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Test Number : C2040-409
Test Name : IBM Notes and Domino 9.0 Social Edition Application Development A
Vendor Name : IBM
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C2040-409 test Format | C2040-409 Course Contents | C2040-409 Course Outline | C2040-409 test Syllabus | C2040-409 test Objectives


Exam Title : IBM Certified Application Developer - Notes and Domino 9.0
Exam ID : C2040-409
Exam Duration : 90 mins
Questions in test : 61
Passing Score : 44 / 61
Official Training : Web Resource
Exam Center : Pearson VUE
Real Questions : IBM Notes and Domino Social Edition Application Development A Real Questions
VCE VCE exam : IBM C2040-409 Certification VCE Practice Test

Application Architecture
- Control behavior based on client type and platform
- Create and use profile documents
- Develop navigation with design elements
- Understand database properties
- Import and utilize resource files
- Manage document locking
- Understand application and xsp.properties
- Understand Document IDs
- Understand parent and response documents
- Understand the Notes Indexing Facility
- Work with field size limits
- Work with local replicas
- Work with master templates or template inheritance

Application Debugging
- Implement error logging
- Debug an agent
- Use Agent Manager debug
- Use remote agent debugger
- Use server-side JavaScript debugger
- Utilize application logs

Application Design Elements
- Create a script library
- Create a Theme and Style Sheets
- Create an action
- Creating a web service (provider and consumer)
- Design a form and field
- Design a view and column
- Design calendar views
- Integrating subforms in forms
- Understand agent management
- Work with shared design elements
- Write an agent

Application Performance
- Optimize XPage performance
- Manage view complexity and size
- Understand the performance characteristics of design

IBM Domino Designer and Eclipse
- Integrate with source control systems
- Understand Eclipse preferences and customization
- Understand Eclipse perspectives
- Perform Eclipse Search
- Use working sets
- Work with Eclipse views

Integrating External Data
- Implement JDBC connections
- Develop LSXLC code
- Develop using Domino Data Service (REST API)
- Integrate with IBM Sametime Instant Messaging
- Understand data sources and data binding
- Work with Component Object Model (COM) and Object Linking and Embedding (OLE) objects

Security Features
- Create a role
- Design a secure web application SAML
- Understand ACL entries and privileges
- Understand document encryption
- Utilize Control Access Sections
- Understand IBM Domino server security
- Understand document security (Authors and Readers fields)
- Understand SSL implementation in IBM Domino
- Use agent security
- Integrate session token management within web applications
- Work with application privileges on the userBean



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IBM Application cheat sheet

laptop gaining knowledge of: A cheat sheet | C2040-409 PDF Questions and test Questions

a close up of a blackboard: Machine learning: A cheat sheet © TechRepublic computing device gaining knowledge of: A cheat sheet

artificial intelligence (AI), which has been round on account that the Nineteen Fifties, has viewed ebbs and flows in popularity over the last 60+ years. but nowadays, with the accurate explosion of huge data, excessive-powered parallel processing, and superior neural algorithms, they are seeing a renaissance in AI--and agencies from Amazon to facebook to Google are scrambling to take the lead. in response to AI skilled Roman Yampolskiy, 2016 was the year of "AI on steroids," and its explosive growth hasn't stopped.

while there are different kinds of AI, computer studying (ML) represents ultra-modern most generally valued mechanism for accomplishing intelligence. right here's what it ability.

SEE: Managing AI and ML in the business (ZDNet particular record) | obtain the document as a PDF (TechRepublic)

executive summary
  • what is computing device discovering? laptop discovering is a subfield of synthetic intelligence. as a substitute of relying on explicit programming, it is a gadget by which computer systems use a large set of information and practice algorithms to "teach" on--to train themselves--and make predictions.
  • When did desktop learning become customary? The term "artificial intelligence" turned into coined within the Fifties by using Alan Turing. desktop studying grew to become ordinary within the 1990s, and lower back to the general public eye when Google's DeepMind beat the area champion of Go in 2016. when you consider that then, ML applications and machine learning's recognition have best expanded.
  • Why does desktop researching count number? machine studying techniques are capable of immediately observe advantage and training from significant records sets to excel at facial consciousness, speech consciousness, object attention, translation, and a lot of different tasks.
  • Which industries use desktop getting to know? computing device getting to know touches industries spanning from govt to education to healthcare. It can also be used through companies concentrated on advertising, social media, consumer carrier, driverless cars, and many more. it's now greatly considered as a core device for determination making.
  • How do organizations use computer discovering? company applications of computing device learning are a large number of, however all boil all the way down to one class of use: Processing, sorting, and finding patterns in large quantities of facts that could be impractical for people to make sense of.
  • What are the protection and ethical issues about desktop learning? AI has already been trained to bypass superior antimalware utility, and it has the knowledge to be an enormous security risk in the future. ethical concerns additionally abound, especially in terms of the lack of jobs and the practicality of enabling machines to make ethical decisions like those that could be quintessential in self-riding automobiles.
  • What computer discovering tools can be found? corporations like IBM, Amazon, Microsoft, Google, and others present equipment for computer researching. There are free systems as well.
  • SEE: Managing AI and ML within the commercial enterprise 2020: Tech leaders raise project construction and implementation (TechRepublic top rate)

    what is computer learning?

    computer getting to know is a branch of AI. different tools for accomplishing AI consist of rule-primarily based engines, evolutionary algorithms, and Bayesian statistics. whereas many early AI classes, like IBM's Deep Blue, which defeated Garry Kasparov in chess in 1997, have been rule-primarily based and stylish on human programming, desktop getting to know is a device in which computer systems have the ability to train themselves, and set their personal suggestions. In 2016, Google's DeepMind beat the world champion in Go by using desktop gaining knowledge of--training itself on a large facts set of knowledgeable strikes.

    There are a number of types of computer getting to know:

  • In supervised gaining knowledge of, the "trainer" will present the laptop with definite guidelines that connect an enter (an object's function, like "clean," for instance) with an output (the thing itself, like a marble).
  • In unsupervised discovering, the computer is given inputs and is left on my own to discover patterns.
  • In reinforcement researching, a pc system receives input invariably (in the case of a driverless vehicle receiving enter concerning the street, as an example) and normally is improving.
  • a massive amount of information is required to train algorithms for machine gaining knowledge of. First, the "practising facts" need to be labeled (e.g., a GPS vicinity connected to a photo). Then it is "categorized." This occurs when elements of the thing in query are labeled and put into the system with a group of suggestions that lead to a prediction. for instance, "crimson" and "circular" are inputs into the equipment that ends up in the output: Apple. in a similar way, a discovering algorithm may well be left by myself to create its personal rules if you want to practice when it is equipped with a big set of the thing--like a gaggle of apples, and the desktop figures out that they have got homes like "round" and "red" in typical.

    SEE: what's machine learning? every thing you should understand (ZDNet)

    Many instances of machine studying contain "deep learning," a subset of ML that makes use of algorithms that are layered, and form a community to method counsel and attain predictions. What distinguishes deep gaining knowledge of is the undeniable fact that the equipment can be trained on its own, with out human practising.

    additional supplies

    When did desktop getting to know turn into conventional?

    computer discovering was time-honored in the Nineteen Nineties, and has seen a accurate resurgence. here are some timeline highlights.

  • 2011: Google mind became created, which changed into a deep neural community that could establish and categorize objects.
  • 2014: fb's DeepFace algorithm changed into brought. The algorithm could appreciate people from a collection of photos.
  • 2015: Amazon launched its desktop getting to know platform, and Microsoft provided a allotted desktop researching Toolkit.
  • 2016: Google's DeepMind program "AlphaGo" beat the area champion, Lee Sedol, at the complicated video game of Go.
  • 2017: Google introduced that its desktop studying equipment can admire objects in pictures and bear in mind speech superior than people.
  • 2018: Alphabet subsidiary Waymo launched the ML-powered self-riding experience hailing carrier in Phoenix, AZ.
  • 2020: desktop researching algorithms are introduced into play towards the COVID-19 pandemic, helping to pace vaccine research and Boost the ability to tune the virus' unfold.

  • further materials

    Why does computer gaining knowledge of matter?

    apart from the enormous energy laptop gaining knowledge of has to beat humans at video games like Jeopardy, chess, and Go, computer studying has many practical applications. desktop studying equipment are used to translate messages on facebook, spot faces from pictures, and find locations all over the world that have definite geographic points. IBM Watson is used to support docs make cancer treatment selections. Driverless vehicles use desktop learning to accumulate advice from the atmosphere. desktop researching is additionally central to fraud prevention. Unsupervised desktop gaining knowledge of, combined with human consultants, has been proven to be very correct in detecting cybersecurity threats, for example.

    SEE: All of TechRepublic's cheat sheets and sensible grownup's guides

    whereas there are many expertise advantages of AI, there are additionally considerations about its usage. Many be concerned that AI (like automation) will put human jobs at risk. And no matter if or now not AI replaces people at work, it's going to really shift the forms of jobs that are necessary. computing device studying's requirement for labeled data, for instance, has meant a major need for people to manually do the labeling.

    As computer getting to know and AI in the office have developed, many of its purposes have founded on helping worker's rather than replacing them outright. This was very true all the way through the COVID-19 pandemic, which forced many organizations to ship big portions of their team of workers home to work remotely, leading to AI bots and desktop gaining knowledge of supplementing people to cope with mundane initiatives.

    There are a number of institutions dedicated to exploring the influence of synthetic intelligence. here are a couple of (culled from their Twitter listing of AI insiders).

  • The way forward for existence Institute brings collectively one of the crucial premiere minds--from the co-founder of Skype to professors at Harvard and MIT--to discover one of the most large questions about their future with machines. This Cambridge-based mostly institute also has a stellar lineup on its scientific advisory board, from Nick Bostrom to Elon Musk to Morgan Freeman.
  • The future of Humanity Institute at Oxford is one of the premier sites for chopping-area tutorial analysis. The FHI Twitter feed is an attractive place for content material on the latest in AI, and the numerous retweets by means of the account are additionally beneficial in finding different Twitter users who're engaged on the latest in synthetic intelligence.
  • The computing device Intelligence analysis Institute at Berkeley is an excellent resource for the latest academic work in artificial intelligence. MIRI exists, based on Twitter, not simplest to examine AI, however additionally to "make certain that the creation of smarter-than-human intelligence has a favorable affect."
  • extra supplies

    Which industries use desktop researching?

    very nearly any organization that wants to capitalize on its records to benefit insights, enrich relationships with clients, increase sales, or be competitive at a selected project will depend on computer getting to know. It has purposes in executive, enterprise, training--very nearly anybody who desires to make predictions, and has a huge satisfactory facts set, can use computing device gaining knowledge of to achieve their dreams.

    SEE: Sensor'd enterprise: IoT, ML, and massive information (ZDNet particular document) | obtain the file as a PDF (TechRepublic)

    along with analytics, machine getting to know can also be used to supplement human worker's by using taking up mundane tasks and releasing them to do more meaningful, ingenious, and productive work. Like with analytics, and enterprise that has employees dealing with repetitive, high-volume initiatives can improvement from desktop getting to know.

    extra elements

    How do companies use desktop researching?

    2017 became a huge year for growth within the capabilities of computer learning, and 2018 set the stage for explosive increase that, by means of early 2020, found that 85% of organizations had been the use of some type of AI of their deployed purposes. 

    some of the things that could be conserving that boom back, Deloitte spoke of, is confusion--simply what is desktop learning in a position to doing for groups?

    There are numerous examples of how organizations are leveraging desktop gaining knowledge of, and all of it breaks down to the identical fundamental aspect: Processing massive amounts of statistics to attract conclusions much faster than a crew of facts scientists ever may.

    Some examples of enterprise uses of computing device getting to know include:

  • Alphabet-owned security company Chronicle is the usage of machine gaining knowledge of to determine cyberthreats and lower the hurt they may cause.
  • Airbus defense & area is the usage of ML-based photograph focus technology to reduce the error cost of cloud attention in satellite photos.
  • world Fishing Watch is combating overfishing by way of monitoring the GPS coordinates of fishing vessels, which has enabled them to monitor the total ocean directly.
  • insurance company AXA raised accident prediction accuracy by using seventy eight% through the use of machine gaining knowledge of to construct accurate driver risk profiles.
  • japanese meals safety enterprise Kewpie has computerized detection of defective potato cubes in order that workers will not have to spend hours staring at for them.
  • Yelp makes use of deep discovering to categorise pictures people take of agencies through certain tags.

  • MIT's OptiVax can advance and examine peptide vaccines for COVID-19 and different diseases in a very digital atmosphere with variables including geographic coverage, population information, and extra.

  • SEE: executive's e book to AI in company (free booklet) (TechRepublic)

    Any business that deals with huge statistics evaluation can use laptop discovering know-how to velocity up the procedure and put humans to better use, and the particulars can range significantly from industry to business.

    AI purposes do not come first--they are tools used to clear up business complications, and may be considered as such. discovering the suitable utility for computer getting to know expertise contains asking the appropriate questions, or being faced with a enormous wall of records that could be inconceivable for a human to procedure.

    further materials

    What are the safety and ethical concerns about desktop discovering?

    There are a few concerns about the use of computing device gaining knowledge of and AI, including the security of cloud-hosted statistics and the moral issues of self-driving vehicles.

    From a protection standpoint, there are at all times considerations about the theft of massive quantities of records, but protection fears go beyond how to lock down facts repositories.

    safety professionals are nearly universally concerned about the competencies of AI to pass antimalware software and different security measures, and that they're appropriate to be concerned: synthetic intelligence utility has been developed that may modify malware to bypass AI-powered antimalware structures.

    a number of tech leaders, like Elon Musk, Stephen Hawking, and bill Gates, have expressed concerns about how AI could be misused, and the significance of developing ethical AI. Evidenced via the disaster of Microsoft's racist chatbot, Tay, AI can go incorrect if left unmonitored.

    SEE: laptop getting to know as a service: Can privateness learn? (ZDNet)

    moral concerns abound in the computing device getting to know world as smartly; one example is a self-driving car adaptation of the trolley issue thought test. in short, when a self-using car is introduced with a call between killing its occupants or a pedestrian, which is the appropriate option to make? there's no clear reply with philosophical problems like this one--no rely how the desktop is programmed, it has to make a moral judgement about the price of human lives.

    Deep fake videos, which realistically replace one grownup's face and/or voice with someone else's based on pictures and different recordings, have the knowledge to upset elections, insert unwilling individuals into pornography, and otherwise insert people into situtations they don't seem to be k with. The a ways-accomplishing results of this desktop gaining knowledge of-powered tool may be devastating.

    along with whether giving researching machines the potential to make moral selections is relevant, or whether access to definite ML tools is socially dangerous, there are issues of the different major human can charge more likely to include laptop discovering: Job loss.

    If the AI revolution is basically the subsequent fundamental shift on the planet, there are lots of jobs in an effort to stop to exist, and it is rarely necessarily those you would think. while many low-knowledgeable jobs are actually at risk of being eliminated, so are jobs that require a high diploma of training however are in keeping with basic ideas like demo attention.

    Radiologists, pathologists, oncologists, and different identical professions are all according to finding and diagnosing irregularities, whatever that laptop getting to know is principally suited to do.

    there may be additionally the ethical situation of barrier to entry--while machine discovering software itself is never high priced, handiest the largest corporations on earth have the sizeable outlets of records fundamental to properly train getting to know machines to deliver official consequences.

    As time goes on, some consultants predict that it be going to become greater complicated for smaller organizations to make an have an effect on, making desktop gaining knowledge of essentially a game for the largest, wealthiest businesses.

    extra materials

    What machine discovering equipment can be found?

    there are many on-line elements about machine learning. To get a top level view of the way to create a computing device getting to know gadget, check out this series of YouTube movies via Google Developer. There are additionally classes on computing device getting to know from Coursera and a lot of different associations.

    And to integrate computer discovering into your organization, you can use components like Microsoft's Azure, Google Cloud computer gaining knowledge of, Amazon machine learning, IBM Watson, and free systems like Scikit.

    further materials

    Editor's note: this text become up-to-date through Brandon Vigliarolo.


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    References :


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    https://arfansaleemfan.blogspot.com/2020/09/c2040-409-ibm-notes-and-domino-90.html
    http://ge.tt/3ne4v483
    https://www.4shared.com/video/Ep1xTivSea/IBM-Notes-and-Domino-9-0-Socia.html
    https://sites.google.com/view/killexams-c2040-409-free-exam-
    https://ello.co/killexamz/post/4oodmiv0fgghw8qeejniqq
    http://killexams.decksrusct.com/blog/uncategorized/c2040-409-ibm-notes-and-domino-9-0-social-edition-application-development-a-practice-test-with-real-question-by-killexams-com/
    https://www.clipsharelive.com/video/4302/c2040-409-ibm-notes-and-domino-9-0-social-edition-application-development-a-2020-update-question-bank-by-killexams-com
    https://hubpages.com/education/C2040-409-IBM-Notes-and-Domino-90-Social-Edition-Application-Development-A-Updated-dumps-by-Killexamscom



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