Google for Business Training Classes in Montebello, California

Learn Google for Business in Montebello, 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 Google for Business related training offerings in Montebello, California: Google for Business Training

We offer private customized training for groups of 3 or more attendees.
Montebello  Upcoming Instructor Led Online and Public Google for Business Training Classes
Using Google Drive and Productivity Apps Training/Class 20 April, 2020 - 20 April, 2020 $390
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Montebello, California
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Wondering why Cisco is teaching network engineers Python in addition to their core expertise?
 
Yes, arguably there are many other tools available to use to automate the network without writing any code. It is also true that when code is absolutely necessary, in most companies software developers will write the code for the network engineers. However, networks are getting progressively more sophisticated and the ability for network engineers to keep up with the rate of change, scale of networks, and processing of requirements is becoming more of a challenge with traditional methodologies. 
 
Does that mean that all network engineers have to become programmers in the future? Not completely, but having certain tools in your tool belt may be the deciding factor in new or greater career opportunities. The fact is that current changes in the industry will require Cisco engineers to become proficient in programming, and the most common programming language for this new environment is the Python programming language. Already there are more opportunities for those who can understand programming and can also apply it to traditional networking practices. 
 
Cisco’s current job boards include a search for a Sr. Network Test Engineer and for several Network Consulting Engineers, each with  "competitive knowledge" desired Python and Perl skills. Without a doubt, the most efficient network engineers in the future will be the ones who will be able to script their automated network-related tasks, create their own services directly in the network, and continuously modify their scripts. 
 
Whether you are forced to attend or are genuinely interested in workshops or courses that cover the importance of learning topics related to programmable networks such as Python, the learning curve at the very least will provide you with an understanding of Python scripts and the ability to be able to use them instead of the CLI commands and the copy and paste options commonly used.  Those that plan to cling to their CLI will soon find themselves obsolete.
 
As with anything new, learning a programming language and using new APIs for automation will require engineers to learn and master the skills before deploying widely across their network. The burning question is where to start and which steps to take next? 
 
In How Do I Get Started Learning Network Programmability?  Hank Preston – on the Cisco blog page suggest a three phase approach to diving into network programmability.
 
“Phase 1: Programming Basics
In this first phase you need to build a basic foundation in the programmability skills, topics, and technologies that will be instrumental in being successful in this journey.  This includes learning basic programming skills like variables, operations, conditionals, loops, etc.  And there really is no better language for network engineers to leverage today than Python.  Along with Python, you should explore APIs (particularly REST APIs), data formats like JSON, XML, and YAML. And if you don’t have one already, sign up for a GitHub account and learn how to clone, pull, and push to repos.
 
Phase 2: Platform Topics
Once you have the programming fundamentals squared away (or at least working on squaring them away) the time comes to explore the new platforms of Linux, Docker, and “the Cloud.”  As applications are moving from x86 virtualization to micro services, and now serverless, the networks you build will be extending into these new areas and outside of traditional physical network boxes.  And before you can intelligently design or engineer the networks for those environments, you need to understand how they basically work.  The goal isn’t to become a big bushy beard wearing Unix admin, but rather to become comfortable working in these areas.
 
Phase 3: Networking for Today and Tomorrow
Now you are ready to explore the details of networking in these new environments.  In phase three you will dive deep into Linux, container/Docker, cloud, and micro service networking.  You have built the foundation of knowledge needed to take a hard look at how networking works inside these new environments.  Explore all the new technologies, software, and strategies for implementing and segmenting critical applications in the “cloud native” age and add value to the application projects.”
 
Community resources: 
GitHub’s, PYPL Popularity of Programming Language lists Python as having grown 13.2% in demand in the last 5 years. 
Python in the  June 2018 TIOBE Index ranks as the fourth most popular language behind Java, C and C++. 
 
Despite the learning curve, having Python in your tool belt is without a question a must have tool.

It is said that spoken languages shape thoughts by their inclusion and exclusion of concepts, and by structuring them in different ways. Similarly, programming languages shape solutions by making some tasks easier and others less aesthetic. Using F# instead of C# reshapes software projects in ways that prefer certain development styles and outcomes, changing what is possible and how it is achieved.

F# is a functional language from Microsoft's research division. While once relegated to the land of impractical academia, the principles espoused by functional programming are beginning to garner mainstream appeal.

As its name implies, functions are first-class citizens in functional programming. Blocks of code can be stored in variables, passed to other functions, and infinitely composed into higher-order functions, encouraging cleaner abstractions and easier testing. While it has long been possible to store and pass code, F#'s clean syntax for higher-order functions encourages them as a solution to any problem seeking an abstraction.

F# also encourages immutability. Instead of maintaining state in variables, functional programming with F# models programs as a series of functions converting inputs to outputs. While this introduces complications for those used to imperative styles, the benefits of immutability mesh well with many current developments best practices.

For instance, if functions are pure, handling only immutable data and exhibiting no side effects, then testing is vastly simplified. It is very easy to test that a specific block of code always returns the same value given the same inputs, and by modeling code as a series of immutable functions, it becomes possible to gain a deep and highly precise set of guarantees that software will behave exactly as written.

Further, if execution flow is exclusively a matter of routing function inputs to outputs, then concurrency is vastly simplified. By shifting away from mutable state to immutable functions, the need for locks and semaphores is vastly reduced if not entirely eliminated, and multi-processor development is almost effortless in many cases.

Type inference is another powerful feature of many functional languages. It is often unnecessary to specify argument and return types, since any modern compiler can infer them automatically. F# brings this feature to most areas of the language, making F# feel less like a statically-typed language and more like Ruby or Python. F# also eliminates noise like braces, explicit returns, and other bits of ceremony that make languages feel cumbersome.

Functional programming with F# makes it possible to write concise, easily testable code that is simpler to parallelize and reason about. However, strict functional styles often require imperative developers to learn new ways of thinking that are not as intuitive. Fortunately, F# makes it possible to incrementally change habits over time. Thanks to its hybrid object-oriented and functional nature, and its clean interoperability with the .net platform, F# developers can gradually shift to a more functional mindset while still using the algorithms and libraries with which they are most familiar.

 

Related F# Resources:

F# Programming Essentials Training

The original article was posted by Michael Veksler on Quora

A very well known fact is that code is written once, but it is read many times. This means that a good developer, in any language, writes understandable code. Writing understandable code is not always easy, and takes practice. The difficult part, is that you read what you have just written and it makes perfect sense to you, but a year later you curse the idiot who wrote that code, without realizing it was you.

The best way to learn how to write readable code, is to collaborate with others. Other people will spot badly written code, faster than the author. There are plenty of open source projects, which you can start working on and learn from more experienced programmers.

Readability is a tricky thing, and involves several aspects:

  1. Never surprise the reader of your code, even if it will be you a year from now. For example, don’t call a function max() when sometimes it returns the minimum().
  2. Be consistent, and use the same conventions throughout your code. Not only the same naming conventions, and the same indentation, but also the same semantics. If, for example, most of your functions return a negative value for failure and a positive for success, then avoid writing functions that return false on failure.
  3. Write short functions, so that they fit your screen. I hate strict rules, since there are always exceptions, but from my experience you can almost always write functions short enough to fit your screen. Throughout my carrier I had only a few cases when writing short function was either impossible, or resulted in much worse code.
  4. Use descriptive names, unless this is one of those standard names, such as i or it in a loop. Don’t make the name too long, on one hand, but don’t make it cryptic on the other.
  5. Define function names by what they do, not by what they are used for or how they are implemented. If you name functions by what they do, then code will be much more readable, and much more reusable.
  6. Avoid global state as much as you can. Global variables, and sometimes attributes in an object, are difficult to reason about. It is difficult to understand why such global state changes, when it does, and requires a lot of debugging.
  7. As Donald Knuth wrote in one of his papers: “Early optimization is the root of all evil”. Meaning, write for readability first, optimize later.
  8. The opposite of the previous rule: if you have an alternative which has similar readability, but lower complexity, use it. Also, if you have a polynomial alternative to your exponential algorithm (when N > 10), you should use that.

Use standard library whenever it makes your code shorter; don’t implement everything yourself. External libraries are more problematic, and are both good and bad. With external libraries, such as boost, you can save a lot of work. You should really learn boost, with the added benefit that the c++ standard gets more and more form boost. The negative with boost is that it changes over time, and code that works today may break tomorrow. Also, if you try to combine a third-party library, which uses a specific version of boost, it may break with your current version of boost. This does not happen often, but it may.

Don’t blindly use C++ standard library without understanding what it does - learn it. You look at std::vector::push_back() documentation at it tells you that its complexity is O(1), amortized. What does that mean? How does it work? What are benefits and what are the costs? Same with std::map, and with std::unordered_map. Knowing the difference between these two maps, you’d know when to use each one of them.

Never call new or delete directly, use std::make_unique and [cost c++]std::make_shared[/code] instead. Try to implement usique_ptr, shared_ptr, weak_ptr yourself, in order to understand what they actually do. People do dumb things with these types, since they don’t understand what these pointers are.

Every time you look at a new class or function, in boost or in std, ask yourself “why is it done this way and not another?”. It will help you understand trade-offs in software development, and will help you use the right tool for your job. Don’t be afraid to peek into the source of boost and the std, and try to understand how it works. It will not be easy, at first, but you will learn a lot.

Know what complexity is, and how to calculate it. Avoid exponential and cubic complexity, unless you know your N is very low, and will always stay low.

Learn data-structures and algorithms, and know them. Many people think that it is simply a wasted time, since all data-structures are implemented in standard libraries, but this is not as simple as that. By understanding data-structures, you’d find it easier to pick the right library. Also, believe it or now, after 25 years since I learned data-structures, I still use this knowledge. Half a year ago I had to implemented a hash table, since I needed fast serialization capability which the available libraries did not provide. Now I am writing some sort of interval-btree, since using std::map, for the same purpose, turned up to be very very slow, and the performance bottleneck of my code.

Notice that you can’t just find interval-btree on Wikipedia, or stack-overflow. The closest thing you can find is Interval tree, but it has some performance drawbacks. So how can you implement an interval-btree, unless you know what a btree is and what an interval-tree is? I strongly suggest, again, that you learn and remember data-structures.

These are the most important things, which will make you a better programmer. The other things will follow.

Communication is one of the main objectives that an organization needs to have in place to stay efficient and productive. A breakdown in accurate and efficient communication between departments at any point in the organization can result in conflict or loss of business.  Sadly, the efficiency between different departments in an organization becomes most evident when communication breaks down. As an example, David Grossman reported in “The Cost of Poor Communications” that a survey of 400 companies with 100,000 employees each cited an average loss per company of $62.4 million per year because of inadequate communication to and between employees.

With the dawning of the big-data era and the global competition that Machine Learning algorithms has sparked, it’s more vital than ever for companies of all sizes to prioritize departmental communication mishaps. Perhaps, today, as a result of the many emerging markets, the most essential of these connections are between IT and the business units. CMO’s and CIO’s are becoming natural partners in the sense that CMO’s, in order to capture revenue opportunities, are expected to master not just the art of strategy and creativity but also the science of analytics. The CIO, on the other hand, is accountable for using technical groundwork to enable and accelerate revenue growth. Since business and technology people speak very different languages, there’s a need on both sides to start sharing the vocabulary or understanding of what is expected in order to avoid gridlock.

In the McKinsey article, Getting the CMO and CIO to work as partners, the author speaks to five prerequisite steps that the CMO and the CIO can take in order to be successful in their new roles.

--- Be clear on decision governance
Teams should define when decisions are needed, what must be decided, and who is responsible for making them.

Tech Life in California

Largely influenced by several immigrant populations California has experienced several technological, entertainment and economic booms over the years. As for technology, Silicon Valley, in the southern part of San Francisco is an integral part of the world?s innovators, high-tech businesses and a myriad of techie start-ups. It also accounts for 1/3rd of all venture capital investments.
Either you came in here a swimmer or you'd better be a really fast learner Suzanne Collins
other Learning Options
Software developers near Montebello 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 California that offer opportunities for Google for Business developers
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

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 California 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 Google for Business programming
  • Get your questions answered by easy to follow, organized Google for Business experts
  • Get up to speed with vital Google for Business 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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