UML Training in Montebello, California

Small actions compound: Reputation, career trajectory, and how others perceive you in the workplace can come down to a handful of things/moments that seem inconsequential/small at the time but compound. Random Thought: Redwood trees come from small seeds and time. With every action you're planting small seeds and these seeds can grow into something bigger (sometimes unimaginably bigger) over time. Don't let small basic mistakes sabotage your reputation because it only takes a few small snafus for people to lose confidence/trust in your ability to do more important tasks. Trust is a fragile thing and the sooner people can trust you the faster they'll give you more responsibility. Some Examples: Being on time (always) or early (better); spending an extra 10-15 minutes reviewing your work and catching basic mistakes before your boss does; structuring your work so it's easy for others to understand and leverage (good structure/footnotes/formatting); taking on unpleasant schleps/tasks (volunteer for them; don't complain; do it even when there's no apparent benefit to you)

Rising tide lifts all boats: Fact: You don't become CEO of a multi-billion dollar public company in your 30s based purely on ability/talent. Your career is a boat and it is at the mercy of tides. No matter how talented you are it's a lot harder to break out in a sluggish situation/hierarchy/economy than a go-go environment. Even if you're a superstar at Sluggish Co., your upside trajectory (more often than not) is fractional to what an average/below average employee achieves at Rocket Ship Co. There's a reason Eric Schmidt told Sheryl Sandberg to "Get on a Rocket Ship". I had colleagues accelerate their careers/income/title/responsibility simply because business demand was nose bleed high (go go economy) and they were at the right place at the right time to ride the wave. Contrast that to the 2008 bust where earnings/promotions/careers have been clamped down and people are thankful for having jobs let alone moving up. Yes talent still matters but I think people generally overweight individual talent and underweight economics when evaluating/explaining their career successes. Sheryl Sandberg Quote: When companies are growing quickly and they are having a lot of impact, careers take care of themselves. And when companies aren’t growing quickly or their missions don’t matter as much, that’s when stagnation and politics come in. If you’re offered a seat on a rocket ship, don’t ask what seat. Just get on.

Seek opportunities where the outcome is success or failure. Nothing in between! You don't become a star doing your job. You become a star making things happen. I was once told early in my career that you learn the most in 1) rapidly growing organizations or 2) failing organizations. I've been in both kinds of situations and wholeheartedly agree. Repeat. Get on a rocket ship. It'll either blow up or put you in orbit. Either way you'll learn a ton in a short amount of time. Put another way; seek jobs where you can get 5-10 years of work experience in 1-2 years.

Career Tracks & Meritocracies don't exist: Your career is not a linear, clearly defined trajectory. It will be messy and will move more like a step function.

You will probably have champions and detractors on day 1: One interesting byproduct of the recruiting & hiring process of most organizations is it can create champions & detractors before you even start the job. Some folks might not like how you were brought into the organization (they might have even protested your hiring) and gun for you at every turn while others will give you the benefit of the doubt (even when you don't deserve one) because they stuck their neck out to hire you. We're all susceptible to these biases and few people truly evaluate/treat folks on a blank slate.

You'll only be known for a few things. Make those labels count: People rely on labels as quick filters. Keep this in mind when you pick an industry/company/job role/school because it can serve as an anchor or elevator in the future. It's unfortunate but that's the way it is. You should always be aware of what your "labels" are.

Nurture & protect your network and your network will nurture & protect you: Pay it forward and help people. Your network will be one of the biggest drivers of your success.

The Impact Machine Learning is Having on Emerging and Existing Markets

[May, 10, 2017] |
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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.

Are 3d Printers the Next Bastion of Piracy?

[Aug, 09, 2013] |
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As someone who works in many facets of the music industry, I used to seethe with a mixture of anger and jealousy when I would hear people in more “traditional” goods-based industries argue in favor of music content-based piracy. They made all the classic talking points, like “I wouldn’t spend money on this artist normally, and maybe if I like it I’ll spend money on them when they come to town” (which never happened), or “artists are rich and I’m poor, they don’t need my money” (rarely the case), or the worst, “if it were fairly priced and worth paying for, I’d buy it” (not true). I always wondered if they’d have the same attitude if 63% of the things acquired by customers in their industries weren’t actually paid for, as was conservatively estimated as the case for the music industry in 2009 (other estimations put the figure of pirated music at 95%). Well, we may soon see the answer to curiosities like that. Though one can say with tentative confidence that music piracy is on the decline thanks to services like Spotify and Rdio, it could be looming on the horizon for the entire global, physical supply chain. Yes, I’m talking about 3d printers.

Before I get into the heart of this article, let me take a moment to make one thing clear: I think these machines are incredible. It’s damn near inspiring to think of even a few of their potentially world-changing applications: affordable, perfectly fit prosthetic limbs for wounded servicemen and women; the ability to create a piece of machinery on the spot instead of having to wait for a spare to arrive in the mail, or en route if your car or ship breaks down in a far away place; a company based out of Austin, TX even made a fully functioning firearm from a 3d printer a few months ago.

If these machines become as consumer-friendly and idiot-proof as possible (like computers), it’s possible that in a matter of decades (maybe less), a majority of U.S. households will have their own 3d printer. There’s also the possibility they could take the tech-hobbyist path, one that is much less appealing to the masses. Dale Dougherty of Makezine.com estimates there are currently around 100,000 “personal” 3d printers, or those not owned for business or educational purposes. I don’t think they’ll ever be as ubiquitous as computers, but there are plenty of mechanically inclined, crafty hobbyists out there who would love to play around with a 3d printer if it was affordable enough.

That being said, is there reason to worry about the economic implications of consumers making what they want, essentially for free, instead of paying someone else to produce it? Or will the printers instead be used for unique items more so than replicating and ripping off other companies’ merchandise in mass amounts? The number of people working in industries that would be affected by a development like this is far greater than the number of people who work in content-based industries, so any downturn would probably have a much larger economic implications. Certainly, those times are a ways off, but a little foresightedness never hurt anyone!

Can Python Predict Outcomes Based on Historical Data?

[Sep, 21, 2017] |
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Python programming language is general purpose open source programming language. One of its main features is flexibility and ease of use. Python has a variety of useful set of utilities and libraries for data processing and analytical tasks. Currently due to the rise in demand of big data processing python has grown in popularity because its features are easy to use which are core to the processing of huge chunks of information.

Guido Van Rossum, the pioneer of python, introduced python in the year 1980 and then implemented it in 1989. The intention behind the development of python was to make it open source language that can also be used for commercial projects. The fundamental principle of python is to write the code that is easy to use, highly readable and embrace writing fewer lines of code for achieving a particular task. One of the most popular standard libraries which have ready to use tools for performing a various work is Python Package Index. It was introduced in January 2016 and contains more than 72,000 packages for third-party software usage.

Python plays a critical role in linking data to customers. Recently python has found few entry barriers and many people have had access to have experienced the power of python in the past. So, what makes python the best language for big data analytics?

One of the reasons to choose python is that python ecosystem is very vibrant, the ratings at Redmonk are a proof of the strength python community. The Redmonk ranking is based on StackOverflow discussions and contribution made in Github to determine the popularity of programming language on the method used by users to ask questions about Python and the number of the open source projects contributions.

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 worldâ€™s innovators, high-tech businesses and a myriad of techie start-ups. It also accounts for 1/3rd of all venture capital investments.

Computer Science is no more about computers than astronomy is about telescopes. Edsger Dijkstra

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.

Perl Mongers- Thousand Oaks, CA · iOS Mobile UI Deconstruction Front @ San Francisco · Perl Mongers- Thousand Oaks, CA ·

Fortune 500 and 1000 companies in California that offer opportunities for UML 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

the hartmann software group advantage

why take UML Training with the hartmann software group?

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 UML programming
Get your questions answered by easy to follow, organized UML experts
Get up to speed with vital UML 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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UML Training Classes in Montebello, California

Learn UML 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 UML related training offerings in Montebello, California: UML Training

UML Training Catalog

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Microsoft Office Classes

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Tech Life in California

training details locations, tags and why hsg

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