprehensive public archive of Internet mailing lists that was originally implemented in pure Python. At one point Scott Hassan, one of the founders of Findmail/eGroups (the company that was later acquired by Yahoo), reported that they had 180,000 lines of Python underlying everything from their 100% dynamic website to all email delivery, pumping out 200 messages/second on a single 400 MHz Pentium.
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.
Python and Ruby, each with roots going back into the 1990s, are two of the most popular interpreted programming languages today. Ruby is most widely known as the language in which the ubiquitous Ruby on Rails web application framework is written, but it also has legions of fans that use it for things that have nothing to do with the web. Python is a big hit in the numerical and scientific computing communities at the present time, rapidly displacing such longtime stalwarts as R when it comes to these applications. It too, however, is also put to a myriad of other uses, and the two languages probably vie for the title when it comes to how flexible their users find them.
A Matter of Personality...
That isn't to say that there aren't some major, immediately noticeable, differences between the two programming tongues. Ruby is famous for its flexibility and eagerness to please; it is seen by many as a cleaned-up continuation of Perl's "Do What I Mean" philosophy, whereby the interpreter does its best to figure out the meaning of evening non-canonical syntactic constructs. In fact, the language's creator, Yukihiro Matsumoto, chose his brainchild's name in homage to that earlier language's gemstone-inspired moniker.
Python, on the other hand, takes a very different tact. In a famous Python Enhancement Proposal called "The Zen of Python," longtime Pythonista Tim Peters declared it to be preferable that there should only be a single obvious way to do anything. Python enthusiasts and programmers, then, generally prize unanimity of style over syntactic flexibility compared to those who choose Ruby, and this shows in the code they create. Even Python's whitespace-sensitive parsing has a feel of lending clarity through syntactical enforcement that is very much at odds with the much fuzzier style of typical Ruby code.
For example, Python's much-admired list comprehension feature serves as the most obvious way to build up certain kinds of lists according to initial conditions:
a = [x**3 for x in range(10,20)]
b = [y for y in a if y % 2 == 0]
first builds up a list of the cubes of all of the numbers between 10 and 19 (yes, 19), assigning the result to 'a'. A second list of those elements in 'a' which are even is then stored in 'b'. One natural way to do this in Ruby is probably:
a = (10..19).map {|x| x ** 3}
b = a.select {|y| y.even?}
but there are a number of obvious alternatives, such as:
a = (10..19).collect do |x|
x ** 3
end
b = a.find_all do |y|
y % 2 == 0
end
It tends to be a little easier to come up with equally viable, but syntactically distinct, solutions in Ruby compared to Python, even for relatively simple tasks like the above. That is not to say that Ruby is a messy language, either; it is merely that it is somewhat freer and more forgiving than Python is, and many consider Python's relative purity in this regard a real advantage when it comes to writing clear, easily understandable code.
And Somewhat One of Performance
Memory management is always a priority in pretty much any programming language you would want to use. In the lower level languages such as C, there are a number of functions which help you manage the memory your application uses, but they are not the easiest to use. Some of the more modern programming languages such as Python, Ruby, Perl, and of course the subject of this article, Javascript all have a built in feature called garbage collection.
Garbage collection essentially means that the languages compiler will automatically free the memory being occupied by unused variables and objects, but there is no telling when this could occur. It is purely down to the compiler to decide when the garbage collection process should be initiated.
Tech Life in California
| Company Name | City | Industry | Secondary Industry |
|---|---|---|---|
| Mattel, Inc. | El Segundo | Retail | Sporting Goods, Hobby, Book, and Music Stores |
| Spectrum Group International, Inc. | Irvine | Retail | Retail Other |
| Chevron Corp | San Ramon | Energy and Utilities | Gasoline and Oil Refineries |
| Jacobs Engineering Group, Inc. | Pasadena | Real Estate and Construction | Construction and Remodeling |
| eBay Inc. | San Jose | Software and Internet | E-commerce and Internet Businesses |
| Broadcom Corporation | Irvine | Computers and Electronics | Semiconductor and Microchip Manufacturing |
| Franklin Templeton Investments | San Mateo | Financial Services | Investment Banking and Venture Capital |
| Pacific Life Insurance Company | Newport Beach | Financial Services | Insurance and Risk Management |
| Tutor Perini Corporation | Sylmar | Real Estate and Construction | Construction and Remodeling |
| SYNNEX Corporation | Fremont | Software and Internet | Data Analytics, Management and Storage |
| Core-Mark International Inc | South San Francisco | Manufacturing | Food and Dairy Product Manufacturing and Packaging |
| Occidental Petroleum Corporation | Los Angeles | Manufacturing | Chemicals and Petrochemicals |
| Yahoo!, Inc. | Sunnyvale | Software and Internet | Software and Internet Other |
| Edison International | Rosemead | Energy and Utilities | Gas and Electric Utilities |
| Ingram Micro, Inc. | Santa Ana | Computers and Electronics | Consumer Electronics, Parts and Repair |
| Safeway, Inc. | Pleasanton | Retail | Grocery and Specialty Food Stores |
| Gilead Sciences, Inc. | San Mateo | Healthcare, Pharmaceuticals and Biotech | Pharmaceuticals |
| AECOM Technology Corporation | Los Angeles | Real Estate and Construction | Architecture,Engineering and Design |
| Reliance Steel and Aluminum | Los Angeles | Manufacturing | Metals Manufacturing |
| Live Nation, Inc. | Beverly Hills | Media and Entertainment | Performing Arts |
| Advanced Micro Devices, Inc. | Sunnyvale | Computers and Electronics | Semiconductor and Microchip Manufacturing |
| Pacific Gas and Electric Corp | San Francisco | Energy and Utilities | Gas and Electric Utilities |
| Electronic Arts Inc. | Redwood City | Software and Internet | Games and Gaming |
| Oracle Corporation | Redwood City | Software and Internet | Software and Internet Other |
| Symantec Corporation | Mountain View | Software and Internet | Data Analytics, Management and Storage |
| Dole Food Company, Inc. | Thousand Oaks | Manufacturing | Food and Dairy Product Manufacturing and Packaging |
| CBRE Group, Inc. | Los Angeles | Real Estate and Construction | Real Estate Investment and Development |
| First American Financial Corporation | Santa Ana | Financial Services | Financial Services Other |
| The Gap, Inc. | San Francisco | Retail | Clothing and Shoes Stores |
| Ross Stores, Inc. | Pleasanton | Retail | Clothing and Shoes Stores |
| Qualcomm Incorporated | San Diego | Telecommunications | Wireless and Mobile |
| Charles Schwab Corporation | San Francisco | Financial Services | Securities Agents and Brokers |
| Sempra Energy | San Diego | Energy and Utilities | Gas and Electric Utilities |
| Western Digital Corporation | Irvine | Computers and Electronics | Consumer Electronics, Parts and Repair |
| Health Net, Inc. | Woodland Hills | Healthcare, Pharmaceuticals and Biotech | Healthcare, Pharmaceuticals, and Biotech Other |
| Allergan, Inc. | Irvine | Healthcare, Pharmaceuticals and Biotech | Biotechnology |
| The Walt Disney Company | Burbank | Media and Entertainment | Motion Picture and Recording Producers |
| Hewlett-Packard Company | Palo Alto | Computers and Electronics | Consumer Electronics, Parts and Repair |
| URS Corporation | San Francisco | Real Estate and Construction | Architecture,Engineering and Design |
| Cisco Systems, Inc. | San Jose | Computers and Electronics | Networking Equipment and Systems |
| Wells Fargo and Company | San Francisco | Financial Services | Banks |
| Intel Corporation | Santa Clara | Computers and Electronics | Semiconductor and Microchip Manufacturing |
| Applied Materials, Inc. | Santa Clara | Computers and Electronics | Semiconductor and Microchip Manufacturing |
| Sanmina Corporation | San Jose | Computers and Electronics | Semiconductor and Microchip Manufacturing |
| Agilent Technologies, Inc. | Santa Clara | Telecommunications | Telecommunications Equipment and Accessories |
| Avery Dennison Corporation | Pasadena | Manufacturing | Paper and Paper Products |
| The Clorox Company | Oakland | Manufacturing | Chemicals and Petrochemicals |
| Apple Inc. | Cupertino | Computers and Electronics | Consumer Electronics, Parts and Repair |
| Amgen Inc | Thousand Oaks | Healthcare, Pharmaceuticals and Biotech | Biotechnology |
| McKesson Corporation | San Francisco | Healthcare, Pharmaceuticals and Biotech | Pharmaceuticals |
| DIRECTV | El Segundo | Telecommunications | Cable Television Providers |
| Visa, Inc. | San Mateo | Financial Services | Credit Cards and Related Services |
| Google, Inc. | Mountain View | Software and Internet | E-commerce and Internet Businesses |
training details locations, tags and why hsg
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 California 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 Microsoft Office programming
- Get your questions answered by easy to follow, organized Microsoft Office experts
- Get up to speed with vital Microsoft Office 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…
Interesting Reads Take a class with us and receive a book of your choosing for 50% off MSRP.
