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Exam Code: 300-430 Practice exam 2022 by Killexams.com team
300-430 Implementing Cisco Enterprise Wireless Networks (ENWLSI) 2022

300-430 ENWLSI
Certifications: CCNP Enterprise, Cisco Certified Specialist - Enterprise Wireless Implementation
Duration: 90 minutes

This exam tests your knowledge of wireless network implementation, including:
FlexConnect
QoS
Multicast
Advanced location services
Security for client connectivity
Monitoring
Device hardening

The Implementing Cisco Enterprise Wireless Networks v1.0 (ENWLSI 300-430) exam is a 90-minute exam associated with the CCNP Enterprise and Cisco Certified Specialist - Enterprise Wireless Implementation certifications. This exam certifies a candidate's knowledge of wireless network implementation including FlexConnect, QoS, Multicast, advanced location services, security for client connectivity, monitoring and device hardening. The course, Implementing Cisco Enterprise Wireless Networks, helps candidates to prepare for this exam.

15% 1.0 FlexConnect
1.1 Deploy FlexConnect components such as switching and operating modes
1.2 Deploy FlexConnect capabilities
1.2.a FlexConnect groups and roaming
1.2.b Split tunneling and fault tolerance
1.2.c VLAN-based central switching and Flex ACL
1.2.d Smart AP image upgrade
1.3 Implement Office Extend
10% 2.0 QoS on a Wireless Network
2.1 Implement QoS schemes based on requirements including wired to wireless mapping
2.2 Implement QoS for wireless clients
2.3 Implement AVC including Fastlane (only on WLC)
10% 3.0 Multicast
3.1 Implement multicast components
3.2 Describe how multicast can affect wireless networks
3.3 Implement multicast on a WLAN
3.4 Implement mDNS
3.5 Implement Multicast Direct
10% 4.0 Location Services
4.1 Deploy MSE and CMX on a wireless network
4.2 Implement location services
4.2.a client tracking
4.2.b RFID tags (tracking only)
4.2.c Interferers
4.2.d Rogue APs
4.2.e Clients
10% 5.0 Advanced Location Services
5.1 Implement CMX components
5.1.a Detect and locate
5.1.b Analytics
5.1.c Presence services
5.2 Implement location-aware guest services using custom portal and Facebook Wi-Fi
5.3 Troubleshoot location accuracy using Cisco Hyperlocation
5.4 Troubleshoot CMX high availability
5.5 Implement wIPS using MSE
20% 6.0 Security for Wireless Client Connectivity
6.1 Configure client profiling on WLC and ISE
6.2 Implement BYOD and guest
6.2.a CWA using ISE (including self-registration portal)
6.2.b LWA using ISE or WLC
6.2.c Native supplicant provisioning using ISE
6.2.d Certificate provisioning on the controller
6.3 Implement 802.1X and AAA on different wireless architectures and ISE
6.4 Implement Identity-Based Networking on different wireless architectures (VLANs, QoS, ACLs)
15% 7.0 Monitoring
7.1 Utilize reports on PI and Cisco DNA center
7.2 Manage alarms and rogues (APs and clients)
7.2.a WLC
7.2.b PI
7.2.c Cisco DNA center
7.3 Manage RF interferers
7.3.a WLC
7.3.b PI
7.3.c Cisco DNA center
7.4 Troubleshoot client connectivity
7.4.a WLC
7.4.b ISE
7.4.c PI
7.4.d Cisco DNA center
10% 8.0 Device Hardening
8.1 Implement device access controls (including RADIUS and TACACS+)
8.2 Implement access point authentication (including 802.1X)
8.3 Implement CPU ACLs on the controller

Implementing Cisco Enterprise Wireless Networks (ENWLSI) 2022
Cisco Implementing learner
Killexams : Cisco Implementing learner - BingNews https://killexams.com/pass4sure/exam-detail/300-430 Search results Killexams : Cisco Implementing learner - BingNews https://killexams.com/pass4sure/exam-detail/300-430 https://killexams.com/exam_list/Cisco Killexams : How Cisco Data Scientists Helped CommonLit Innovate Teacher Feedback for Better Learning

Published 10-12-22

Submitted by Cisco Systems, Inc.

students at a round table, each on a laptop. A large pull-down projection screen behind them with a presentation on it.

The Transformational Tech series highlights Cisco’s nonprofit grant recipients that use technology to help transform the lives of individuals and communities.

Student studying and math comprehension is in decline. The U.S. “Nations Scorecard,” based on long term scores, recorded by the National Association of Education Progress (NAEP) and analysis by the National Bureau of Economic Research (NEBR), shows the largest average score decline in studying since 1990, and the first ever score decline in mathematics. This decline comes from analysis of testing data from over two million students in 10,000 schools in 49 states.

More can and will be done to address the implications of widening achievement for all students, and in particular students from underserved districts. To stimulate an academic recovery, we need innovative classroom solutions like CommonLit to support teachers and their students in today’s classrooms.

For years, Cisco nonprofit grantee CommonLit has focused on their mission to help students learn how to be better readers and writers. They’ve been successful in their approach: by giving students online access to studying materials, assignments, and tests, and through giving teachers resources, like dashboards that show where kids may be struggling with certain skills.

“CommonLit offers programs that are fully interactive and have everything teachers and students need—much like a studying program in a box.” Agnes Malatinszky, Chief Operating Officer at CommonLit explains.

Their highly engaging Annotation Tool, launched in July 2019, enables teachers to deliver relevant and real-time feedback to students. But research shows that receiving timely feedback leads to better student outcomes. So, the team at CommonLit wanted to find ways to make their Annotation Tool more effective for teachers to use.

So two years ago, with support from the Cisco Foundation, CommonLit came to Cisco’s data scientists, who volunteer with AI for Good, to help them review Annotation Tool usage information and determine ways to optimize the Annotation Tool through machine learning (ML) to help teachers and students better connect.

Partnering up and giving back

At Cisco, we have a proven track record of supporting nonprofits through our strategic social impact grants along with a strong culture of giving back. Cisco’s AI for Good program brings these values together by connecting Cisco data science talent to nonprofits, like CommonLit, that do not have the resources to use AI/ML to meet their goals.

This CommonLit and AI for Good partnered project was led by data scientist Kirtee Yadav, who also served as cause champion–which means she led the project from start to finish to ensure the project’s success. Other members of the project included Technical Lead Sampann Nigam and Team members, William Bickelmann, Bob Lapcevic, Aakriti Saxena, Sree Yadavalli, and Tana Franko.

“This CommonLit project was a good opportunity for Cisco’s data scientists to help for a good cause by using their unique skills,” stated Kirtee Yadav, a customer experience product manager at Cisco. “I jumped on this opportunity because it offered me the chance to learn new skills while I make an impact on this nonprofit.”

Finding the gaps through data science

Multiple studies have shown that the more feedback that kids receive, and the faster they receive it after completing an assignment, the more they will interact and learn from content. Yet many teachers often don’t have the time to provide detailed personalized feedback.

CommonLit challenged AI for Good data scientists to find out how that issue can be improved or resolved. The first thing the AI for Good team did was look at how Cisco’s machine learning models could modify, streamline, or Excellerate the Annotation Tool so teachers could more efficiently deliver feedback to students. Through results from pulled data, they found that teachers could only provide feedback to an average of two percent of student’s comments.

“Based on our analysis of the [CommonLit] data,” Sampann Nigam, data science leader at Cisco and tech lead on the AI for Good team, pointed out, “we found that feedback from teachers pushes engagement up. So, we created an AI model to recommend feedback options to teachers.”

The data science-built solution

After months of research and hard work, The AI for Good team built a natural language processing (NLP) solution to help teachers with limited bandwidth deliver feedback to more students. Through NLP, the improved Annotation application will generate three suggested feedback phrases with the added option of freeform feedback.

“The feedback is built to look like teacher’s direct feedback, but instead it’s a tool that provides feedback options, which teachers can pick and send to students with just a click,” Kirtee reasoned. “In the end, AI for Good helped CommonLit Excellerate their student teacher feedback loop.”

Sampann described the technical process to us: The AI for Good team built the phrase prediction solution using the BERT (Bi-directional Encoder Representations from Transformers) model and free-form feedback prediction, using a T5 model. Data scientists trained (fine-tuned) the BERT model by using the provided data set of annotated texts and student notes as the feature set and the feedback phrases as labels.

“Besides generating a set of phrases as suggested feedback, we decided to provide freeform feedback,” Sampann said. “These models use transfer learning, a specialized machine learning process.”

Proof of success

Over one million teachers use CommonLit in more than 80,000 schools. By fall semester of 2019, just months after launch, over 603,000 students had used the Annotation Tool, creating 3,210,156 Annotations and 5,029,973 highlights. So it comes as no surprise that the Annotation Tool, with its newly improved natural language processing, has proven very useful within its first year – close to 2.5 million annotations were logged.

“An education technology tool like CommonLit could never replace a classroom teacher, but we can make their time more effective.” Agnes said, “The way we think about machine learning and natural language processing tools, like what’s been developed for the Annotation Tool, is to make the jobs of teachers as easy as possible. We can make their jobs easier. We can nudge them towards best practices.”

This data science focused collaboration included a team of ten AI for Good data science volunteers and over 200 hours of their time spent on research, analysis, and problem-solving to successfully build a natural language-informed Annotation Tool.

The AI for Good team is working with CommonLit on options for releasing their Feedback recommendation AI model as open source, so that the education community can benefit from it.

“Cisco has been a partner for us for a couple of years now. They have supported some of our most innovative work around the technology,” Agnes explained. “And working with the Cisco AI for Good team was a unique experience that moved our organization’s most cutting-edge work forward.”

Learn more about our partnership with CommonLit.

View original content here.

Wed, 12 Oct 2022 02:03:00 -0500 en text/html https://www.csrwire.com/press_releases/757056-how-cisco-data-scientists-helped-commonlit-innovate-teacher-feedback-better
Killexams : Smart Learning Systems Market Size, Growth, Share, 2022 Global Company Profiles, Opportunity Assessment and Industry Expansion Strategies 2026

The MarketWatch News Department was not involved in the creation of this content.

Oct 17, 2022 (The Expresswire) -- Global “Smart Learning Systems Market” (2022-2026) research report covers of opportunities, segmentation of the global Smart Learning Systems market based growth, size, share. The report establishes a solid foundation for the users who wish to enter into the global market in terms of drivers, restraints, developments, top trends, and landscape estimation. The report further offers a detailed overview of leading companies encompassing their successful industrial strategies, contribution, latest techniques in present and future contexts. It reports also covers monetary and exchange fluctuations, import-export trade, and global market status in a market pattern. It helps the reader understand the business strategies, new collaborations that players are highlights in the market. The report provides a significant microscopic look at the market.

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Market Overview:

The global Smart Learning Systems market size is projected to reach USD million by 2026, from USD million in 2021, at a CAGR of during 2022-2026. Smart Learning Systems market growth in the Asia Pacific is primarily driven by countries, such as China, Japan, India, and Singapore.

With industry-standard accuracy in analysis and high data integrity, the report makes a brilliant attempt to unveil key opportunities available in the global Smart Learning Systems Market Share to help players in achieving a strong market position. Buyers of the report can access Verified and reliable market forecasts, including those for the overall size of the global Smart Learning Systems market in terms of revenue.

The Smart Learning Systems market growing trend of rising demand for comfortable and innovative Smart Learning Systems solutions and the need for energy-efficient solutions will create a market opportunity for the Smart Learning Systems market.- Further, with the ongoing technological evolution, such as Smart Learning Systems systems increasing projects worldwide coupled with consumer preferences for better Smart Learning Systems is favoring the growth of the market.- Moreover, the rising concerns over global climate change have led to the implementation of various rules and regulations pertaining to energy efficiency.

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List of TOP KEY PLAYERS in Smart Learning Systems Market Report are -

● Adobe Systems Inc.
● Educomp Solutions
● NIIT Limited
● Scholastic Corporation
● Smart Technologies
● Three Rivers Systems
● Cisco Systems
● Intel Corporation
● Ellucian Company L.P.
● Saba Software
● Blackboard, Inc.
● McGraw-Hill
● Pearson PLC
● Desire2learn
● Samsung Electronics
● SumTotal Systems
● Tata Interactive System
● Promethean, Inc

Global Smart Learning Systems Scope and Market Size: -

Smart Learning Systems market analysis is segmented by players, region (country), by Type and by Application. Players, stakeholders, and other participants in the global Smart Learning Systems market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on revenue and forecast by Type and by Application for the Smart Learning Systems Market Forecast period 2015-2026.

The Smart Learning Systems Market is Segmented by Types:

● Hardware
● Software
● Services

The Smart Learning Systems Market is Segmented by Applications:

● Academic
● Corporate
● Others

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Geographically, this report is segmented into several key regions, with sales, revenue, market share and growth Rate of Smart Learning Systems in these regions, from 2021 to 2027, covering

● North America (United States, Canada and Mexico) ● Europe (Germany, UK, France, Italy, Russia and Turkey etc.) ● Asia-Pacific (China, Japan, Korea, India, Australia, Indonesia, Thailand, Philippines, Malaysia and Vietnam) ● South America (Brazil, Argentina, Columbia etc.) ● Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

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Outline: The team of experienced research analysts at Research Reports World has thoroughly evaluated the primary and secondary information related to the global Smart Learning Systems market. The organization offers a bunch of trending industry reports on the portal, of which the recently published report is the global Smart Learning Systems market report. The publishers of the Smart Learning Systems report particularly focused on the research-based services to offer crucial information for business executives and investors. Utilizing such pivotal knowledge can help to opt for precise business-related decisions.

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● Smart Learning Systems Market report provides comprehensive analysis of the market with the help of up-to-date market new opportunities, overview, outlook, challenges, trends, market dynamics, size and growth, competitive analysis, major competitors analysis. ● Report recognizes the key drivers of growth and challenges of the key industry players. Also, evaluates the future impact of the propellants and limits on the market. ● Uncovers potential demands in the Smart Learning Systems Market. ● Smart Learning Systems Market report provides in-depth analysis for changing competitive dynamics Provides information on the historical and current market size and the future potential of the market.

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Major Points from Table of Contents:

Detailed TOC of Global Smart Learning Systems Market Report 2021

1 Smart Learning Systems Market Overview

1.1 Smart Learning Systems Product Scope

1.2 Smart Learning Systems Segment by Type

1.3 Smart Learning Systems Segment by Application

1.4 Smart Learning Systems Market Estimates and Forecasts (2015-2026)

2 Smart Learning Systems Estimates and Forecasts by Region

2.1 Global Smart Learning Systems Market Size by Region: 2015 VS 2021 VS 2026

2.2 Global Smart Learning Systems Market Scenario by Region (2015-2021)

2.3 Global Market Estimates and Forecasts by Region (2022-2026)

2.4 Geographic Market Analysis: Market Facts and Figures

3 Global Smart Learning Systems Competition Landscape by Players

3.1 Global Top Smart Learning Systems Players by Sales (2015-2021)

3.2 Global Top Smart Learning Systems Players by Revenue (2015-2021)

3.3 Global Smart Learning Systems Market Share by Company Type (Tier 1, Tier 2 and Tier 3) and (based on the Revenue in Smart Learning Systems as of 2020)

3.4 Global Smart Learning Systems Average Price by Company (2015-2021)

3.5 Manufacturers Smart Learning Systems Manufacturing Sites, Area Served, Product Type

3.6 Manufacturers Mergers and Acquisitions, Expansion Plans

4 Global Smart Learning Systems Market Size by Type

4.1 Global Smart Learning Systems Historic Market Review by Type (2015-2021)

4.2 Global Market Estimates and Forecasts by Type (2022-2026)

4.2.3 Global Price Forecast by Type (2022-2026)

Get a sample Copy of the Smart Learning Systems Market Report 2022

5 Global Smart Learning Systems Market Size by Application

5.1 Global Smart Learning Systems Historic Market Review by Application (2015-2021)

5.2 Global Market Estimates and Forecasts by Application (2022-2026)

6 North America Smart Learning Systems Market Facts and Figures

6.1 North America Smart Learning Systems by Company

6.2 North America Smart Learning Systems Breakdown by Type

6.3 North America Smart Learning Systems Breakdown by Application

7 Europe Smart Learning Systems Market Facts and Figures

8 China Smart Learning Systems Market Facts and Figures

9 Japan Smart Learning Systems Market Facts and Figures

10 Southeast Asia Smart Learning Systems Market Facts and Figures

11 India Smart Learning Systems Market Facts and Figures

12 Company Profiles and Key Figures in Smart Learning Systems Business

13 Smart Learning Systems Manufacturing Cost Analysis

13.1 Smart Learning Systems Key Raw Materials Analysis

13.1.1 Key Raw Materials

13.1.2 Key Raw Materials Price Trend

13.1.3 Key Suppliers of Raw Materials

13.2 Proportion of Manufacturing Cost Structure

13.3 Manufacturing Process Analysis of Smart Learning Systems

13.4 Smart Learning Systems Industrial Chain Analysis

14 Marketing Channel, Distributors and Customers

14.1 Marketing Channel

14.2 Smart Learning Systems Distributors List

14.3 Smart Learning Systems Customers

15 Market Dynamics

15.1 Smart Learning Systems Market Trends

15.2 Smart Learning Systems Drivers

15.3 Smart Learning Systems Market Challenges

15.4 Smart Learning Systems Market Restraints

Continued…

Browse complete table of contents at -

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Killexams : The Microsoft-Cisco Teams collaboration could create an interoperability revolution No result found, try new keyword!That's why the news from Microsoft and Cisco at this week's Ignite event matters. Editor's note: Both Microsoft and Cisco are clients of the author. I’ve covered videoconferencing since the late ... Thu, 13 Oct 2022 17:13:00 -0500 en text/html https://www.computerworld.com/ Killexams : Cisco partners with Microsoft to add Teams to its meeting devices

Networking firm Cisco Systems Inc. will add Microsoft Corp.'s Teams messaging app to its meeting devices, the two firms said on Wednesday, offering users an alternative to its own Webex video conferencing app.

Ticker Security Last Change Change %
CSCO CISCO SYSTEMS INC. 41.30 +1.10 +2.74%
Ticker Security Last Change Change %
MSFT MICROSOFT CORP. 237.53 +8.97 +3.92%

Cisco's Jeetu Patel, head of Security & Collaboration, said the company aims to be the hardware platform for a wide range of conferencing software platforms.

"The way this market is evolving is very similar to the way that the movie entertainment market evolved," Patel said, with consumers having multiple subscriptions to streaming services like Netflix, Disney, HBO and Hulu.

Microsoft Teams app is seen on the smartphone placed on the keyboard in this illustration taken, July 26, 2021. REUTERS/Dado Ruvic/Illustration (REUTERS/Dado Ruvic/Illustration / Reuters Photos)

MELINDA GATES OPENS UP ON ‘UNBELIEVABLY PAINFUL’ DIVORCE

"There's going to be times that people want to jump on a Microsoft Teams call, they want to jump on a Zoom call, they want to jump on a Google call."

Asked whether the strategy could cannibalize market share for Cisco's Webex app, Patel said he believed the company will benefit if customers have a better experience using multiple platforms.

Webex, once a widely used conferencing platform, has lost out to several newcomers including Zoom Video Communications Inc (ZM.O), which was founded by an early Webex engineer and grabbed a large share of the market during the coronavirus pandemic.

The new Operating System Microsoft Windows 11 is available in France since October 5 , 2021 (Photo by Daniel Pier/NurPhoto via Getty Images) (Daniel Pier/NurPhoto / Getty Images)

Ilya Bukshteyn, vice president of Microsoft Teams Calling and Devices, told Reuters the Teams Room software already runs on several other hardware devices and will be available on Cisco devices from the first quarter of next year.

FILE PHOTO - The logo of Dow Jones Industrial Average stock market index listed company Cisco is seen in San Diego, California April 25, 2016. REUTERS/Mike Blake/File Photo (REUTERS/Mike Blake/File Photo / Reuters Photos)

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Microsoft made the announcement at its annual Ignite conference.

Patel conceded "many people have a misconception of Webex as their granddad's software" but said in the last two years Cisco has launched many new functions, including real-time translation and transcription of meetings, that would eventually allow a multi-language conversation through Webex's video platform.

Wed, 12 Oct 2022 03:03:00 -0500 en-US text/html https://www.foxbusiness.com/technology/cisco-partners-microsoft-add-teams-meeting-devices
Killexams : Cisco tightens its SD-WAN integration with Microsoft Azure

Cisco continues to build tighter SD-WAN integration with the leading cloud service providers to better tie together widely distributed resources.

This week Cisco and Microsoft extended their SD-WAN/Microsoft Azure integration to enable building single or multiple overlays on top of Microsoft’s backbone to interconnect enterprise sites worldwide, and to connect sites to workloads running inside Azure, similar to an arrangement Cisco has with Google Cloud.

With Microsoft, Cisco said its SD-WAN package will soon let Azure customers build automated site-to-site connectivity over Microsoft’s global network using the Cisco SD-WAN Cloud Hub and Azure Virtual WAN with its multi-region fabric. The features are part of a new version of the SD-WAN software due out in December.

Microsoft’s fabric can identify a site based on its geographic location and attach sites to regions based on geographic boundaries. This architecture supports dividing SD-WAN overlay networks into multiple regions, wrote Jean-Luc Valente, vice president, product management with Cisco’s Enterprise Routing and SD-WAN group in a blog about the enhancements:

“As enterprises’ digital transformation brings in more cloud and cloud-hosted applications, there’s an increasing need for more agile connection between globally distributed sites. Cisco is working to make the unused global backbone capacity in the public cloud available to enterprises to use for inter-site connectivity. With Cisco SD-WAN Cloud Hub, enterprises who have deployed Cisco SD-WAN fabric for their WAN infrastructure can now securely extend their fabric to the public cloud in a simple and automated way and consider utilizing this for their global site-to-site connectivity.”

Benefits of this architecture include on-demand connectivity among the SD-WAN overlay regions, the ability to apply consistent policies across regions, and the enablement of end-to-end encryption of data  between sites using Cisco SD-WAN, Valente stated.

Copyright © 2022 IDG Communications, Inc.

Thu, 06 Oct 2022 18:10:00 -0500 en text/html https://www.networkworld.com/article/3675356/cisco-tightens-its-sd-wan-integration-with-microsoft-azure.html
Killexams : New partnership brings Microsoft Teams to Cisco meeting room devices

Customers will now have the option to run Microsoft Teams by default on Cisco Room and Desk devices

REDMOND, Wash., and SAN JOSE, Calif. — Oct. 12, 2022 — Cisco and Microsoft Corp. Wednesday announced at Microsoft’s annual Ignite conference a new partnership that will provide customers with more choice. In the first half of 2023, Cisco and Microsoft will soon offer the ability to run Microsoft Teams natively on Cisco Room and Desk devices Certified for Microsoft Teams, with the option of Teams as the default experience. Cisco will become a partner in the Certified for Microsoft Teams program for the first time.

“Interoperability has always been at the forefront of our hybrid work strategy, understanding that customers want collaboration to happen on their terms — regardless of device or meeting platform,” said Jeetu Patel, EVP and GM, Security & Collaboration, Cisco. “Our partnership with Microsoft brings together two collaboration leaders to completely reimagine the hybrid work experience.”

“Our vision to make Teams the best collaboration experience for physical spaces is brought to life by our incredible ecosystem of hardware partners,” said Jeff Teper, president, collaborative apps and platforms at Microsoft. “By welcoming Cisco as our latest partner building devices Certified for Microsoft Teams, we are excited to bring leading collaboration hardware and software to market together for our joint customers.”

Initially, six of Cisco’s most popular meeting devices and three peripherals will be certified for Teams, with more to come. The first wave of devices, expected to be certified by early 2023, will include the Cisco Room Bar, the Cisco Board Pro 55-inch and 75-inch, and the Cisco Room Kit Pro for small, medium and large meeting room spaces, respectively. The Cisco Desk Pro and Cisco Room Navigator will follow. Customers will have the option to make Microsoft Teams Rooms the default experiences, and the devices will continue to support joining Webex meetings with all the features and functionality customers enjoy today. The first peripheral — the Cisco Desk Camera 4K — is an intelligent USB webcam and will be available by the end of October 2022, followed by two headphones with a Teams button by early 2023.

Microsoft Teams customers will enjoy the digital workplace where they connect and collaborate with teammates, partners and customers, combined with Cisco’s high-quality, reliable video technology with powerful camera intelligence and noise removal technologies that enable inclusive and collaborative meeting experiences. All certified devices will be manageable in the Teams Admin Center and the new Teams Rooms Pro Management Portal, as well as through the Cisco Control Hub device management.

About Cisco

Cisco (NASDAQ: CSCO) is the worldwide leader in technology that powers the Internet. Cisco inspires new possibilities by reimagining your applications, securing your data, transforming your infrastructure, and empowering your teams for a global and inclusive future. Discover more on The Newsroom and follow us on Twitter at @Cisco.

Cisco and the Cisco logo are trademarks or registered trademarks of Cisco and/or its affiliates in the U.S. and other countries. A listing of Cisco’s trademarks can be found at www.cisco.com/go/trademarks. Third-party trademarks mentioned are the property of their respective owners. The use of the word partner does not imply a partnership relationship between Cisco and any other company.

About Microsoft

Microsoft (Nasdaq “MSFT” @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more.

For more information, press only:

Microsoft Media Relations, WE Communications for Microsoft, (425) 638-7777, [email protected]

Cisco Media Relations, Melissa Chanslor, (408) 527-0792, [email protected]

Note to editors: For more information, news and perspectives from Microsoft, please visit the Microsoft News Center at http://news.microsoft.com. Web links, telephone numbers and titles were correct at time of publication but may have changed. For additional assistance, journalists and analysts may contact Microsoft’s Rapid Response Team or other appropriate contacts listed at https://news.microsoft.com/microsoft-public-relations-contacts.

Tue, 11 Oct 2022 12:00:00 -0500 en-US text/html https://news.microsoft.com/2022/10/12/new-partnership-brings-microsoft-teams-to-cisco-meeting-room-devices/
Killexams : How Cisco Data Scientists Helped CommonLit Innovate Teacher Feedback for Better Learning

NORTHAMPTON, MA / ACCESSWIRE / October 11, 2022 / Cisco Systems Inc.

Cisco Systems Inc., Tuesday, October 11, 2022, Press release picture

The Transformational Tech series highlights Cisco's nonprofit grant recipients that use technology to help transform the lives of individuals and communities.

Student studying and math comprehension is in decline. The U.S. "Nations Scorecard," based on long term scores, recorded by the National Association of Education Progress (NAEP) and analysis by the National Bureau of Economic Research (NEBR), shows the largest average score decline in studying since 1990, and the first ever score decline in mathematics. This decline comes from analysis of testing data from over two million students in 10,000 schools in 49 states.

More can and will be done to address the implications of widening achievement for all students, and in particular students from underserved districts. To stimulate an academic recovery, we need innovative classroom solutions like CommonLit to support teachers and their students in today's classrooms.

For years, Cisco nonprofit grantee CommonLit has focused on their mission to help students learn how to be better readers and writers. They've been successful in their approach: by giving students online access to studying materials, assignments, and tests, and through giving teachers resources, like dashboards that show where kids may be struggling with certain skills.

"CommonLit offers programs that are fully interactive and have everything teachers and students need-much like a studying program in a box." Agnes Malatinszky, Chief Operating Officer at CommonLit explains.

Their highly engaging Annotation Tool, launched in July 2019, enables teachers to deliver relevant and real-time feedback to students. But research shows that receiving timely feedback leads to better student outcomes. So, the team at CommonLit wanted to find ways to make their Annotation Tool more effective for teachers to use.

So two years ago, with support from the Cisco Foundation, CommonLit came to Cisco's data scientists, who volunteer with AI for Good, to help them review Annotation Tool usage information and determine ways to optimize the Annotation Tool through machine learning (ML) to help teachers and students better connect.

Partnering up and giving back

At Cisco, we have a proven track record of supporting nonprofits through our strategic social impact grants along with a strong culture of giving back. Cisco's AI for Good program brings these values together by connecting Cisco data science talent to nonprofits, like CommonLit, that do not have the resources to use AI/ML to meet their goals.

This CommonLit and AI for Good partnered project was led by data scientist Kirtee Yadav, who also served as cause champion-which means she led the project from start to finish to ensure the project's success. Other members of the project included Technical Lead Sampann Nigam and Team members, William Bickelmann, Bob Lapcevic, Aakriti Saxena, Sree Yadavalli, and Tana Franko.

"This CommonLit project was a good opportunity for Cisco's data scientists to help for a good cause by using their unique skills," stated Kirtee Yadav, a customer experience product manager at Cisco. "I jumped on this opportunity because it offered me the chance to learn new skills while I make an impact on this nonprofit."

Finding the gaps through data science

Multiple studies have shown that the more feedback that kids receive, and the faster they receive it after completing an assignment, the more they will interact and learn from content. Yet many teachers often don't have the time to provide detailed personalized feedback.

CommonLit challenged AI for Good data scientists to find out how that issue can be improved or resolved. The first thing the AI for Good team did was look at how Cisco's machine learning models could modify, streamline, or Excellerate the Annotation Tool so teachers could more efficiently deliver feedback to students. Through results from pulled data, they found that teachers could only provide feedback to an average of two percent of student's comments.

"Based on our analysis of the [CommonLit] data," Sampann Nigam, data science leader at Cisco and tech lead on the AI for Good team, pointed out, "we found that feedback from teachers pushes engagement up. So, we created an AI model to recommend feedback options to teachers."

The data science-built solution

After months of research and hard work, The AI for Good team built a natural language processing (NLP) solution to help teachers with limited bandwidth deliver feedback to more students. Through NLP, the improved Annotation application will generate three suggested feedback phrases with the added option of freeform feedback.

"The feedback is built to look like teacher's direct feedback, but instead it's a tool that provides feedback options, which teachers can pick and send to students with just a click," Kirtee reasoned. "In the end, AI for Good helped CommonLit Excellerate their student teacher feedback loop."

Sampann described the technical process to us: The AI for Good team built the phrase prediction solution using the BERT (Bi-directional Encoder Representations from Transformers) model and free-form feedback prediction, using a T5 model. Data scientists trained (fine-tuned) the BERT model by using the provided data set of annotated texts and student notes as the feature set and the feedback phrases as labels.

"Besides generating a set of phrases as suggested feedback, we decided to provide freeform feedback," Sampann said. "These models use transfer learning, a specialized machine learning process."

Proof of success

Over one million teachers use CommonLit in more than 80,000 schools. By fall semester of 2019, just months after launch, over 603,000 students had used the Annotation Tool, creating 3,210,156 Annotations and 5,029,973 highlights. So it comes as no surprise that the Annotation Tool, with its newly improved natural language processing, has proven very useful within its first year - close to 2.5 million annotations were logged.

"An education technology tool like CommonLit could never replace a classroom teacher, but we can make their time more effective." Agnes said, "The way we think about machine learning and natural language processing tools, like what's been developed for the Annotation Tool, is to make the jobs of teachers as easy as possible. We can make their jobs easier. We can nudge them towards best practices."

This data science focused collaboration included a team of ten AI for Good data science volunteers and over 200 hours of their time spent on research, analysis, and problem-solving to successfully build a natural language-informed Annotation Tool.

The AI for Good team is working with CommonLit on options for releasing their Feedback recommendation AI model as open source, so that the education community can benefit from it.

"Cisco has been a partner for us for a couple of years now. They have supported some of our most innovative work around the technology," Agnes explained. "And working with the Cisco AI for Good team was a unique experience that moved our organization's most cutting-edge work forward."

Learn more about our partnership with CommonLit.

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