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Published 3/2025 MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz Language: English | Size: 12.00 GB | Duration: 13h 13m​

Automate Everything: n8n, LLMs, OpenAI API, Deepseek, Ollama & RAG! Business & Private AI Agents; More than just ChatGPT

What you’ll learn
Fundamentals of Automation, AI Agents & LLMs (ChatGPT, Claude, Gemini, Deepseek, Llama, Mistral & more)
Introduction to automation & key tools (n8n, Make, Zapier, LangChain, LangGraph, Flowise)
Understanding and utilizing APIs for automation
OpenAI API: Pricing structure, compliant usage & project setup
Function calling with LLMs: Using calendars, emails, web search, webhooks, Airtable, Google Sheets & more
Everything about vector databases, embedding models & Retrieval-Augmented Generation (RAG)
n8n Basics & Automation Applications
Basics of n8n: Installation, importing, exporting & selling workflows
Automations with Airtable, Google Sheets & Google Cloud
Using simple JavaScript variables in automation
Expanding AI automation with LLMs: Email automation, sentiment analysis, databases
Integrating open-source LLMs (Deepseek R1, Llama, Mistral) into automation
Using external LLM APIs in n8n (Deepseek API, Groq API & more)
AI Agents & RAG Chatbots in Workflows
Integrating AI agents & RAG chatbots into workflows
Automated vector database updates with Google Drive
RAG chatbot with AI agent node, embeddings & retrieval techniques
AI-powered email agents for automated summaries & responses
Prompt engineering: Principles, best practices & avoiding errors
Hosting, Social Media & Advanced Automations
n8n self-hosting with Render & other options
Using AI agents in WhatsApp, Telegram & social media
Web scraping & automation with sub-workflows & webhooks
Debugging strategies for error-free n8n automation
Connecting Flowise AI agents with webhooks & Google Sheets
Extending n8n with Flowise & JavaScript custom tools
Business & Market Aspects of AI Automation
AI automation as a business: Selling automation & AI agents
Creating market-ready RAG bots for lead generation & website integration
Marketing strategies for successfully selling AI solutions
Optimizing RAG chatbots: Chunk size, overlap & data quality
LlamaIndex & LlamaParse for data preprocessing in Google Colab
Using Firecrawl for web data extraction in Markdown format
Security, privacy & ethical concerns: Jailbreaks, prompt injections & data poisoning
Copyright & data protection for AI-generated data
Legal frameworks: EU AI Act & more

Requirements
No prior knowledge required, everything is shown step by step.

Description
AI Automation is the Future!But how does it really work? And how can AI optimize business processes-on a whole new level, far beyond ChatGPT? The answer: AI Agents.This course guides you through both essential and advanced concepts in automation using AI automation, AI agents, LLMs, vector databases, Retrieval-Augmented Generation (RAG), and n8n. You’ll learn how to create powerful automations, build intelligent AI agents, and seamlessly integrate them into your workflows to enhance both business and personal projects.Additionally, you’ll receive 29 downloadable JSON workflows to accelerate your learning and implementation.What You’ll Learn in This Course:Fundamentals of Automation, AI Agents & LLMsDive into the world of AI automation:Introduction to automation, AI agents & essential tools (n8n, Make, Zapier, LangChain, LangGraph, Flowise).Understanding APIs and their role in automation.LLMs explained: ChatGPT, Claude, Gemini, Deepseek, Llama, Mistral & more.OpenAI API: Pricing structure, GDPR-compliant usage & project setup.Function calling with LLMs: How AI agents use tools like calendars, emails, web search, webhooks, Airtable, Google Sheets, and more.RAG (Retrieval-Augmented Generation): Vector databases & embeddings explained.n8n Basics: Installation & First WorkflowsMaster the fundamentals of n8n, the key to intelligent automation:Local installation with Node.js & using the web version without installation.Importing, exporting, and selling workflows.Setting up automations with Airtable, Google Sheets & Google Cloud.Using simple JavaScript variables in automation.Expanding AI Automation with LLMsBuild advanced AI-powered automations:Email automation with OpenAI API, Gmail, and Airtable.Real-time sentiment analysis & database storage.Integrating open-source LLMs (Deepseek R1, Llama, Mistral) into automation.Using any LLM API in n8n (Deepseek API, Groq API & more).Integrating AI Agents & RAG Chatbots into WorkflowsAutomate customer communication & data processing:RAG Agent: Automatically updating vector databases with Google Drive.RAG Chatbot using AI agent nodes, embeddings & retrieval techniques.AI-powered email agents for automated summaries & responses.Prompt Engineering for AI AgentsOptimize your prompts for better AI responsesrinciples & best practices for effective prompt engineering.Avoiding errors & precisely controlling AI outputs.Hosting, Social Media & Advanced AutomationsExpand your automations with self-hosting & real-time integrations:n8n self-hosting with Render & other options.Using AI agents in WhatsApp & Telegram.Social media automation with sub-workflows, webhooks & web scraping.Debugging & Optimizing API IntegrationsEnhance performance & error handling in n8n workflowsebugging strategies for error-free n8n automations.Connecting Flowise AI agents with webhooks & Google Sheets.Extending n8n with Flowise & JavaScript custom tools.Building a Business with AI Automation & AI AgentsLeverage your skills to create a profitable AI automation business:Selling automations & AI agents as services.Developing market-ready RAG bots for lead generation & website integration.Marketing strategies for successfully selling AI solutions.Optimizing RAG Chatbots: Data Quality & ChunkingImprove AI responses with optimized data strategies:Chunk size, overlap & data quality for better chatbot performance.Using Firecrawl for web data extraction in Markdown format.LlamaIndex & LlamaParse for data preprocessing in Google Colab.Security, Privacy & Ethical ConsiderationsProtect your AI agents & ensure GDPR compliance:Understanding & preventing jailbreaks, prompt injections & data poisoning.Ensuring copyright & data protection for AI-generated content.Key legal frameworks: EU AI Act & moreAdditionally, you’ll gain access to 29 ready-to-use JSON workflows, available for download to streamline your learning experience and accelerate implementation.Become an Expert in AI Agents & Automation!After this course, you will have a deep understanding of AI automation, n8n, LLMs & RAG and be able to develop, optimize, and deploy powerful AI agents for business applications.Sign up now and step into the future of AI automation.

Overview
Section 1: Introduction

Lecture 1 Welcome!

Lecture 2 Course Overview

Lecture 3 Important Tips for the Course

Lecture 4 Explanation of the Links that you need in the Course

Lecture 5 Important Links

Section 2: Basics – Automation, LLMs, Function Calling, Vector Databases & RAG Explained

Lecture 6 What to Expect in This Section

Lecture 7 What Are Automations, AI Automation, and AI Agents?

Lecture 8 What Is an API (Client and Server)

Lecture 9 Tools for Automation & AI Agents: n8n, Make, Zapier, LangChain, Flowise & More

Lecture 10 What are LLMs like ChatGPT, Claude, Gemini, Llama, Deepseek, Grok etc.

Lecture 11 OpenAI API Explained: Pricing, Project Setup, Management & Compliance

Lecture 12 Test Time Compute (TTS) Explained: Thinking Models like Deepseek R1 & OpenAI o3

Lecture 13 What is Function Calling in LLMs for AI Agents and AI Automations

Lecture 14 Vector Databases, Embedding Models & Retrieval-Augmented Generation (RAG)

Lecture 15 Key Takeaways

Section 3: n8n Basics – Installation, Interface & First Simple Workflows

Lecture 16 What This Section Covers

Lecture 17 Local Installation of n8n with Node.js & Interface Overview

Lecture 18 Managing Node Versions (Fixing Errors in n8n Installation)

Lecture 19 Updating n8n Locally via Node.js

Lecture 20 Testing n8n for Free Without Local Installation

Lecture 21 First Automation: Automatically Save Bookings from On Form Submit in Airtable

Lecture 22 Importing, Exporting, and Selling Workflows as JSON

Lecture 23 Automatically Backing Up Airtable Data Locally

Lecture 24 Connecting Google Sheets with n8n (Google Cloud Platform Console)

Lecture 25 Recap

Section 4: Expanding Automations with LLMs & AI

Lecture 26 Overview of This Section

Lecture 27 Email Automation for Customer Bookings with OpenAI (ChatGPT) Gmail & Airtable

Lecture 28 Sentiment Analysis with LLMs & Storing Data in Airtable: OpenAI API

Lecture 29 Using Open-Source LLMs with Ollama: Deepseek R1, Llama, Mistral & More

Lecture 30 Integrating Any LLM into n8n via APIs: Deepseek API, Groq, Gemini, Claude & More

Lecture 31 Recap of Automations with LLMs in n8n

Section 5: AI Agents & RAG Chatbots in Your Automations & Email Automation

Lecture 32 What to Expect in This Section

Lecture 33 RAG Agent (Part 1): Automatic Vector Database Updates with Google Drive

Lecture 34 RAG Chatbot (Part 2): AI Agent Node, Vector Database, Embeddings & More

Lecture 35 Email Agent with Sub-Workflows, Vector Database, Google Sheets & More

Lecture 36 The Fastest Way to Build an Email Agent!

Lecture 37 Automatically Summarizing All New Emails of the Day with LLMs at 7AM

Lecture 38 AI-Powered Email Automation: Filtering Messages & Auto-Replying

Lecture 39 Recap & Practical Task

Section 6: Prompt Engineering for AI Agents & AI Automations

Lecture 40 Prompt Engineering for AI Agents & AI Automations (Systemprompts)

Lecture 41 Key Principles of Prompt Engineering for AI Agents & Automations (Atricle)

Section 7: Hosting & Tool Integration: Telegram, WhatsApp, Calendar, Scraping & More

Lecture 42 Hosting n8n: Self-Hosting with Render & Other Options

Lecture 43 Integrating AI Agents & Automations into WhatsApp

Lecture 44 Code Snippet (Dynamic Expression) for WhatsApp as Download

Lecture 45 Using AI Agents & Sub-Workflows with Telegram Trigger Node

Lecture 46 Telegram Agent: Automating Emails, Calendars & More via Voice & Text

Lecture 47 Push the Boundaries: Big AI-Agent that can talk and automate everything

Lecture 48 More Practical Examples. Social Media Automation, Scraping, Crawling & More

Lecture 49 My BEST Tip for Building and Prompting AI-Agents

Lecture 50 Recap

Section 8: Debugging Workflows & Integrating Other Apps/APIs with HTTP Requests & Webhooks

Lecture 51 What to Expect: Debugging & Controlling n8n from Other Apps with Webhooks

Lecture 52 Finding Errors in n8n Workflows with This Automation (Debugging n8n)

Lecture 53 Flowise AI Agent & n8n Webhook: Integrate Sheets with JavaScript & HTTP request

Lecture 54 JavaScript Code for the Flowise Custom Tool as Download (fetch for HTTP-Request)

Lecture 55 One more example for Webhooks and HTTPS request

Lecture 56 Recap of Webhooks, HTTP Requests and Error Trigger Nodes

Section 9: Integrate Apps in Websites and Build a Business with AI Automation & AI Agents

Lecture 57 Overview of This Section: AI Automation as a Business

Lecture 58 What AI Automations & Agents Can Be Sold?

Lecture 59 Market-Ready RAG Bot for Lead Generation (n8n, Pinecone & Google Sheets)

Lecture 60 RAG Lead Bot as a Standalone App with a Published URL

Lecture 61 Integrating RAG Bots into Websites: HTML, WordPress & Custom CSS Branding

Lecture 62 Selling Automations & AI Agents: Marketing, Offers, Price, Sales & More

Lecture 63 Web Scraping with Software – Quickly Find Many Leads

Lecture 64 Summary & Additional Tips

Section 10: Optimizing RAG Chatbots – Data Quality, Chunk Size, Overlap, Embeddings & More

Lecture 65 Optimizing RAG Chatbots: Data Quality, Chunk Size, Overlap, Embeddings & More

Lecture 66 Scraping Webpages and Converting HTML & PDFs to Markdown for Better RAG

Lecture 67 Efficient RAG with LlamaIndex & LlamaParse: Data Preparation for PDFs & CSVs

Lecture 68 Chunk Size and Chunk Overlap for your Embeddings (Better RAG Application)

Lecture 69 Recap: Data Quality, Chunk Size, Overlap, Embeddings for betther RAG

Section 11: Problems, Security & Compliance – Copyright, Data Protection, GDPR & EU AI Act

Lecture 70 First Problems and what will we Learn in this Section?

Lecture 71 Jailbreaks: A Method to Hack LLMs and AI-Agents & Automations with Prompts

Lecture 72 Prompt Injections: Another Security Vulnerability of LLMs, Agents & Automations

Lecture 73 Data Poisoning and Backdoor Attacks

Lecture 74 Copyrights & Intellectual Property of Generated Data from AI Agents

Lecture 75 Privacy & Protection for your own and Client Data

Lecture 76 Censorship, Alignment & Bias in LLMs: Deepseek, ChatGPT, Claude, Gemini, Dolphin

Lecture 77 License of n8n: Can you sell AI agents, AI Automations or the Codebase from n8n?

Lecture 78 EU & US Compliance: GDPR (DSGVO), CCPA/CPRA & the EU AI Act

Lecture 79 Overview of the EU AI Act for ChatBots & AI Agents + CCPA/CPRA (Deep Research)

Lecture 80 DSGVO (GDPR) Compliance for Chatbots & AI Agents + CCPA/CPRA (Deep Research)

Lecture 81 Recap Important Points to Remember

Section 12: What’s Next?

Lecture 82 Recap, Thank You & Next Steps

For entrepreneurs who want to become more efficient, save money, or build an AI business.,For anyone eager to learn something new and gain deep insights into AI automation.,For individuals interested in AI and automation who want to build their own agents.,For developers and data scientists who want to stay on top of GenAI, automation, AI agents, and frameworks.,For anyone looking to automate tasks.

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Year of release : September 2025
Manufacturer : Packt Publishing via O’Reilly Learning
Manufacturer’s website : Code:Copy to clipboard

https://learning.oreilly.com/course/ai-python/9781806679652/

Author : Vivian Aranha
Duration : 57h 57m
Type of distributed material : Video lesson
Language : En + subtitles

Description:
In this 58-hour course, you will gain a comprehensive pathway in AI and Python development, covering programming, data science, machine learning, deep learning, NLP, computer vision, and reinforcement learning. Through hands-on exercises, mini-projects, and real-world deployments, you’ll build scalable AI systems while applying best practices in ethics and governance.
What I will be able to do after this course
Write Pythonic code and manage data using NumPy, Pandas, and Matplotlib
Design supervised, unsupervised, and ensemble machine learning algorithms
Construct deep learning models with TensorFlow, Keras, and PyTorch
Apply CNNs, RNNs, LSTMs, and Transformers to NLP and computer vision tasks
Generate data and solutions using GANs and reinforcement learning frameworks
Course Instructor(s)
Vivian Aranha is a technology professional with nearly two decades of AI expertise, specializing in machine learning, deep learning, and intelligent systems. He mentors aspiring AI developers and simplifies complex concepts into practical, hands-on learning.
Who is it for?
This course is designed for aspiring AI developers, data scientists, and software engineers seeking an end-to-end AI pathway. It is suitable for learners with basic programming knowledge aiming to master advanced AI techniques, deployment practices, and ethical AI principles.
Content
Chapter 01 Week 01 – Python Programming Basics for Artificial Intelligence
Chapter 02 Week 02 – Data Science Essentials for Artificial Intelligence
Chapter 03 Week 03 – Mathematics for Machine Learning and Artificial Intelligence
Chapter 04 Week 04 – Probability and Statistics for Machine Learning and AI
Chapter 05 Week 05 – Introduction to Machine Learning
Chapter 06 Week 06 – Feature Engineering and Model Evaluation
Chapter 07 Week 07 – Advanced Machine Learning Algorithms
Chapter 08 Week 08 – Model Tuning and Optimization
Chapter 09 Week 09 – Neural Networks and Deep Learning Fundamentals
Chapter 10 Week 10 – Convolutional Neural Networks (CNNs)
Chapter 11 Week 11 – Recurrent Neural Networks (RNNs) and Sequence Modeling
Chapter 12 Week 12 – Transformers and Attention Mechanisms
Chapter 13 Week 13 – Transfer Learning and Fine-Tuning
Chapter 14 Week 01 – Python Basics
Chapter 15 Week 02 – Intermediate Python
Chapter 16 Week 03 – Working with Data
Chapter 17 Week 04 – Object-Oriented Programming
Chapter 18 Week 05 – GUI Programming
Chapter 19 Week 06 – Web Development with Python
Chapter 20 Week 07 – Data Science Basics
Chapter 21 Days 50_60 – Intermediate Projects
Chapter 22 Days 61_70 – Advanced Intermediate Projects
Chapter 23 Days 71_80 – AI & Machine Learning Projects
Chapter 24 Machine Learning Algorithms and Implementation in Python
Example files : none
Video format : MP4
Video : AVC, 1920×1080, 16:9, 30,000 fps, 3,000 kbps (0.017 bit/pixel)
Аудио: AAC, 44.1 KHz, 2 channels, 128 kb/s, CBR

AI & Python Development Megaclass (2025) (13.88 GB)
UsersDrive Link(s)
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https://usersdrive.com/ykuvhv6rciay.html
https://usersdrive.com/scypp8y0wlh2.html
https://usersdrive.com/7xzclmxr3qy2.html
https://usersdrive.com/szkmb4l6pfbb.html
https://usersdrive.com/l10hrnmc6680.html

RapidGator Link(s)
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https://rapidgator.net/file/2f408bd65b59aee29d8562f973c518b6/AI..Python.Development.Megaclass.2025.part1.rar
https://rapidgator.net/file/7b84669383c38ce5d5b68ec634b57ab0/AI..Python.Development.Megaclass.2025.part2.rar
https://rapidgator.net/file/70d04a7d643d3a0b9122ebf0e876f83f/AI..Python.Development.Megaclass.2025.part3.rar
https://rapidgator.net/file/df344ac826c8b0f50cf22cdfbfe1dd85/AI..Python.Development.Megaclass.2025.part4.rar
https://rapidgator.net/file/af3175c6f39411ada7226b7024b0da26/AI..Python.Development.Megaclass.2025.part5.rar

Agile Transformation: Organizational Agility
Duration: 1h 6m | .MP4 1280×720 30 fps(r) | AAC, 48000 Hz, 2ch | 164.29 MB
Genre: eLearning | Language: English​

Getting your enterprise to be more Agile is a worthwhile challenge. This course will teach you how to adapt your organization to be more Agile.

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Agile Transformation: Organizational Agility

Agentic AI Human-Agent Collaboration Design Patterns
.MP4, AVC, 1280×720, 30 fps | English, AAC, 2 Ch | 1h 1m | 153 MB
Instructor: Thomas Erl​

As autonomous AI systems are becoming a greater part of business operations and work environments, it’s becoming increasingly important to understand how these systems need to be designed to collaborate with humans. Often, the more responsibility agentic AI systems are given, the more human involvement and oversight become necessary.

In this new course, LinkedIn Top Voice and best-selling author Thomas Erl explains the common roles that need to be established for humans and AI agents to successfully work together. This course basically explores a number of specialized implementations of the human-in-the-loop concept, whereby AI systems are designed specifically for both humans and AI agents to carry out different parts of an overall workflow. The design patterns covered range from foundational collaborative designs, to system architectures that involve intelligent escalation, dynamic task allocation, and cognitive transparency, as well as correction and safety controls.

Homepage

Agentic AI Human-Agent Collaboration Design Patterns
.MP4, AVC, 1280×720, 30 fps | English, AAC, 2 Ch | 1h 1m | 153 MB
Instructor: Thomas Erl​

As autonomous AI systems are becoming a greater part of business operations and work environments, it’s becoming ly important to understand how these systems need to be designed to collaborate with humans. Often, the more responsibility agentic AI systems are given, the more human involvement and oversight become necessary.

In this new course, LinkedIn Top Voice and best-selling author Thomas Erl explains the common roles that need to be established for humans and AI agents to successfully work together. This course basically explores a number of specialized implementations of the human-in-the-loop concept, whereby AI systems are designed specifically for both humans and AI agents to carry out different parts of an overall workflow. The design patterns covered range from foundational collaborative designs, to system architectures that involve intelligent escalation, dynamic task allocation, and cognitive transparency, as well as correction and safety controls.

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Year of issue : 8/2025
Manufacturer : Udemy
Manufacturer’s website : Code:Copy to clipboard

https://www.udemy.com/course/sql-advanced/

Автор: Database Masters Training | 300,000+ Students Worldwide, Code Star Academy
Duration : 13h 28m 51s
Type of distributed material : Video lesson
Language : En
Subtitles : En

Description:
Level Up Your Oracle SQL Knowledge From Intermediate to Advanced and Become an In-Demand Database SQL Expert in Oracle!
What you’ll learn
All Advanced SQL Topics Necessary to Become an Expert in SQL!

Learn How to Construct Advanced SQL Queries with Hundreds of Examples!

Write, Read & Analyze Advanced SQL Queries Easily!

Over 130+ Lectures, 13+ Hours of On-Demand High-Quality Content!

Learn Advanced SQL Functions in Oracle

Get a Better Job and Income!

Master at Analytical SQL Functions in Oracle

Learn How to Work with Regular Expressions
Requirements
Nothing more than a working computer (All PC, Mac, Linux, Users are All Welcome!)

Basic SQL Knowledge is Preferred

No Previous Programming Experience is required!

No Paid Tools are Required!
Description
Welcome to
Most Comprehensive

Well-Organized

Professionally Designed by SQL Experts
Advanced SQL course, not only in Udemy but also on the planet!
This Advanced SQL course is the "One", "Enough", and "Ultimate" course to make you an "SQL Expert!".
Here is the chance for you to Advance Your SQL Knowledge and Get Better Income From Your Job, like $200-300k per/year.
Get Oracle’s SQL Expert Certification.
Oracle has two Certification Exams for SQL;
The first one (SQL Fundamentals) covers the basic subjects (All of these subjects are covered in my first course.)
The second one (SQL Expert) covers more advanced subjects including the basic ones. (All the advanced subjects (and more) for this exam are covered in this course.)
All the subjects are explained in detail and exampled as many as I do with Oracle’s HR schema. You can check the subjects from Oracle’s related pages.
Now, you are looking at a course that will make you pass this exam.
You can ask any questions about this course from the discussion board.

Your questions will be answered as soon as possible.
You can check our website for further details.
What are you going to learn from this Advanced SQL course?
Introducing Database Objects

Data Dictionary Views

Creating, Using, and Managing Sequences

Creating, Using, and Analyzing Synonyms

Understanding and Using Indexes

Creating, Using, and Managing Views

Creating, Using, and Managing Materialized Views

Creating and Using Advanced Subqueries

Advanced-Data Manipulation

Controlling Schema Objects

Administering User Privileges and Roles

Hierarchical Queries (Tree Structure)

Writing Advanced SQL Scripts

Generating Dynamic SQL Scripts

Analytical SQL Functions

Regular Expressions

And much more beyond these like:
Supportive Course Materials

Quizzes

Bonus Lectures

Regular Course Updates

Lifetime Support from Authors

More?
Hundreds of Examples

Well-Organized Course Content by SQL Experts

In-Depth Subjects (All Subjects are Explained in All Detail)

Lifetime Author(s) Support
Who this course is for:
This SQL Course is meant for who already know SQL in basic level and want to improve it to Advance

This course is not for newbies. (Newbies can take our fundamental SQL courses by checking the Intructor Page)
Video format : MP4
Video : avc, 1280×720, 16:9, 30,000 fps, 831 kbps
Audio : aac lc sbr, 44.1 kHz, 62.8 kbps, 2 audio

Udemy – Advanced SQL The Ultimate Guide (2025) (8.2025) (3.59 GB)
UsersDrive Link(s)
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https://usersdrive.com/np2jlydbfu5k.html
https://usersdrive.com/ixnn7pfb6yk4.html

RapidGator Link(s)
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https://rapidgator.net/file/6aead325e484e7a3a0e715c677182b01/Udemy.-.Advanced.SQL..The.Ultimate.Guide.2025.8.2025.part1.rar
https://rapidgator.net/file/925259f2290d2c4e635053d7251c49ba/Udemy.-.Advanced.SQL..The.Ultimate.Guide.2025.8.2025.part2.rar

Advanced Practices in Application Security
.MP4, AVC, 1280×720, 30 fps | English, AAC, 2 Ch | 3h 55m | 625 MB
Instructor: Derek Fisher​

Software rules the world whether it runs a datacenter, a cloud workload, on an IoT device in a factory, or an application on a mobile device-software is inescapable. Traditionally, security approaches have "bolted on" security in the final stages of development. But these last-minute techniques are no longer sufficient in providing security against sophisticated cyber threats. Each year cyberattacks become more prevalent and more dangerous, and organizations face unprecedented pressure to embed security into their development processes rather than treating it like an afterthought. This course is designed to empower cybersecurity professionals, software developers, and DevSecOps teams to implement application security techniques that integrate into and throughout the entire software development lifecycle (SDLC).

Learning objectives

• Conduct automated and manual security testing.
• Debug and resolve critical vulnerabilities.
• Test software using penetration testing tools.
• Generate actionable security reports.

Homepage

Advanced Power BI: DAX Language, Formulas, and Calculations
Duration: 3h 3m | .MP4 1280×720, 30 fps(r) | AAC, 48000 Hz, 2ch | 552 MB
Genre: eLearning | Language: English​

View Helen’s LinkedIn NewsletterData visualization allows you to represent information digitally and graphically, to convey the results of data analysis. Microsoft Power BI is a suite of business analytics tools that help you gain insights from your data. The suite brings together familiar operations from well-known products-including Excel, Access, Power Query, and Power Pivot-to help you quickly move past the basics and on to comprehensive analysis. In this course, Helen Wall guides you through the advanced capabilities of the service. She shows how to work with calculations, effectively leverage the DAX language, create advanced queries, and use the M language to improve the querying process. Helen also demonstrates how to get data into Power BI using the Power Query editor and then model the loaded data using DAX columns, tables, and measures. To lend these concepts a real-world context, she shares how to create a financial model for loans.

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