1992 2022 720p 10bit WEBRip 6CH x265 HEVC-PSA

1992 (2022) 5.7 (3,782 Votes)
Runtime: 1h 37m

Genre: Action, Drama, Thriller

Cast: Tyrese Gibson, Ray Liotta, Scott Eastwood

Plot: A factory worker must protect his son during the 1992 L.A. uprising after the Rodney King verdict.


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http://www.imdb.com/title/tt4959750

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Rate: 6.3 from 487 Users
Genre: Action,Drama,Thriller
Runtime: 97
Language: English
Country: United States

1992 2022 720p 10bit WEBRip 6CH x265 HEVC-PSA
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Size: 0.66 GB
Video:
Format : HEVC
Bit rate : 765362
Width : 1280
Height : 536
Frame rate : 23.976
Audio:
Format : AAC
Bit rate : 210563
Channels : 6
Sampling rate : 48000
Compression mode : Lossy
Language : English


Rapidgator:
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Other Quality
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AI Integration in Test Automation for Writing and Debugging


Free Download AI Integration in Test Automation for Writing and Debugging
Published 4/2026
Created by Suleyman Yuksel
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 42 Lectures ( 6h 0m ) | Size: 4.3 GB

Design AI-friendly test automation, integrate AI, turn plain text scenarios into test automation, and analyze failures
What you’ll learn
✓ Design AI-friendly test automation frameworks using Java, TestNG/JUnit, and Maven
✓ Integrate OpenAI APIs into real-world test automation workflows
✓ Design and prepare effective prompts for AI-driven test automation
✓ Build a Spring MVC microservice that converts plain-text scenarios into automation code using AI
✓ Transform multi-scenario test plans into executable automation suites using an AI-powered service
✓ Generate clean, maintainable automated tests from natural-language scenarios
✓ Integrate AI safely into existing automation frameworks without breaking test reliability
✓ Connect AI to service logs, test execution output, and reports for intelligent analysis
✓ Use AI to analyze test failures, logs, and automation code to identify root causes
✓ Produce clear, human-readable bug Descriptions from raw logs and test results using AI
✓ Design controlled AI workflows that ensure deterministic and reliable test results
✓ Apply all techniques to enterprise-scale automation and microservice-based systems
Requirements
● Basic to intermediate Java knowledge
● Basic understanding of OOP concepts (classes, interfaces, inheritance)
● Basic xperience with Java-based test automation frameworks such as TestNG or JUnit
● Basic familiarity with Spring Boot or Spring MVC, but it is not required to follow the course.
Description
AI is changing how test automation is built-but using AI effectively requires more than copying scenarios into a chat window.
This course shows how to design and build real AI-powered automation systems, where plain-text test plans are transformed into executable automation suites, tests are run automatically, and failures are analyzed intelligently using test code, execution output, and service logs.
Rather than focusing on prompt-only workflows or demos, this course takes a system-level engineering approach. You will learn how to integrate AI into existing automation frameworks in a controlled, deterministic, and reliable way, without compromising test quality or trust in results.
You will build an AI-assisted automation pipeline using Java and Spring MVC, integrate AI APIs, and design automation that is intentionally structured to work well with AI. The course also tackles one of the biggest real-world challenges in automation: a failing test does not always mean a service bug. You will learn how to use AI to analyze test code, test execution output, and service logs together to reduce investigation time and produce clear, human-readable explanations of what actually went wrong.
This course is designed for engineers working with enterprise-scale systems, where automation must be maintainable, debuggable, and scalable. The focus is on architecture, design decisions, and practical implementation-not basic Java, beginner automation, or AI hype.
Who this course is for
■ SDETs, QA Automation Engineers, and Software Developers who want to integrate AI into existing test automation frameworks
■ Engineers who want to transform multi-scenario test plans into executable automation suites using an AI-powered service
■ Professionals looking to adopt AI safely and in a controlled way without compromising test reliability or determinism
■ Engineers who spend significant time investigating failed tests and want to use AI to distinguish test issues from real service defects
■ Teams that want to reduce debugging time by using AI to analyze test code, execution output, and service logs together and produce clear, user-friendly failure explanations
Homepage
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https://www.udemy.com/course/ai-integration-in-test-automation-for-writing-and-debugging


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AI Income Blueprint 2026


Free Download AI Income Blueprint 2026
Published 3/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 52m | Size: 3.2 GB
From Beginner to Paid: A Complete Guide to Earning with AI

What you’ll learn
Learn how to use AI tools like ChatGPT, image, and video generators to create real freelance services from scratch
Build and package AI-powered services such as content writing, design, and video creation that clients will pay for
Find clients on platforms like Upwork and Fiverr and write proposals that get accepted even as a beginner
Follow a step-by-step roadmap to go from beginner to your first real results with AI, including practical action plans and workflows
Requirements
No prior experience needed. This course is beginner-friendly and covers everything step by step. You only need a computer, internet connection, and willingness to take action
Description
This course contains the use of artificial intelligence.
AI Income Blueprint 2026
From Beginner to Paid: A Complete Guide to Earning with AI
AI Income Blueprint 2026 is a practical, beginner-friendly course designed to help you turn AI tools into real income, even if you have no prior experience. This program provides a clear, step-by-step roadmap that takes you from learning the basics of AI to landing your first client and growing your results.
Throughout the course, you will learn how to use powerful AI tools for writing, design, video, and automation, and how to turn those skills into services that businesses are actively looking for. You will also discover how to create compelling offers, set your pricing, and position yourself effectively in a competitive market.
The course is structured into six sections covering everything from foundational knowledge to execution and long-term growth. You will follow a proven system that guides you through choosing a service, building a simple portfolio, finding clients, and closing your first project. A dedicated execution plan helps you take action quickly, including a 7-day roadmap to get started.
In addition, the included AI Income Blueprint Workbook provides hands-on exercises for every lesson, helping you apply what you learn immediately and build a practical, repeatable system.
By the end of the course, you will have a clear service, a client acquisition strategy, and a structured path to grow using AI.
Who this course is for
Beginners who want to make money online using AI, freelancers looking to upgrade their skills, and anyone who wants to build a side income or start an AI-based business


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AI in SDLC Software Development Lifecycle with AI


Free Download AI in SDLC Software Development Lifecycle with AI
Published 3/2026
Created by Sandeep Soni
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 9 Lectures ( 1h 39m ) | Size: 1.67 GB

Use AI tools to plan, design, code, test, and deploy software across the SDLC with modern development workflows
What you’ll learn
✓ Understand SDLC phases and their purpose
✓ Identify how AI can be applied in each SDLC phase
✓ Use AI tools for requirement analysis and planning
✓ Apply AI in software design and architecture
✓ Use AI for code generation and debugging
✓ Automate testing using AI-based tools
✓ Automate testing using AI-based tools
✓ Understand real-world AI-driven development workflows
✓ Improve team productivity using AI tools
Requirements
● Basic understanding of software development concepts
● Familiarity with programming basics
● Awareness of software development lifecycle (SDLC) concepts
Description
This course provides a comprehensive understanding of how Artificial Intelligence is transforming the Software Development Lifecycle (SDLC), enabling teams to build, test, and deliver software faster and more efficiently.
Modern development teams are increasingly adopting AI tools to improve productivity, reduce manual effort, and enhance code quality. In this course, you will learn how AI can be applied across every phase of the SDLC, from planning and requirement analysis to development, testing, and deployment.
You will begin by understanding the traditional SDLC phases and how AI integrates into each stage. The course then explores how AI tools can assist in requirement gathering, design decisions, code generation, debugging, testing automation, and documentation.
You will learn how to use tools such as GitHub Copilot, AI-based testing tools, and modern AI workflows to improve development efficiency. The course also covers how AI supports DevOps practices, CI/CD pipelines, and continuous delivery.
In addition, the course highlights real-world use cases, showing how organizations are adopting AI to streamline development workflows and improve collaboration across teams.
By the end of this course, you will have a clear understanding of how to apply AI across the software development lifecycle, making this course highly valuable for developers, DevOps engineers, and teams adopting AI-driven development practices.
Who this course is for
■ Software Developers
■ DevOps Engineers
■ QA Engineers
■ Engineering Managers
■ IT professionals adopting AI workflows
■ Teams looking to improve development productivity using AI
Homepage
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https://www.udemy.com/course/ai-in-sdlc-software-development-lifecycle-with-ai


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AI in Clinical Medicine


Free Download AI in Clinical Medicine
Published 3/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 8h 21m | Size: 5.18 GB
LLMs, Imaging AI & Digital Pathways-From Use Case to Safe Deployment in Real Healthcare Systems

What you’ll learn
Select high-impact clinical AI use cases using a practical impact x feasibility framework
Map workflows to identify where AI truly changes decisions, timing, and workload
Define outcomes, guardrails, and equity checks that withstand governance scrutiny
Deploy LLMs safely using structured prompts, verification, and RAG grounded in policies
Evaluate imaging AI like a reviewer: prevalence traps, external validation, and failure modes.
Design patient-facing AI and monitoring pathways that avoid harm, alerts fatigue, and unsafe triage.
Requirements
There are no formal prerequisites-but to get full value, learners should come in with a solid professional baseline and the right expectations. Recommended background Clinical familiarity: you should understand how care is delivered in at least one setting (hospital, clinic, imaging, or digital care). You don’t need to be a physician, but you should know what workflows, handoffs, and clinical risk feel like. Basic AI literacy: comfort with core terms like training vs inference, sensitivity vs specificity, and what an LLM is at a high level. (You don’t need to code.) Quality/safety mindset: willingness to think in failure modes, escalation pathways, and "what could go wrong" rather than only "how accurate is it?" Operational thinking: interest in how tools get adopted-EHR integration, alert burden, staffing capacity, governance, and measurable outcomes.
Description
– This course contains the use of artificial intelligence –
Healthcare doesn’t need more AI hype-it needs leaders who can turn AI into outcomes without creating new risks. This course is a hands-on, expert-level playbook for building and deploying clinical AI in the real world: hospitals, clinics, imaging workflows, and patient-facing digital pathways.
You will learn how modern clinical AI actually works across predictive models, imaging AI, LLMs, multimodal systems, and agent-like workflow automation. More importantly, you’ll learn how to choose problems worth solving, map clinical workflows, define outcomes and guardrails (clinical, operational, safety, equity), and write use-case briefs that survive governance, IT security, and procurement.
We go deep into the realities of LLMs in healthcare: hallucinations, uncertainty, automation bias, structured prompting, and Retrieval-Augmented Generation (RAG) grounded in local policies and guidelines. You’ll also master imaging AI from dataset and labeling strategy to external validation, prevalence traps, and production integration patterns such as worklist triage, second reader workflows, QA backstops, and reporting automation.
Patient-facing AI gets equal rigor: symptom triage vs coaching vs adherence support, remote monitoring at scale, alert fatigue, and high-risk mental health and neurological safeguards. Throughout the course, you’ll work with real-world examples and the same frameworks used by leading health systems and digital health companies-so you can move from "interesting pilot" to safe, measurable, scalable deployment.
Who this course is for
Global and regional Market Access / HEOR / Medical Affairs leaders who need to evaluate AI-enabled clinical value claims
CMIO/CCIO teams, clinical informaticians, and digital transformation leaders
Radiology, pathology, dermatology, and ophthalmology leaders implementing imaging AI
Clinical operations and quality/safety leaders responsible for governance and outcomes
Digital health product managers building patient-facing AI and remote monitoring pathways
Healthcare data science and ML teams who want a workflow-native, deployment-first mindset
Consultants and strategy teams supporting AI adoption, vendor selection, and scaling


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AI in Action Global Case Studies from Public Institutions


Free Download AI in Action Global Case Studies from Public Institutions
Released 4/2026
With United Nations University and Microsoft
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: General | Genre: eLearning | Language: English + subtitle | Duration: 41m | Size: 183 MB

Explore what AI looks like in practice through expert segments on public policy, digital government, global health, and research, in this course from the United Nations University.
Course details
AI governance and implementation look different depending on sector, region, and institutional context-and those differences matter for anyone working at the intersection of technology and policy.This course brings together experts from the United Nations University network and partner institutions to explore what AI looks like in practice. Through short, focused segments, you’ll learn from practitioners in public policy, digital government, global health, youth research, and development. Each perspective highlights how AI governance and cooperation unfold across borders-from inclusive development and health equity to evidence-based policymaking.Contributors include Dr. Nicole Goldin (UNU-CPR), Charmaine Distor (UNU-EGOV), Dr. Rohit Ramchandani of Antara Global Health Advisors, Dr. Jaimee Stuart of Victoria University of Wellington, and Georgina Curto Rex of UNU Macau.This course was created by Microsoft and United Nations University. We are pleased to host this training in our library.
Skills covered
Artificial Intelligence (AI), Governance, Risk Management, and Compliance (GRC), AI Policy, Governance, and Regulation
Homepage
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https://www.linkedin.com/learning/ai-in-action-global-case-studies-from-public-institutions


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AI Implementation and Operations


AI Implementation and Operations
Duration: 49m | .MP4 1920×1080 30 fps(r) | AAC, 48000 Hz, 2ch | 290.01 MB
Genre: eLearning | Language: English​

AI success doesn’t end with training a model. This course will teach you how to implement, integrate, and operate AI systems in real-world environments to ensure reliability, scalability, and continuous improvement.

More Info:
AI Implementation and Operations


AI Governance Fundamentals Framework, Templates & Sprint


Free Download AI Governance Fundamentals Framework, Templates & Sprint
Published 4/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 56m | Size: 1.94 GB
Build an AI governance framework, assess risk, draft policies, and assign accountability with ready-to-use templates

What you’ll learn
Build a complete AI governance framework: inventory, risk assessment, policy, and accountability
Identify and score AI risk across seven categories using a practical scoring matrix
Draft an AI acceptable use policy that any employee can understand and follow
Understand the EU AI Act, US state laws, and the national AI legislative framework
Assign governance accountability using a RACI matrix with named owners for every AI use case
Create a 30-day sprint plan to take your organization from ungoverned to Level 3 maturity
Prepare audit-ready evidence across six categories that regulators and auditors expect
Apply governance to real scenarios through hands-on assignments and AI-powered role plays
Requirements
No technical background required. This course is designed for business professionals, not engineers. You should have a basic understanding of what AI tools like ChatGPT or Copilot do (you do not need to know how they work). Familiarity with your organization’s structure and current AI usage will help you apply the frameworks immediately.
Description
Your organization is already using AI. The question is whether anyone is governing it.
78% of employees admit to using AI tools their employer never approved. Over a third are sharing confidential data with those tools. AI incidents are up 56% year over year. And only 34% of organizations have a governance framework.
This course is designed to help you start closing that gap.
What makes this course different
● Built by someone who has governed AI in regulated industries, not by someone who read about it
● Covers the 2026 White House National AI Legislative Framework alongside existing regulations
● Practical, not theoretical: includes five ready-to-use templates, not just concepts
● Running scenario (Meridian Consulting) that makes every framework concrete and applicable
● Hands-on assignments where you build governance artifacts for your own organization
● AI-powered role play scenarios where you rehearse real governance conversations
● 15 years of regulated finance experience (Citi, JPMorgan, Bloomberg) distilled into a focused course
What you will learn
● What AI governance actually is (and the five things it is NOT)
● The three pillars: visibility, accountability, and oversight
● Seven categories of AI risk with real-world failure examples
● How to build an AI inventory and discover shadow AI
● How to score risk across seven categories using a practical matrix
● How to draft an acceptable use policy your employees can understand and follow
● How to assign accountability using a RACI matrix
● The EU AI Act phased timeline and what it means for your organization
● The three layers of US AI regulation: state laws, federal agency guidance, and the national legislative framework
● NIST AI RMF vs ISO/IEC 42001: which framework to adopt and why
● Industry-specific Requirements for financial services, healthcare, legal, HR, and government
● What evidence auditors expect and the minimum viable evidence package
● The five-level AI governance maturity model
● A week-by-week 30-day sprint plan designed to help you move from Level 1 (Unaware) toward Level 3 (Defined)
What you will build
Throughout the course, you will follow Meridian Consulting, a fictional 200-person firm with four ungoverned AI use cases. By the end, you will have worked through governing all four and practiced building governance artifacts for your own organization.
Your governance starter kit (5 downloadable templates)
1. AI Inventory Template (Excel)
2. AI Risk Assessment Template (Excel)
3. Acceptable Use Policy Template (Word)
4. AI Governance RACI Matrix (Excel)
5. 30-Day Governance Sprint Planner (PDF)
Plus 3 bonus resources: Audit Readiness Checklist, Regulatory Quick Reference Guide, and Maturity Model Self-Assessment.
What you will practice
● Assignment 1: Build a governance framework for your organization (inventory, risk score, policy rules, owner assignment)
● Assignment 2: Draft your 30-day governance sprint plan with specific people, timelines, and deliverables
● Role Play 1: Brief your CEO on AI governance Requirements (AI-powered, you rehearse the real conversation)
● Role Play 2: Address shadow AI on your team with a defensive VP who sees governance as a threat to productivity
Course format
● ~90 minutes across 15 videos + 1 promo
● Face-on-camera for hooks, scenarios, and recaps
● Professional slides with voiceover for frameworks and data
● Screen recordings walking through each template live
● 2 hands-on assignments with instructor solutions
● 2 AI-powered role play scenarios
● able templates ready to use the same day
Your instructor
Ritesh Vajariya has spent 15 years in regulated finance at Citi, JPMorgan, and Bloomberg, including work on BloombergGPT. He spent 5 years as an AWS Principal Architect, involved in launching SageMaker and Bedrock. Most recently, he led global generative AI strategy at Cerebras. He has trained over 60,000 professionals across 65+ courses. When he covers compliance, he is drawing from 15 years in regulated financial environments, not reading documentation.
This course is designed for anyone responsible for how AI is used in their organization. If you are a business leader, compliance professional, IT director, HR leader, legal counsel, or anyone who has realized that AI governance is no longer optional, this course provides the frameworks, templates, and practice scenarios to help you get started.
Who this course is for
Business leaders and executives responsible for AI adoption and risk management
Compliance and governance professionals expanding into AI oversight
IT directors and CISOs managing AI tool deployment and security
HR leaders using or evaluating AI for hiring, performance, or workforce decisions
Legal counsel advising on AI-related regulatory Requirements
Consultants and advisors helping clients navigate AI governance
Anyone who has realized their organization is using AI without governance and wants to fix it


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AI Governance Basics What Every Professional Must Know


Free Download AI Governance Basics What Every Professional Must Know
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 532.94 MB | Duration: 1h 15m
Learn AI governance fundamentals – frameworks, risk, responsible AI, and regulation – in under 2 hours. No technical bac
What you’ll learn

Understand what AI governance is, why it matters, and how global regulations like the EU AI Act and NIST AI RMF define the landscape.
Identify the core principles of responsible AI – fairness, transparency, privacy, accountability, and human oversight – and why they exist.
Recognize the main categories of AI risk and how organizations classify, assess, and manage AI systems responsibly.
Understand how data governance, consent, and privacy obligations connect to AI development and deployment.
Navigate generative AI governance challenges and evaluate vendor AI tools using the right due diligence questions.
Requirements
No technical background required – this course is designed for professionals across all functions and seniority levels.
A basic familiarity with AI tools (such as chatbots or AI-assisted software) is helpful but not mandatory.
Curiosity and an openness to exploring how governance, ethics, and regulation intersect with AI technology.
Description
This course contains the use of artificial intelligence.AI is reshaping every industry – but are the people deploying it equipped to do so responsibly?From biased hiring algorithms to chatbots giving legally binding wrong advice, from hallucinating AI outputs to opaque automated decisions – the risks of ungoverned AI are no longer hypothetical. They are landing in courts, regulators’ inboxes, and boardrooms right now. This free introductory course gives you a structured, jargon-free foundation in AI governance – so you understand what it is, why it matters, and how organizations are approaching it.Whether you work in compliance, legal, HR, operations, finance, technology, or leadership, this course explains AI governance in plain language and connects every concept to situations you’re likely to encounter at work.What This Course CoversWhat AI governance is, why it has become a global regulatory and business priority, and what the cost of getting it wrong looks like in practiceThe global regulatory landscape – including the EU AI Act’s four-tier risk classification, the NIST AI RMF, ISO 42001, and OECD AI PrinciplesThe core principles of responsible AI: fairness, transparency, accountability, privacy, safety, and human oversightHow organizations identify, classify, and manage AI risk – including third-party and vendor AI riskData governance obligations connected to AI: consent, lawful basis, automated decision-making, and privacy by designHow governance applies across the AI development lifecycle – from pre-development ethics review to post-deployment monitoringGenerative AI governance: hallucination risks, acceptable use policies, and vendor evaluationThe organizational structures, roles, and policy frameworks that underpin effective AI governanceHow to begin your own AI governance learning journey and what certifications and frameworks to explore nextWho Will BenefitProfessionals in compliance, legal, operations, HR, and business functions who need a structured AI governance foundationManagers and business leaders beginning to oversee AI tools and wanting clarity on their responsibilities under emerging regulationLearners considering a career path in AI governance, AI risk management, responsible AI, or related certificationsPrerequisitesNo technical background is required. If you have a basic awareness of AI tools – such as chatbots or AI-assisted software – you have everything you need. This course is designed for professionals across all functions and seniority levels, not just IT or data teams.What You Get With This CourseChapter quizzes at the end of every section to test and reinforce your understandingAn initial knowledge check and a final full-length assessment to measure your progress from start to finishThree practical assignments that take you from passive learner to active practitionerThree immersive role play scenarios that put your knowledge into real organizational contextsA comprehensive downloadable toolkit – including glossaries, checklists, templates, cheat sheets, a vendor due diligence questionnaire, a risk assessment worksheet, and an AI acceptable use policy template – tools you can start using immediatelyThis course is the first step on the AI Governance Professional Track. Completing it will give you a clear picture of your next steps – whether that’s the EU AI Act, NIST AI RMF, AI risk management, or a formal certification pathway.
Professionals in compliance, legal, HR, operations, and business functions who need a structured, jargon-free introduction to AI governance.,Managers and decision-makers beginning to use or oversee AI tools who want to understand their responsibilities under emerging regulations.,Learners exploring a career path in AI governance, AI risk management, or responsible AI – and looking for a structured starting point.
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1480 Radio Pirates 2021 1080p WEB-DL AAC2 0 H 264-EVO

1480 Radio Pirates 2021 1080p WEB-DL AAC2 0 H 264-EVO

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https://www.imdb.com/title/tt1545295/

Title: 1480: Radio Pirates (2014)
Genres: Adventure, Drama, Music
Description: It’s 1965 and rock music is shaking up the world but not in New Zealand. Richard Davis a 23 year old journalist is determined to break the Government’s monopoly on broadcasting and bring rock n’ roll to a younger generation, and at the same time hold onto the woman he loves. Based on a true story.
Director: Craig Newland
Writer: Andrew Gunn, Craig Newland
Actors: Matt Whelan, Daniel Musgrove, Elliot Wrightson
Rating: 5.9
Votes: 155
Rated: N/A
Runtime: 105 min

General:
Name: 1480 Radio Pirates 2021 1080p WEB-DL AAC2 0 H 264-EVO
Format: mkv
Size: 4.98 GB

Video:
Width: 1912 pixels
Height: 808 pixels
Format: AVC
Codec: V_MPEG4/ISO/AVC
Duration: 01:45:56
Bit rate: 6570 Kbps
Frame rate: 23.976 fps
Aspect ratio: 2.40:1
Subtitles: N/A

Audio:
Audio track: 1
Language: English
Codec: A_AAC-2
Bit rate: 151 Kbps
Compression: Lossy
Sampling rate: 48 Khz

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