For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai

In this webinar, you will gain an introduction to the concept of agentic language models (LMs) and their usage. You will learn about common limitations of LMs and agentic LM usage patterns, such as reflection, planning, tool usage, and iterative LM usage.

This online session will cover:
Overview of LMs
LM Usage and limitations
Retrieval Augmented Generation (RAG)
Tool usage
Agentic LMs
Agentic design patterns

About the speaker: Insop Song

Insop is a Principal Machine Learning Researcher at GitHub Next. Previously he worked at Microsoft, where he focused on leveraging machine learning and large language models to boost engineering productivity. His projects included fine-tuning open-source large language models with internal code and text, developing document assistance tools, and applying AI to various engineering tasks. He is currently a course developer as well as a course facilitator for Stanford Online’s professional AI program.


Chapters:
00:00 - Introduction
00:10 - Overview of the Talk
01:50 - Training Language Models
02:30 - Modeling Objectives
04:00 - Examples of Training Data Formatting
05:40 - Applications of Language Models
06:50 - Using API for Language Models
09:00 - Best Practices for Prompt Preparation
11:10 - Importance of Clear Instructions
13:40 - Reflection and Improvement Techniques
16:30 - Tool Usage and Function Calling
20:30 - Definition of Agentic Language Models
21:50 - Reasoning and Action in Agentic Models
24:00 - Example of a Customer Support AI Agent
29:20 - Summary of Applications
36:00 - Key Design Patterns in Agentic Models
44:00 - Summary of Agentic Language Model Usage
47:40 - Audience Q&A
50:00 - Addressing Ethical Considerations
54:50 - Getting Started with Language Models
57:00 - Resources for Staying Updated
58:20 - Closing Remarks

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Join us live as we explore the power of Azure DevOps, Microsoft’s end-to-end platform for modern software development and delivery. In this session, we’ll walk through the key features including Repos, Boards, Pipelines, and Artifacts, and show you how to set up a complete CI/CD workflow. Whether you’re new to DevOps or looking to streamline your deployment process, this live stream will provide practical guidance, real-time demos, and actionable insights to help you work smarter and deliver faster. Don’t miss this opportunity to level up your DevOps skills and get your questions answered live!

00:00:00 INTRODUCTION
00:01:35 What is Azure?
00:12:31 Azure Certifications
00:22:40 How To Create Azure Free Account?
00:28:17 Introduction to Azure Portal
00:42:15 DevOps Introduction (Scribe Video)
00:44:16 DevOps Stages
01:34:20 What is Git?
02:28:41 GitHub Basics
02:58:15 What is Jenkins?
03:59:45 What is Docker?
04:39:15 Azure Virtual Machine
05:00:56 Azure Active Directory
05:27:37 ARM Templates
05:55:51 What is Azure DevOps?
06:19:37 Azure Boards
06:34:17 Azure DevOps Pipeline
06:46:53 Azure DevOps Test Plans
07:12:25 Azure DevOps Artifacts
07:36:21 Introduction To Azure Kubernetes Service (AKS)
08:26:00 Microsoft Azure DevOps Solutions: AZ-400
08:32:57 AWS DevOps vs Azure DevOps
08:36:44 Azure DevOps Interview Questions and Answers
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📝Feel free to share your comments below.📝

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Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: +18885487823 (toll-free) for more information.

Official Music Video for "MAD WORLD" from the album III available here:
https://linktr.ee/thewinerydogs

The Winery Dogs are:
Richie Kotzen (guitar/vocals)
Billy Sheehan (bass/vocals)
Mike Portnoy (drums/vocals)

http://www.thewinerydogs.com
https://www.instagram.com/thewinerydogs/
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This Simplilearn video on How To Introduce Yourself In Interview will brief you on how you can craft a well-prepared self-introduction. Here, we will provide you with an outline of how to get going with a smart self-introduction that will help you grab your dream job. So, let's begin!

The topics covered in this video on How To Introduce Yourself In Interview are:
Introduction 00:00:00
What the Interviewer Wishes to See in Your Self-Introduction 00:00:51
Self-Introduction Outline 00:01:46
Tip 1: Start Your Introduction With a Greeting 00:01:58
Tip 2: Brief About Your Educational Background 00:02:21
Tip 3: Speak About Your Current Job 00:02:47
Tip 4: Hobbies and Passion 00:03:34
Tip 5: Closing Statement 00:03:50
Additional Self-Introduction Tips 00:04:31

Don't forget to participate in the contest at 03:26!

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Gain powerful digital leadership skills with the Post Graduate Digital Transformation Certification Program in collaboration with Purdue University. Also, master the most comprehensive framework for a successful business transformation with this Digital Transformation Course. This Digital Transformation Course will focus on the critical aspects of building a digital-ready business. You'll learn everything from understanding and leveraging the drivers of transformation to build a digital business strategy, to lead organizations, and help them navigate through the digital disruption.

Key Features:
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✅8X higher live interaction with 100+ hours of live online classes by industry experts
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Skills Covered:
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** Tableau Certification Training: https://www.edureka.co/tableau....-certification-train **
"Level of Detail" is a new syntax which, both, simplifies and extends Tableau’s calculation language by making it possible to address level of detail questions directly. In this Edureka tutorial, you’ll gain insights into how LOD Expressions work, along with a more in-depth look at the different types of LOD Expressions and their respective use cases.

01:18 Introduction to LOD
06:12 Include Calculation
06:46 Exclude Calculation
07:12 Fixed Calculation
08:21 Aggregation & LOD
11:14 Nesting in LOD
12:16 Data Sources Supported by LOD
12:26 How to Create LOD Expressions
17:00 Level of Detail vs Table Calculations
18:04 Limitations of LOD

Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

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Tableau playlist here: https://goo.gl/NTpehs
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How it Works?
This is a 5 Week Instructor-led Online Course, 25 hours of assignment and 20 hours of project work
We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate!

- - - - - - - - - - - - - - - - -

About the Course

Edureka's Tableau Certification training is designed to help you become a top Tableau Professional. During this course, our expert Tableau instructors will help you:
Understand the need for visualization
Make advance insightful visuals
Perform scripting
Create comprehensive dashboards
Connect with multiple sources
Integrate Tableau with R
- - - - - - - - - - - - - - - - - - -

Who should go for this course?

The following professionals can go for this course :
Data Scientists
Business Analysts
Statisticians and Analysts
Project Managers
- - - - - - - - - - - - - - - -

Why learn Tableau?

Tableau is a leader in Gartner's magic quadrant in BI & Data analytic field. Being used in various leading domains like Business Intelligence, Marketing, Big Data Hadoop, etc., Tableau is one skill set most professional wish to carry ahead in their career. As per Indeed.com, the mean salary of Tableau professional is $ 100,000.

Got a question on the topic? Please share it in the comment section below and our experts will answer it for you.

For Tableau Training and Certification, Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

🔥 Data Science Master Program: https://www.edureka.co/masters....-program/data-scient
This Machine Learning Algorithms Tutorial shall teach you what machine learning is, and the various ways in which you can use machine learning to solve a problem! Towards the end, you will learn how to prepare a data-set for model creation and validation and how you can create a model using any machine learning algorithm!

Check our complete Data Science playlist here: https://bit.ly/2KEEFdf
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How it Works?

1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. You will get Lifetime Access to the recordings in the LMS.
4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate!

- - - - - - - - - - - - - -

About the Course

Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities.

- - - - - - - - - - - - - -

Why Learn Data Science?

Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework.

After the completion of the Data Science course, you should be able to:
1. Gain insight into the 'Roles' played by a Data Scientist
2. Analyse Big Data using R, Hadoop and Machine Learning
3. Understand the Data Analysis Life Cycle
4. Work with different data formats like XML, CSV and SAS, SPSS, etc.
5. Learn tools and techniques for data transformation
6. Understand Data Mining techniques and their implementation
7. Analyse data using machine learning algorithms in R
8. Work with Hadoop Mappers and Reducers to analyze data
9. Implement various Machine Learning Algorithms in Apache Mahout
10. Gain insight into data visualization and optimization techniques
11. Explore the parallel processing feature in R

- - - - - - - - - - - - - -

Who should go for this course?

The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course:

1. Developers aspiring to be a 'Data Scientist'
2. Analytics Managers who are leading a team of analysts
3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics
4. Business Analysts who want to understand Machine Learning (ML) Techniques
5. Information Architects who want to gain expertise in Predictive Analytics
6. 'R' professionals who want to captivate and analyze Big Data
7. Hadoop Professionals who want to learn R and ML techniques
8. Analysts wanting to understand Data Science methodologies

For more information, Please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll free).

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Customer Reviews:

Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "

Learn how to design with Claude Code from Anthropic in real product workflows with Figma MCP.

I cover what Claude Code is, how designers can use it, and how to turn it into a serious productivity multiplier for UX exploration, documentation, prototyping, and shipping faster.

If you’re a UI, UX, or Product Designer looking to build better products, work smarter with AI, and stay competitive in a rapidly changing industry, this guide is for you.

🔗 KEY LINKS
📣 JOIN THE COMMUNITY: https://uicollective.co/
❎ Follow me on X: https://x.com/KirkMDesign

Why Join UI Collective Academy? Get access to premium courses, premium downloads, and so much more on the way (I am largely building this solo...trying to make design education available for all, support goes a long way!)

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🔗 VIDEOS TO WATCH
Build a Design System: https://youtu.be/opTANvl9G1g
Complex Design System Setup: https://youtu.be/L-tpK7Eeuow
AI & Design Systems: https://youtu.be/XfezMs8B-O8

🔗 MORE LINKS
Let us build or fix your design system: https://designsystemlabs.co/
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kirkland@uicollective.co

VIDEO LINKS & MORE:
Installation: https://code.claude.com/docs/en/overview#terminal
For installation: /plugin install figma@claude-plugins-official
MCP documentation: https://code.claude.com/docs/en/mcp
https://www.pencil.dev/

0:00 An Introduction
0:53 Introduction to Claude Code
3:23 Claude Code & Opus 4.6
4:26 Setting Up Claude Code
6:07 Connecting Figma MCP
7:35 Building a Figma Design with Claude Code
11:59 Claude Code Desktop App
13:32 Pencil App Demo
14:31 Building a Design with Claude Code & Pencil