Agile/Scrum Training Classes in Woodland, California
Learn Agile/Scrum in Woodland, 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 Agile/Scrum related training offerings in Woodland, California: Agile/Scrum Training
Agile/Scrum Training Catalog
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2 May, 2024 - 3 May, 2024 - Linux Fundaments GL120
15 July, 2024 - 19 July, 2024 - Object-Oriented Programming in C# Rev. 6.1
24 June, 2024 - 28 June, 2024 - VMware vSphere 8.0 Boot Camp
10 June, 2024 - 14 June, 2024 - RED HAT SATELLITE V6 (FOREMAN/KATELLO) ADMINISTRATION
24 June, 2024 - 27 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.
C# PROGRAMMING –MAIN DESIGN GOALS
C# is a popular programming language these days, and it was designed from inception to provide a simple, clean, general purpose programming language for those intending to work within the confines of Microsoft’s .NET framework. Since then, it has been approved as one of the standard languages by both ECMA and ISO, making C# programming an essential tool in every programmers’ kit.
Different languages have different uses and specialties, and C# was designed for programmers to be able to use it to create different components for use in software that would be deployed and distributed en masse, to live use environments. This means that designers had to really put an emphasis on making the actual source code extremely compatible and portable. Those already familiar with C or C++ should definitely notice this emphasis.
Another particular point of emphasis during design was focus on internationalization of the language; it was intended from inception to be available all over the world, and to see all sorts of different implementations based on variance in regional programming technique. The resultant use should help the language develop sophistication as it is refined throughout different versions.
Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied. For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.
In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.
Panelist, Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”
Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”
There has been and continues to be a plethora of observational studies by different researchers in the publishing industry focused on how e-books have affected hard-copy book sales. Evidence from these studies has indicated that there is a significant and monumental shift away from hard-copy books to e-books.[1]These findings precipitate fears that hard-copy books might become more expensive in the near future as they begin to be less available. This scenario could escalate to the point where only collectors of hard-copy books are willing to pay the high price for ownership.
The founder of Amazon, Jeff Bezos, made a statement in July 2010 that sales of digital books had significantly outstripped U.S. sales of hard-copy. He claimed that Amazon had sold 143 digital books for its e-reader, the Kindle, for every 100 hard-back books over the past three months. The pace of this change was unprecedented; Amazon said that in the four weeks of June 2010, the rate of sales had reached 180 e-books for every 100 hard-backs sold. Bezos said sales of the Kindle and e-books had reached a "tipping point", with five authors including Steig Larsson, the writer of Girl with a Dragon Tattoo, and Stephenie Meyer, who penned the Twilight series, each selling more than 500,000 digital books.[2] Earlier in July 2010, Hachette said that James Patterson had sold 1.1m e-books to date.
According to a report made by Publishers Weekly, for the first quarter of 2011, e-book sales were up 159.8%; netting sales of $233.1 million. Although adult hard-cover and mass market paperback hard-copies had continued to sell, posting gains in March, all the print segments had declined for the first quarter with the nine mass market houses that report sales. Their findings revealed a 23.4% sales decline, and that children’s paper-back publishers had also declined by 24.1%.[3] E-book sales easily out-distanced mass market paperback sales in the first quarter of 2011 with mass market sales of hard-copy books falling to $123.3 million compared to e-books’ $233.1 million in sales.
According to .net sales report by the March Association of American Publishers (AAP) which collected data and statistics from 1,189 publishers, the adult e-Book sales were $282.3 million in comparison to adult hard-cover book sales which counted $229.6 million during the first quarter of 2012. During the same period in 2011, eBooks revenues were $220.4 million.[4] These reports indicate a disconcerting diminishing demand for hard-copy books.
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 Agile/Scrum programming
- Get your questions answered by easy to follow, organized Agile/Scrum experts
- Get up to speed with vital Agile/Scrum 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.
