Google for Business Training Classes in Rochester, New York
Learn Google for Business in Rochester, NewYork 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 Rochester, New York: Google for Business Training
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
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- Crystal Reports Classes
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- Foundations of Web Design & Web Authoring Classes
- Git, Jira, Wicket, Gradle, Tableau Classes
- IBM Classes
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- JUnit, TDD, CPTC, Web Penetration Classes
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- Perl Programming Classes
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- Tcl, Awk, Bash, Shell Classes
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- XML Classes
- OpenShift Fundamentals
24 June, 2024 - 26 June, 2024 - ASP.NET Core MVC, Rev. 6.0
19 August, 2024 - 20 August, 2024 - RED HAT ENTERPRISE LINUX V7 DIFFERENCES
13 May, 2024 - 15 May, 2024 - Docker
22 July, 2024 - 24 July, 2024 - RED HAT ENTERPRISE LINUX AUTOMATION WITH ANSIBLE
3 June, 2024 - 6 June, 2024 - See our complete public course listing
Blog Entries publications that: entertain, make you think, offer insight
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.
Disruptive technologies such as hand-held devices, cloud computing and social media are rattling the foundations upon which traditional businesses are built. Enterprise customers have grown smarter at ensuring the latest technological trends work in their favor. Everyone is trying to zero in on their core competencies by employing commodity services to run their business.
Likewise, enterprise application vendors need to zero in on their core competencies and enhance more value to the businesses of their clientele by leveraging standards-based commodity services, such as IaaS and PaaS, provided by leaders in those segments (e.g. Amazon EC2, Google Cloud Platform etc.).
What else enterprises need to do is learn to adopt new and emerging technologies such as cloud, utility and social computing to build on them to penetrate new market avenues.
New small and medium-sized entrants into the market are constantly challenging enterprises given their ability to rapidly turnaround and address the requirements of the customers in a cost-effective manner. Additionally, these new advancements also affect how enterprises create, deploy, and manage solutions and applications. If you take the example of Force.com, for instance, you find that it’s a common war zone for enterprise application vendors to furnish SME markets with their applications, with the new entrants mostly having an edge.
The interpreted programming language Python has surged in popularity in recent years. Long beloved by system administrators and others who had good use for the way it made routine tasks easy to automate, it has gained traction in other sectors as well. In particular, it has become one of the most-used tools in the discipline of numerical computing and analysis. Being put to use for such heavy lifting has endowed the language with a great selection of powerful libraries and other tools that make it even more flexible. One upshot of this development has been that sophisticated business analysts have also come to see the language as a valuable tool for those own data analysis needs.
Greatly appreciated for its simplicity and elegance of syntax, Python makes an excellent first programming language for previously non-technical people. Many business analysts, in fact, have had success growing their skill sets in this way thanks to the language's tractability. Long beloved by specialized data scientists, the iPython interactive computing environment has also attracted great attention within the business analyst’s community. Its instant feedback and visualization options have made it easy for many analysts to become skilled Python programmers while doing valuable work along the way.
Using iPython and appropriate notebooks for it, for example, business analysts can easily make interactive use of such tools as cohort analysis and pivot tables. iPython makes it easy to benefit from real-time, interactive researches which produce immediately visible results, including charts and graphs suitable for use in other contexts. Through becoming familiar with this powerful interactive application, business analysts are also exposing themselves in a natural and productive way to the Python programming language itself.
Gaining proficiency with this language opens up further possibilities. While interactive analytic techniques are of great use to many business analysts, being able to create fully functioning, independent programs is of similar value. Becoming comfortable with Python allows analysts to tackle and plumb even larger data sets than would be possible through an interactive approach, as results can be allowed to accumulate over hours and days of processing time.
This ability can sometime allow business analysts to address the so-called "Big Data" questions that can otherwise seem the sole province of specialized data scientists. More important than this higher level of independence, perhaps, is the fact that this increased facility with data analysis and handling allows analysts to communicate more effectively with such stakeholders. Through learning a programming language which allows them to begin making independent inroads into such areas, business analysts gain a better perspective on these specialized domains, and this allows them to function as even more effective intermediaries.
Related:
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.
Tech Life in New York
Company Name | City | Industry | Secondary Industry |
---|---|---|---|
NYSE Euronext, Inc. | New York | Financial Services | Securities Agents and Brokers |
Anderson Instrument Company Inc. | Fultonville | Manufacturing | Tools, Hardware and Light Machinery |
News Corporation | New York | Media and Entertainment | Radio and Television Broadcasting |
Philip Morris International Inc | New York | Manufacturing | Manufacturing Other |
Loews Corporation | New York | Travel, Recreation and Leisure | Hotels, Motels and Lodging |
The Guardian Life Insurance Company of America | New York | Financial Services | Insurance and Risk Management |
Jarden Corporation | Rye | Manufacturing | Manufacturing Other |
Ralph Lauren Corporation | New York | Retail | Clothing and Shoes Stores |
Icahn Enterprises, LP | New York | Financial Services | Investment Banking and Venture Capital |
Viacom Inc. | New York | Media and Entertainment | Media and Entertainment Other |
Omnicom Group Inc. | New York | Business Services | Advertising, Marketing and PR |
Henry Schein, Inc. | Melville | Healthcare, Pharmaceuticals and Biotech | Medical Supplies and Equipment |
Pfizer Incorporated | New York | Healthcare, Pharmaceuticals and Biotech | Pharmaceuticals |
Eastman Kodak Company | Rochester | Computers and Electronics | Audio, Video and Photography |
Assurant Inc. | New York | Business Services | Data and Records Management |
PepsiCo, Inc. | Purchase | Manufacturing | Nonalcoholic Beverages |
Foot Locker, Inc. | New York | Retail | Department Stores |
Barnes and Noble, Inc. | New York | Retail | Sporting Goods, Hobby, Book, and Music Stores |
Alcoa | New York | Manufacturing | Metals Manufacturing |
The Estee Lauder Companies Inc. | New York | Healthcare, Pharmaceuticals and Biotech | Personal Health Care Products |
Avon Products, Inc. | New York | Healthcare, Pharmaceuticals and Biotech | Personal Health Care Products |
The Bank of New York Mellon Corporation | New York | Financial Services | Banks |
Marsh and McLennan Companies | New York | Financial Services | Insurance and Risk Management |
Corning Incorporated | Corning | Manufacturing | Concrete, Glass, and Building Materials |
CBS Corporation | New York | Media and Entertainment | Radio and Television Broadcasting |
Bristol Myers Squibb Company | New York | Healthcare, Pharmaceuticals and Biotech | Biotechnology |
Citigroup Incorporated | New York | Financial Services | Banks |
Goldman Sachs | New York | Financial Services | Personal Financial Planning and Private Banking |
American International Group (AIG) | New York | Financial Services | Insurance and Risk Management |
Interpublic Group of Companies, Inc. | New York | Business Services | Advertising, Marketing and PR |
BlackRock, Inc. | New York | Financial Services | Securities Agents and Brokers |
MetLife Inc. | New York | Financial Services | Insurance and Risk Management |
Consolidated Edison Company Of New York, Inc. | New York | Energy and Utilities | Gas and Electric Utilities |
Time Warner Cable | New York | Telecommunications | Cable Television Providers |
Morgan Stanley | New York | Financial Services | Investment Banking and Venture Capital |
American Express Company | New York | Financial Services | Credit Cards and Related Services |
International Business Machines Corporation | Armonk | Computers and Electronics | Computers, Parts and Repair |
TIAA-CREF | New York | Financial Services | Securities Agents and Brokers |
JPMorgan Chase and Co. | New York | Financial Services | Investment Banking and Venture Capital |
The McGraw-Hill Companies, Inc. | New York | Media and Entertainment | Newspapers, Books and Periodicals |
L-3 Communications Inc. | New York | Manufacturing | Aerospace and Defense |
Colgate-Palmolive Company | New York | Consumer Services | Personal Care |
New York Life Insurance Company | New York | Financial Services | Insurance and Risk Management |
Time Warner Inc. | New York | Media and Entertainment | Media and Entertainment Other |
Cablevision Systems Corp. | Bethpage | Media and Entertainment | Radio and Television Broadcasting |
CA Technologies, Inc. | Islandia | Software and Internet | Software |
Verizon Communications Inc. | New York | Telecommunications | Telephone Service Providers and Carriers |
Hess Corporation | New York | Energy and Utilities | Gasoline and Oil Refineries |
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 New York 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 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…