Data Blending and Joins in Alteryx


Data Blending and Joins in Alteryx
Duration: 1h 30m | .MP4 1280×720 30 fps(r) | AAC, 48000 Hz, 2ch | 283.21 MB
Genre: eLearning | Language: English​

Alteryx is a powerful tool to manipulate and analyze data. This course will introduce you to common functions in Alteryx that will help you combine data from multiple tables or sources for further summarization or aggregation.

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Data Blending and Joins in Alteryx


Data Architecture Mastery Think Like Senior Data Architect


Free Download Data Architecture Mastery Think Like Senior Data Architect
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 5.36 GB | Duration: 19h 0m
Master data architecture decisions, patterns, and trade-offs – from lakehouse to AI-ready systems
What you’ll learn

Master core data modeling paradigms using first-principles frameworks that turn business Requirements into defensible architectural decisions.
Build lakehouses, data mesh platforms, streaming pipelines, and serving layers with clear tradeoff reasoning across cloud architectures and open table formats.
Design AI-ready architectures for RAG, vector databases, and agentic AI, with data quality, FinOps cost models, and operational SLOs built in from day one.
Apply governance, security, and compliance by design; prevent costly anti-patterns; and produce a portfolio ADR demonstrating senior architect-level thinking.
Understand how team topology and Conway’s Law shape data platforms, and make organizational design decisions that prevent architecture from drifting into chaos.
Evaluate emerging paradigms and build migration-ready architectures that adapt to change without full rewrites – a critical skill for long-lived platforms.
Requirements
Some experience in data engineering, analytics engineering, or a related data platform role.
Comfortable reading and understanding technical concepts – you work with data systems regularly, even if not as a hands-on coder.
Basic familiarity with data pipeline and storage concepts – terms like ETL, data warehouse, or data lake should not be new to you.
No prior architecture experience needed – this course builds structured architectural thinking from the ground up.
Description
Most data engineers can build pipelines. Few can architect systems that survive scale, regulation, cost pressure, and the next paradigm shift. This course closes that gap.Data Architecture Mastery teaches you to think like a senior data architect – not by memorizing tools, but by building a repeatable decision framework you can apply to any stack, any workload, and any constraint.What you’ll learnecompose any business requirement into six architectural constraint dimensions and use a weighted scoring framework to make defensible technology decisionsEvaluate storage paradigms – data warehouse, data lake, lakehouse, data mesh, and data fabric – and choose the right one for your workloadNavigate modern data paradigms: evaluate lakehouse architecture, open table formats, real-time OLAP engines, columnar storage, and medallion architecture – and know when each is the right call versus a legacy warehouseArchitect pipeline patterns across batch ETL/ELT, streaming, CDC, Lambda, Kappa, and Zero ETLApply data modeling paradigms – Kimball star schema, Inmon 3NF, Data Vault 2.0, MDM, SCD and One Big Table – to the right use caseBuild AI-ready platforms with RAG pipelines, embedding architectures, feature stores, and agentic AI systemsDesign the serving layer: semantic layers, data contracts, materialized views, and reverse ETLModel total cost of ownership, apply hot/warm/cold storage tiering, and use FinOps practices to prevent runaway cloud spendDefine SLOs with error budgets, design for failure with chaos engineering, and build production-grade observability into your pipelinesImplement privacy by design, data classification, active metadata, policy-as-code, access control architectures, and GDPR/CCPA compliance patternsApply Strangler Fig, Blue-Green deployment, and Parallel Run patterns for zero-risk platform migrationsAlign architecture with team structure using Conway’s Law, and avoid the most costly anti-patterns seen in production systemsDocument every decision using the Architecture Decision Canvas – a portfolio artifact you keep and build on after the courseEvery module builds on a single framework. By the end you’ll have a completed Architecture Decision Canvas for a real workload from your own platform – something you can present to leadership, defend in review, and update as Requirements change.This course is for senior data engineers, data architects, technical leads and even data engineering managers who want to move from building to designing, from tool familiarity to architectural reasoning, and from opinions to decisions they can defend in any room.
Data engineers who know the tools but want to level up into architectural thinking and design decisions.,Analytics engineers and data leads looking to expand their scope from pipeline-level to platform-level responsibility.,Engineers transitioning into data architect or staff engineer roles who need a structured, repeatable decision framework.,Teams preparing their data platforms for AI and GenAI workloads who need a principled, future-ready architecture approach.,Senior Engineering Managers, Data Directors & Technical Leads responsible for platform strategy and investment decisions who wants to gain deep data architectural knowledge and evaluate proposals critically, not just contextually.
Homepage
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https://www.udemy.com/course/data-architecture-mastery-think-like-senior-data-architect/


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Data Analyst Complete Course Excel Sql & Python Projects


MP4 | Free Download Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 16.44 GB | Duration: 30h 44m
Learn data analysis from scratch using Excel dashboards, SQL queries, Python automation & real-world projects (2026)
What you’ll learn
Analyze data using Microsoft Excel with formulas, functions, charts, pivot tables, dashboards, and projects

Clean, organize, and validate real-world data using Excel best practices
Create Excel dashboards and reports used in business and analyst roles
Write SQL queries to retrieve, filter, group, and analyze data from databases
Use SQL functions and JOINs to work with multiple tables
Learn Python fundamentals required for data analysis
Work with CSV and JSON files using Python
Perform data analysis using Python Pandas
Visualize data using Python charts and plots
Understand when to use Excel, SQL, or Python in real data analyst workflows
Apply skills through practical projects and real datasets
Build a strong foundation for entry-level data analyst roles
Requirements
No prior programming or data analysis experience required
Basic computer usage knowledge is enough
Willingness to learn and practice step by step
Description
Become a Data Analyst with Practical Skills – Not Just TheoryThis Data Analyst Bootcamp is designed for beginners who want a clear, structured, and practical path to learning data analysis using Excel, SQL, and Python.Instead of learning tools separately, this course shows you how data analysts actually work in real companies – starting with Excel, moving to SQL, and then using Python for automation and advanced analysis.What You Will Learn:• Use Excel for data cleaning, analysis, dashboards, and reporting• Write SQL queries to retrieve and analyze data from databases• Use Python for data handling, automation, and analysis with Pandas• Work on practical projects and real datasets• Understand how Excel, SQL, and Python work together in real analyst roles• Build a strong foundation for Data Analyst jobs or internshipsHow This Course Is Structured:This course follows a beginner-friendly, job-oriented sequence:Excel for Data Analysis – basics to advanced dashboards, projects, and AI-assisted ExcelSQL for Data Analysis – querying, filtering, functions, and joinsPython Foundations & Projects – complete Python basics with projectsPython for Data Analysis – Pandas, data visualization, and analysis workflowsAdditional Skills – automation, extra Excel topics, and practice datasetsTo give you the best learning experience, technical lessons are created with the help of experienced professionals, while the overall learning path, guidance, and support are provided directly by the instructor.Who this course is for:• Beginners who want to start a career as a Data Analyst• Students and fresh graduates from any background• Working professionals looking to switch to data roles• Excel users who want to upgrade to SQL and Python• Anyone who prefers clear explanations and practical learningNo prior programming or data experience is required.Who This Course Is NOT For:• Advanced data scientists• People looking only for deep machine learning or AI theory• Database administrators or backend developersThis course focuses on practical data analysis foundations, not advanced specialization.Why This Course Is Different:• Clear learning path instead of scattered topics• Strong focus on Excel dashboards and projects• Practical SQL and Python usage (not certification theory)• Beginner-friendly explanations• Designed for non-native English speakersStart Learning with Confidence:If you want a structured, practical, and beginner-friendly Data Analyst course that focuses on real skills, this bootcamp is for you.Enroll now and start your Data Analyst journey step by step.Let’s get started and build real-world data skills step by step.Post your questions in the Q&A section and I’ll support you throughout the journey.
Beginners who want to start a career in Data Analysis,Students and fresh graduates from any background,Working professionals planning to switch to Data Analyst roles,Excel users who want to upgrade their skills with SQL and Python,Non-technical learners who prefer clear and step-by-step explanations,Anyone preparing for entry-level data analyst jobs or internships
Homepage
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https://www.udemy.com/course/data-analyst-complete-course-excel-sql-python-projects/


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Data Analysis with Pandas and Python


Data Analysis with Pandas and Python
Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: aac, 48000 Hz
Language: English | Size: 6.11 GB | Duration: 20h 37m​

Analyze data quickly and easily with Python’s powerful pandas library! All datasets included — beginners welcome!

What you’ll learn
Perform a multitude of data operations in Python’s popular "pandas" library including grouping, pivoting, joining and more!
Learn hundreds of methods and attributes across numerous pandas objects
Possess a strong understanding of manipulating 1D, 2D, and 3D data sets
Resolve common issues in broken or incomplete data sets

Requirements
Basic / intermediate experience with Microsoft Excel or another spreadsheet software (common functions, vlookups, Pivot Tables etc)
Basic experience with the Python programming language
Strong knowledge of data types (strings, integers, floating points, booleans) etc

Description
Student Testimonials:

The instructor knows the material, and has detailed explanation on every topic he discusses. Has clarity too, and warns students of potential pitfalls. He has a very logical explanation, and it is easy to follow him. I highly recommend this class, and would look into taking a new class from him. – Diana

This is excellent, and I cannot complement the instructor enough. Extremely clear, relevant, and high quality – with helpful practical tips and advice. Would recommend this to anyone wanting to learn pandas. Lessons are well constructed. I’m actually surprised at how well done this is. I don’t give many 5 stars, but this has earned it so far. – Michael

This course is very thorough, clear, and well thought out. This is the best Udemy course I have taken thus far. (This is my third course.) The instruction is excellent! – James

Welcome to the most comprehensive Pandas course available on Udemy! An excellent choice for both beginners and experts looking to expand their knowledge on one of the most popular Python libraries in the world!

Data Analysis with Pandas and Python offers 19+ hours of in-depth video tutorials on the most powerful data analysis toolkit available today. Lessons include:

installing

sorting

filtering

grouping

aggregating

de-duplicating

pivoting

munging

deleting

merging

visualizing

and more!

Why learn pandas?

If you’ve spent time in a spreadsheet software like Microsoft Excel, Apple Numbers, or Google Sheets and are eager to take your data analysis skills to the next level, this course is for you!

Data Analysis with Pandas and Python introduces you to the popular Pandas library built on top of the Python programming language.

Pandas is a powerhouse tool that allows you to do anything and everything with colossal data sets – analyzing, organizing, sorting, filtering, pivoting, aggregating, munging, cleaning, calculating, and more!

I call it "Excel on steroids"!

Over the course of more than 19 hours, I’ll take you step-by-step through Pandas, from installation to visualization! We’ll cover hundreds of different methods, attributes, features, and functionalities packed away inside this awesome library. We’ll dive into tons of different datasets, short and long, broken and pristine, to demonstrate the incredible versatility and efficiency of this package.

Data Analysis with Pandas and Python is bundled with dozens of datasets for you to use. Dive right in and follow along with my lessons to see how easy it is to get started with pandas!

Whether you’re a new data analyst or have spent years (cough too long cough) in Excel, Data Analysis with pandas and Python offers you an incredible introduction to one of the most powerful data toolkits available today!

Who this course is for:
Data analysts and business analysts
Excel users looking to learn a more powerful software for data analysis

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Data Analysis and Visualization with Microsoft Power BI 2020


Free Download Data Analysis and Visualization with Microsoft Power BI 2020
Last updated 11/2020
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 45m | Size: 915.82 MB
Analyze , Transform & Visualize Data with Microsoft Power BI Desktop with hands-on projects lab work

What you’ll learn
At the end of this course students will be able to analyze data from different data sources and create their own datasets
Importing data from CSV, Excel and other sources in Power BI
Data Analytics
Different Data Visualization techniques
Students will have the required knowledge to dive deeper into Power BI and find out more about its advanced features
Requirements
PC with Microsoft Windows
Basic understanding of Data Analysis and Data Visualization (but not mandatory)
Microsoft Power BI Desktop installed on your system
Description
This course teaches you how to do Data Analysis and Visualization in Microsoft Power BI Desktop.
You want to analyze data from single or multiple sources? You want to create your individual datasets based on these sources and transform your results into beautiful and easy-to-make visualizations? You also want to share your results with colleagues or collaborate on your projects? Finally, you want to be able to access your data from multiple devices? Then the Power BI tools are the tools to choose for you!
This is what you will learn
• Get to know the different tools of the Power BI universe and learn how to use them
• Understand Power BI Desktop and its components
• Learn how to use the Query Editor to connect Power BI to various source types, how to work on the Data Model, and understand the difference between those two steps
• How to work in the different views of the Data Model
• How to create calculated columns and measures
• How to create a report with different interactive visualization types
This course if for
• People who never worked with Power BI and who want to understand how to use these tools
• People who want to learn to analyze and to visualize the data in Microsoft Power BI
• People with no or less knowledge of Data Analysis and Visualization
• Students of Business operations
• Owners of any business who want to see the day-to-day position of their business
• Everyone who wants to be an expert in Data Analytics and Microsoft Power BI
We would be happy to welcome you to this course!
Who this course is for
Anyone having the need to learn Data Analysis and Data Visualization using Microsoft Power BI


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Data + AgenticAI Academy 2026


Free Download Data + AgenticAI Academy 2026
Last updated 4/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 11.95 GB | Duration: 13h 48m
Develop Critical Thinking, Data Skills, and AgenticAI for Future Careers

What you’ll learn
Interpret how industries, data platforms, and workflows connect to create real-world value beyond isolated tools or technologies.
Master critical thinking for data careers: SWOT, risk analysis, design thinking, problem-solving, and real-world business decision making.
Apply essential engineering practices: Git, DevOps, CI/CD, MLOps, Cloud platforms, ETL, Agile, and solution architecture for real-world projects.
Assess how automation, agents, and AI can augment decision-making and operational workflows in modern organisations.
Requirements
Curiosity, ambition, and a desire to build a long-term career in data, AI, or tech.
No programming experience is required, everything is explained from first principles, with optional depth for those who have prior exposure
Description
The Data + AgenticAI Academy is designed to take you from curiosity to capability in one of the most important domains shaping the future of work. We are living in a world where data is everywhere-but real value comes from knowing how to think about it, structure it, and ultimately turn it into intelligent action. This course is built specifically for early-career professionals, students, and career switchers who want to build critical, job-ready skills without needing a deeply technical background. You will learn how industries actually work, how data flows through modern systems, and how AI-especially agentic AI-is transforming decision-making and operations. Rather than focusing only on theory, this Academy bridges the gap between learning and doing, helping you understand not just what tools exist, but how and why they are used in real-world environments. By the end, you will have a clear model of data ecosystems, the confidence to engage with technical teams, and the foundational skills to step into roles across data, analytics, and AI-driven organisations. This is a structured pathway into future careers.Module overview:Industry Insider Secrets – Understand how industries operate, how value is created, and how to analyse markets and organisations.Critical Thinking Accelerators – Learn frameworks like SWOT, design thinking, and process mapping to improve decision-making and problem-solving.Data Literacy – Build a clear understanding of data structures, architectures, and how data behaves in real systems.ETL – Learn how data is collected, transformed, and moved across systems to make it usable and reliable.Engineering Essentials – Gain foundational knowledge of modern engineering concepts that underpin data platforms.Modern Methodologies – Explore agile, product thinking, and delivery approaches used in high-performing teams.AgenticAI – Understand how AI agents work, how they interact with data, and how they are shaping the future of intelligent systems.This course is for educational purposes only; while every effort has been made to ensure accuracy, you should verify details independently and seek professional advice before making decisions.No guarantees or liability are provided for outcomes, and all views are personal, vendor-neutral, and independent of any affiliated organisations.
This course is for college students, university students, graduates, early career, career changers, and anyone seeking career growth in data and AgenticAI.,Learners from a STEM backgroun (Science, Technology, Engineering, Mathematics) wanting a career in data and AgenticAI.,Designed for anyone in data or tech who wants more than just technical skills – perfect for those ready to build confidence, land jobs, and grow long-term careers.
Homepage
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https://www.udemy.com/course/data-agenticai-academy/


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Dan Koe – How To Turn Yourself Into A One-Person Business Download


Free Download Dan Koe – How To Turn Yourself Into A One-Person Business is a modern digital entrepreneurship training program focused on building a scalable solo business model in the creator economy. The course teaches how to combine personal branding, content creation, and digital product systems to generate income without relying on traditional employment or large teams.

With a strategic and systems-based approach, this program covers audience building, value-driven content, offer creation, and automation of income streams. It is ideal for creators, freelancers, and entrepreneurs who want to develop a sustainable one-person business by leveraging online platforms and personal expertise.

Here’s What You Get:
3 days. 6 hours of training. Learn the money mechanics to turn yourself into a business as fast as possible.
If you’re reading this, I’m assuming you’re like me a few years ago.
You see others online that have the same amount of knowledge and skill as you (why can’t I do that?)
You know you have value to offer, but aren’t sure how to turn that into an income source outside of your main job or schooling.
You’ve tried growing an audience before, but it all seemed to be based on luck and manipulative tactics. You couldn’t grow.
You’ve tried freelancing, agency work, digital products, or maybe even dropshipping, but couldn’t make any substantial amount from it.
Or, you started a personal brand, chose a niche, copied what works, and you either didn’t gain traction or hated how meaningless it felt.
Now the internet is being filled with AI-generated slop.
All you see are "idiots" getting the most attention.
You may think that the internet is broken or too saturated, but the demand for meaningful content and products are shooting through the roof.
You don’t need a large following

How To Turn Yourself Into A Business
This isn’t another "make money online" course promising you’ll quit your job in 30 days.
In fact, I’m not going to promise anything. There are too many absurd promises nowadays.
However, I am confident that you will come out of this with strategies you can try right now that directly result in making more money doing something meaningful.
I’ll give you the education, and if you implement it without quitting after the first try, you will be just fine.
This is a live 3-day intensive (September 4-6) where you’ll learn to turn your authentic interests into income streams while outsourcing the busy work to AI.

Exactly What You Get
If you can’t make the scheduled times, don’t worry.
All trainings are recorded and uploaded to a dashboard you have access to for life. That way you can refer back to them as you take action.
1) Dan Koe on how to turn your story, skills, or interests into a profitable product, because you can’t make money without a product (clearly).
2) JK Molina on how to use AI to turn average ideas into million-dollar opportunities that separate you from the sea of other entrepreneurs and creators.
JK Molina tore down his multi-million dollar agency with the goal of making $1M a year as one person working 4 hours a day or less, and he accomplished that. His "Big Idea" training is the core part of that.
AI Prompts Included
3) Dan Koe and Randy Hill on the "laziest" beginner method to start making money immediately, without a website, logo, or tons of time invested in building a product.
Randy Hill is a fitness creator with a few thousand followers, but recently started making $80K per month. Since his results are fresh in his mind, he will be able to share it with other beginners with small audiences.
4) Justin Welsh on the best monetization paths for beginner creators and entrepreneurs that will take you from $1,000 to $10,000 to $100,000 or higher.
Justin Welsh left his executive position to slow down. He has built a $10M one-person business solely with writing (no video for those who are camera shy).
5) Dan Koe how to turn AI into your personal marketer, copywriter, and business strategist, so you can save 1-3 years learning how to do them yourself.
AI Prompts Included
6) Dan Koe on how to make money without being a sleazy salesman. No big sales funnels, just talking about your interests to people who want to know more.
By the end of the 3 day training, you will have a clear path to replacing your current salary with your interests.
Of course, this is only information. It is only as valuable as you make it.

Sales Page
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https://stan.store/thedankoe/p/how-to-productize-yourself–paths-to-10k


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Cybersecurity Tools Bootcamp 2026 Siem, Edr, Soar+Devsecops


Free Download Cybersecurity Tools Bootcamp 2026 Siem, Edr, Soar+Devsecops
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.20 GB | Duration: 11h 56m
Master 70+ enterprise security tools: SIEM, EDR, SOAR, DevSecOps, cloud & forensics with Apex Digital case study
What you’ll learn

Master 70+ enterprise cybersecurity tools including SIEM, EDR, SOAR, and DevSecOps platforms
Build a complete enterprise security operations stack from detection through incident response
Gain hands-on experience with Splunk, CrowdStrike, Wazuh, TheHive, MISP, and dozens more tools
Follow a realistic Apex Digital case study applying tools to real-world security scenarios
Requirements
Basic IT and networking knowledge is helpful but not required. No prior cybersecurity experience needed – this course starts from fundamentals and builds up to advanced topics.
Description
"This course contains the use of artificial intelligence."Become the cybersecurity professional every company is looking for. This bootcamp is the most comprehensive hands-on tour of the 70+ tools that modern security teams actually use – from SIEMs and EDRs to SOAR, DevSecOps, cloud security, threat intelligence, and digital forensics.Across 132 focused video lessons and 12 sections, you will build a complete enterprise security stack alongside our fictional case-study company, Apex Digital, applying every tool to a realistic scenario so you understand not just how each tool works, but when and why to use it.What you will master:Network defense with pfSense, Snort, Suricata, Wireshark, Zeek and ModSecurityVulnerability management and pentesting with Nessus, OpenVAS, Metasploit, Burp Suite and NmapSIEM and detection engineering with Splunk, ELK, Wazuh, Security Onion and Sigma rulesEndpoint protection with CrowdStrike Falcon, Microsoft Defender, SentinelOne and YARAIdentity, Active Directory hardening, MFA, SSO, PAM and secret managementCloud and container security across AWS, Azure, GCP, Kubernetes, CSPM and CNAPPIncident response, SOAR automation (Shuffle, Cortex XSOAR, Tines), disk, memory and network forensicsThreat intelligence, MITRE ATT&CK, MISP, OpenCTI and purple teaming with Atomic Red Team and CalderaDevSecOps with SAST, DAST, SCA, secret scanning, container image security and policy as codeData security, DLP, encryption, PKI, email and database security, and GDPR complianceBusiness continuity, disaster recovery, and how to plan your cybersecurity careerWho is this course for? Aspiring SOC analysts, blue team engineers, IT professionals moving into security, and anyone who wants a practical, tool-driven foundation in modern cybersecurity. No prior security experience required – basic IT knowledge is enough.By the end of this course you will have the vocabulary, the hands-on exposure, and the architectural thinking of a working security engineer – ready to contribute on day one in any modern SOC or security team.
Aspiring SOC analysts, security engineers, and blue team professionals. IT staff and system administrators transitioning into cybersecurity. Students and career changers who want practical, hands-on experience with the tools used in modern security operations centers.
Homepage
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https://www.udemy.com/course/cybersecurity-tools-bootcamp-2026-siem-edr-soardevsecops/


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Cyber Threat Intel: Risk and Emulation


Cyber Threat Intel: Risk and Emulation
Duration: 1h 12m | .MP4 1920×1080 30 fps(r) | AAC, 48000 Hz, 2ch | 143.02 MB
Genre: eLearning | Language: English​

Cybercriminals can target the business in various ways. This course will teach you to accurately identify cyber risks to the business and emulate these threats.

More Info:
Cyber Threat Intel: Risk and Emulation


Cyber Security Soc Analyst Training – Siem (Splunk) – [2022]


Cyber Security Soc Analyst Training – Siem (Splunk) – [2022]
Last updated 5/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 57.67 GB | Duration: 87h 30m​

[ eLearninfosec ] SOC Analyst training – Interview Questions also included -Its hands on experience on splunk SIEM

What you’ll learn
Student will gain the knowledge of Networking, Cyber Security and SOC analyst role activities content with hands on practicals
Requirements
There are no course prerequisites. You should know how to use internet and computer
Description
Cyber Security SOC analyst training Splunk (SIEM) For those who are aspiring to certify themselves as well as enhance their knowledge and skills on becoming a SOC analyst. This course is specially designed for all level of interested candidates who wants get in to SOC.Work of a SOC analyst?A Security Operation Center Analyst is primarily responsible for all activities that occur within the SOC. Analysts in Security Operations work with Security Engineers and SOC Managers to give situational awareness via detection, containment, and remediation of IT threats. With the increment in cyber threats and hacks, businesses are becoming more vulnerable to threats. This has significantly enhanced the importance of a SOC Analyst. For those in cybersecurity, it can be a dynamic role. SOC Analysts cooperate with other team members to detect and respond to information security incidents, develop and follow security events such as alerts, and engage in security investigations.Furthermore, SOC Analysts analyze and react to undisclosed hardware and software vulnerabilities. They also examine reports on security issues and act as ‘security advisors’ for an organization.This course helps you to learn and implement those strategies and with training provided. This will in turn help you play a significant role in defending against cyber threats and keeping sensitive information secure.

Overview

Section 1: Course Introduction

Lecture 1 1. Cyber Security Analyst – Intro to Course Content

Section 2: Networking Concepts

Lecture 2 Introduction to organization Network

Lecture 3 Introduction to organization Network

Lecture 4 ISO Model – Application and Presentation Layer Basics

Lecture 5 ISO Model – Session, Transport, Network and DataLink Layer Basics

Lecture 6 ISO Model Recap AND Public/Private Address Range

Lecture 7 Introduction to web technology

Lecture 8 Understanding HTTP protocol Part 1

Lecture 9 Understanding HTTP Part 2 and Understanding Service Ports Part 1

Lecture 10 Understanding SMB, SMTP, Telnet, SSH, FTP, SMTP, MySql Services.

Lecture 11 Introduction to Windows – Types of Wiondows OS and Permissions

Lecture 12 Windows OS – Computer Management, Utilities

Lecture 13 Indept on Port Numbers – Part 1

Lecture 14 Indept on Port Numbers – Part 2

Section 3: Cyber Security Concepts

Lecture 15 Introduction to Security CIA Encryption and Hashing

Lecture 16 Defence InDeapth Approach

Lecture 17 Cyber Kill chain OR Phases of Attack.mp4

Lecture 18 Brute Force Attack and Types

Lecture 19 Phishing and Spoofing Attacks

Lecture 20 DNS Tunneling Attack

Lecture 21 Malware and its Types

Lecture 22 OWASP Top 10

Section 4: Understanding Splunk, SIEM and SOC Process

Lecture 23 Splunk installation

Lecture 24 Splunk Universal Farward Installation

Lecture 25 Introduction to Splunk

Lecture 26 SOC Process

Lecture 27 SOC Roles and Responsabilities

Lecture 28 SIEM Architecture

Section 5: Understanding Various Logs, Dashboard and Alert creations

Lecture 29 Uploading Demo Logs to Splunk and firewall Log analysis

Lecture 30 Understanding Firewall Logs

Lecture 31 Splunk Dashboard creation – Firewall Part 1

Lecture 32 Splunk Dashboard creation – Firewall Part 2

Lecture 33 IDS Log Analysis

Lecture 34 DNS Profiling Scenarios Part 1

Lecture 35 DNS Profiling Scenarios Part 2

Lecture 36 Understanding DNS Logs

Lecture 37 Understanding HTTP Logs Part 1

Lecture 38 Understanding HTTP Logs Part 2

Lecture 39 Understanding Windows Log

Lecture 40 Understanding Windows Event IDs

Lecture 41 Windows Sysmon Log Analysis

Lecture 42 Understanding Antivirus Logs

Section 6: Walkthrough SIEM usecases and Incident Handling Stages

Lecture 43 SIEM Use cases Part 1

Lecture 44 SIEM Use cases Part 2

Lecture 45 SIEM Use cases Part 3

Lecture 46 Malware outbreak Analysis

Lecture 47 Incident Handling stages

Section 7: Introduction to threat Hunting

Lecture 48 Threat Hunting – Scanning attack on Web Server

Lecture 49 hreat Hunting – Brute Force Attack

Lecture 50 Email Header Analysis

Section 8: Networking and Security Interview Questions

Lecture 51 what are networking devices?

Lecture 52 what is P address and IP address classification?

Lecture 53 What is NAT and PAT?

Lecture 54 Tell me few port numbers which you know?

Lecture 55 How a Firewall Works?

Lecture 56 How VPN works?

Lecture 57 What is Symmetric and Asymmetric Encryption?

Lecture 58 Explain CIA triad?

Lecture 59 What is the difference in between SSL and HTTPS?

Lecture 60 How do you stay up to date on Cyber Security news and latest attacks

Lecture 61 What is the difference between Virus and Warm?

Lecture 62 Explain SQL Injection Attack

Lecture 63 What is botnet?

Lecture 64 What is Brute Force Attack?

Lecture 65 SIEM related interview topics

Section 9: SIEM Interview Questions and Answers

Lecture 66 SIEM Dashboard and Use cases

Lecture 67 What are different event logs you analyze?

Section 10: SOC Process Interview Questions and Day to Day Activities

Lecture 68 What is Security Operation Center?

Lecture 69 What are various Security Devices used in your orrganization?

Lecture 70 How does a SOC Team manage or work in an Organization?

Lecture 71 What are the Roles and Responsibilities of SOC Engineer?

Lecture 72 What are the fields in Sample Incident Ticket – ServiceNow ?

Lecture 73 what are Service level Agreements for the SOC Incidents?

Lecture 74 What is False Positive Analysis? or what are various outcomes of Analysis?

Lecture 75 How many Logs sources are there in your organization?

Lecture 76 What are the steps in Incident Response Life Cycle

Lecture 77 Can you please explain what you will do after getting an alert? (Alert IR FLow)

Lecture 78 How will you manage work in shifts?

Lecture 79 How do you handle P1, P2, P3 and P4 Incidents?

Section 11: SIEM Alert Analysis Interview Questions

Lecture 80 How do you analyze if receive a Brute Force Attack Alert?

Lecture 81 what will you do if receive a Malware Attack Alert?

Lecture 82 How do you analyze Phishing email attack?

Lecture 83 How do you Analyze SQL Injection attack?

Lecture 84 How do you analyze DDOS Attack?

Lecture 85 How do you analyze if a suspicious IP detected in outbound traffic?

Section 12: Discussion on Real Time Activities

Lecture 86 Discussion on Real Time Activities

Section 13: Course wrapup

Lecture 87 Course Wrapup

Students who are interested in Cyber security

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