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IBM C2090-011 : IBM SPSS Statistics Level 1 v2 Exam

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Test Number : C2090-011
Test Name : IBM SPSS Statistics Level 1 v2
Vendor Name : IBM
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C2090-011 exam Format | C2090-011 Course Contents | C2090-011 Course Outline | C2090-011 exam Syllabus | C2090-011 exam Objectives

Exam Title : IBM Certified Specialist - SPSS Statistics Level 1 v2
Exam ID : C2090-011
Exam Duration : 90 mins
Questions in exam : 55
Passing Score : 67%
Official Training : IBM SPSS Statistics Essentials (V25)
Exam Center : Pearson VUE
Real Questions : IBM SPSS Statistics Level 1 Real Questions
VCE Practice Test : IBM C2090-011 Certification VCE Practice Test

Operations/Running IBM SPSS Statistics
- General use
- Operations
- Settings
- Syntax
- Variables 15%
Reading and Defining Data
- Datasets
- Reading data
- Variables 16%
Data Understanding/Descriptives
- Crosstabs
- Descriptive statistics
- Dispersion
- Procedure
- Frequencies
- Means procedure
- Statistics 9%
Data Management
- Adding cases
- Aggregation
- Duplicate cases
- SelectCases
- SplitFile 15%
Data Transformations
- Categorical variables
- Computing variables
- Counting values across variables
- Counting values across cases
- IfConditions
- Recoding
- Variables 16%
Output: Editing and Exploring
- Charts
- Exporting results
- Output
- Pivot Tables Editor
- ScaleData::Boxplots
- ScaleVariable charts
- Scatterplots
- TableLooks 7%
Basic Inferential Statistics
- Chi-square
- Correlations
- Regression
- Samples
- Statistics::Error
- T-Test
- Statistics 22%

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IBM is using mild, in its place of electricity, to create extremely-quick computing | C2090-011 PDF get and Latest Topics

To quench algorithms' reputedly limitless thirst for processing power, IBM researchers have unveiled a new approach that might mean massive changes for deep-getting to know functions: processors that operate computations thoroughly with light, rather than electrical energy.  

The researchers have created a photonic tensor core that, in keeping with the homes of light particles, is able to processing statistics at unheard of speeds, to convey AI purposes with extremely-low latency.  

besides the fact that children the device has simplest been tested at a small scale, the file means that as the processor develops, it might obtain 1000 trillion multiply-accumulate (MAC) operations per second and per square-millimeter – in response to the scientists, that is two to a few orders greater than "state-of-the-art AI processors" that rely on electrical alerts.  

SEE: Kubernetes security guide (free PDF) (TechRepublic)

IBM has been working on novel procedures to processing contraptions for a couple of years now. a part of the business's analysis has concentrated on developing in-reminiscence computing technologies, during which reminiscence and processing co-exist in some form. This avoids transferring data between the processor and a separate RAM unit, saving power and reducing latency. 

last 12 months, the business's researchers unveiled that they'd correctly developed an all-optical method to in-reminiscence processing: they built-in in-reminiscence computing on a photonic chip that used easy to perform computational tasks. As a part of the scan, the team Tested that a fundamental scalar multiplication could readily be conducted the use of the expertise. 

In a new blog post, IBM research staff member Abu Sebastian shared a new milestone that has now been completed using light-based mostly in-memory processors. Taking the technology to the next stage, the crew has developed a photonic tensor core, which is a sort of processing core that performs refined matrix math, and is principally relevant for deep-studying purposes. The gentle-based mostly tensor core was used to perform an operation known as convolution, it's effective to system visual information reminiscent of photographs. 

"Our experiments in 2019 have been more often than not about displaying the skills of the expertise. A scalar multiplication is terribly removed from any true-life software," Abu Sebastian, research team of workers member at IBM research, tells ZDNet. "however now, they now have a complete convolution processor, which you might possibly use as a part of a deep neural network. That convolution is a killer utility for optical processing. In that sense, it be quite a big step." 

the most giant potential that mild-based circuits have over their electronic counterparts is rarely-before-seen pace. Leveraging optical physics, the know-how developed by using IBM can run complex operations in parallel in a single core, the usage of distinctive optical wavelengths for each calculation. combined with in-reminiscence computing, IBM's scientists completed extremely-low latency that's yet to be matched through electrical circuits. For functions that require very low latency, for this reason, the velocity of photonic processing may make a huge difference. 

Sebastian puts forward the illustration of self-using automobiles, the place velocity of detection may have existence-saving implications. "when you are using on the highway at 100 miles-per-hour, and also you should observe anything inside a certain distance – there are some cases where the existing know-how does not help you try this. but the type of speed that you simply get with photonic-based methods is a couple of orders of magnitude stronger than electrical approaches." 

SEE: This potent new supercomputer will let scientists ask 'the correct questions'

With its capacity to operate several operations concurrently, the easy-based mostly processor developed with the aid of IBM also requires much much less compute density. according to Sebastian, this may well be a further key differentiator: there might be a point, says the scientist, the place loading vehicle trunks with rows of popular GPUs to guide ever-greater subtle AI systems won't cut it anymore.  

With most tremendous automobile companies now opening their personal AI analysis facilities, Sebastian sees self sustaining vehicles as a key application for light-primarily based processors. "there's a true need for low latency inference in the domain of autonomous driving, and no technology that may meet it as of now. this is a distinct chance." 

IBM's group, even though it has effectively designed and proven a magnificent core, nevertheless should prolong trials to be sure that the know-how may also be built-in at a equipment stage to be sure end-to-conclusion efficiency. "We deserve to do a lot greater there," says Sebastian; but in accordance with the scientist, work is already underway, and as analysis continues, more applications are handiest more likely to come up. trading electrical energy for gentle, in the field of computing, actually makes for a spot to observe. 

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