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Free Download Astronomy – The Solar System
Last updated 3/2025
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 20m | Size: 3.55 GB
Learn 100 of topics of our solar system at one place

What you’ll learn
The Sun, the Earth, the Moon – starting from the formation of the solar system till how it will die
The fascinating world of planets Jupiter and Saturn and the moons of our solar system
The dwarf planets of our solar system, the asteroid belt, the Kuiper Belt and Oort Cloud
The spacecrafts and artificial satellites
Requirements
You will learn everything you need to know from scratch
Description
Whether you want to build a career in astrophysics or just exploring the areas out of interest, this Spotle compact course is for you. What’s so exciting about this course?
• Hundreds of topics have been taught with detailed explanation.
• Learn about the often left-out part of our solar system such as – the dwarf planets, asteroid belt or Kuiper belt.
• Learn about the Sun, the Earth, the Moon, the gas giants and hundreds of moons of our solar system.
• In modern days our solar system is just not a family of natural objects. There are few thousands of artificial objects there in the solar system – learn about them.
• Did you know – you don’t even have to buy this course if you already know the answers to all the questions. It’s simple, you will not pay if we are not adding to your knowledge. You can play all the videos with questions for free. Please try.
Let’s start our journey here. We know, Pluto is no more the ninth planet of our solar system. It has now been categorised as a dwarf planet. Do you know how many more known dwarf planets we have in our solar system? We know Mercury is the closest planet to the Sun. But, do you know the name of the dwarf planet closest to the Sun? Do you know its details? Colonizing Mars is a topic of the moment, no doubt. Do you know when it all began? What is the name of the first artificial satellite orbiting Mars? What is the first spacecraft that landed on Mars? Do you know the planet Saturn would float in water, only if you had such a big enough ocean to hold Saturn? Do you know Pluto is just not a dwarf planet. It is also a double planet. But why? When was our solar system created and how? When was the Earth, the Moon created and how? You will learn about hundreds of such fascinating topics in this course.
Who this course is for
This course is for all, irrespective of the field of study or work.

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Free Download Asset Servicing in a Digital World
Published 4/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 33m | Size: 2.78 GB
Post-Trade Processing, Corporate Actions, Blockchain, AI and Digital Assets in Capital Markets

What you’ll learn
Understand how asset servicing and corporate actions operate within modern capital markets infrastructure
Explain how blockchain technology, digital assets, and tokenization interact with financial market systems
Compare traditional exchanges and financial infrastructure with emerging decentralized financial technologies
Understand the roles of stablecoins, CBDCs, and digital settlement systems in future financial markets
Evaluate how technologies such as tokenization, stablecoins, and CBDCs may influence future capital markets
Requirements
Basic familiarity with financial markets or capital markets is helpful but not required. The course explains core concepts step-by-step and introduces the necessary terminology as we go along.
No programming experience required.
Description
Asset Servicing in a Digital World
Financial markets are undergoing one of the most significant technological transformations in decades. Technologies such as blockchain, digital assets, artificial intelligence, and tokenization are beginning to reshape the infrastructure that powers global capital markets.
This course explores how these emerging technologies intersect with the world of asset servicing and post-trade processing, with a particular focus on corporate actions, financial market infrastructure, and digital financial systems.
You will learn how blockchain networks function, how digital assets and tokenization are evolving, and how decentralized applications interact with financial infrastructure. We also explore the role of governance, regulation, and exchanges within emerging digital markets.
A key focus of the course is understanding how new digital systems connect to existing capital markets infrastructure. Topics such as stablecoins, central bank digital currencies (CBDCs), tokenized securities, decentralized exchanges, and blockchain governance are explored through the lens of real financial market operations.
This course is designed for professionals in Capital Markets – particularly those working in post-trade and operations roles, including asset servicing professionals, Business and Systems analysts, Product Owners, and Project Managers.
By the end of the course, you will have a clear conceptual understanding of how traditional financial systems and digital technologies intersect – and how these changes may influence the future of global capital markets.
Who this course is for
Professionals working in capital markets, securities processing, or asset servicing
Corporate actions and post-trade specialists who want to understand emerging digital technologies
Financial technology professionals interested in blockchain and digital assets
Students and analysts seeking a structured introduction to digital financial infrastructure
Anyone interested in how blockchain and tokenization may reshape capital markets

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Free Download Aspen HYSYS V15 Fundamentals of Process Simulation
Last updated 2/2026
Created by Vítor Vanzolin Bento
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 39 Lectures ( 4h 2m ) | Size: 2.57 GB

Learn the fundamentals of steady-state process simulation using Aspen HYSYS V15 through practical engineering examples.
What you’ll learn
✓ Understand the Aspen HYSYS V15 interface and workflow for steady-state simulation.
✓ Perform heat exchanger design and rating using Aspen EDR.
✓ Design and analyze distillation columns for separation processes.
✓ Apply appropriate thermodynamic models for different unit operations.
✓ Build and configure steady-state process flowsheets from scratch.
✓ Model and simulate chemical reactors, including reaction kinetics and conversion.
✓ Simulate and optimize pressure-changing equipment such as pumps and compressors.
✓ Interpret simulation results to make process optimization and troubleshooting decisions.
Requirements
● No prior experience with Aspen HYSYS or any process simulation software is required. This course is designed to guide students step-by-step, from basic concepts to practical application.
● Understanding of energy balances – including heat and work interactions in unit operations.
● Familiarity with common unit operations – such as reactors, distillation columns, heat exchangers, pumps, and compressors.
● Basic chemical engineering concepts – such as reaction stoichiometry, phase behavior, and process variables.
● Basic knowledge of mass balances – understanding how to account for the flow of materials in process systems.
Description
This course covers the fundamentals of process simulation using Aspen HYSYS V15, with a clear focus on steady-state simulation applied to chemical, petrochemical, and oil & gas processes.
The content is structured around a practical and professional engineering workflow, showing how steady-state process simulations are developed from scratch. You will learn how to select appropriate thermodynamic property packages and how to model the main process equipment, including heat exchangers, pressure-changing equipment (pumps and compressors), separation units, and reactors, all within a steady-state environment.
The course emphasizes clarity, efficiency, and real-world application, avoiding unnecessary complexity while ensuring a solid understanding of how Aspen HYSYS is used in industrial steady-state simulations. Each section helps you understand how individual unit operations interact within a complete process flowsheet.
In this course, you will use the Exchanger Design and Rating (EDR) module to simulate and evaluate shell-and-tube heat exchangers under realistic operating conditions. You will learn how to define geometry, operating parameters, and thermal specifications, as well as how to analyze heat transfer performance, pressure drop, and design feasibility within steady-state process simulations.
By the end of the course, you will be able to
• Build and analyze steady-state process simulations in Aspen HYSYS V15
• Select and apply thermodynamic property packages correctly
• Model and connect key process equipment used in industry
• Understand the structure and logic of steady-state process simulation workflows
This course provides a strong foundation in steady-state process simulation with Aspen HYSYS, serving as a reliable base for more advanced modeling and future dynamic studies.
—
Course Scope
This course focuses exclusively on steady-state process simulation using Aspen HYSYS. Dynamic or transient simulations, process control studies, and Aspen Dynamics are not included.
—
Through practical examples and case studies, learners will simulate common industrial separation problems, analyze results, and evaluate performance.
After completing this course, participants will be able to confidently build, run, and analyze distillation models in Aspen HYSYS, interpret simulation results, and apply them to process design, operation, and optimization tasks in an industrial context.
You will learn the fundamental concepts required to build, run, and analyze steady-state simulations in Aspen HYSYS, starting from the user interface and progressing to complete process flowsheets.
Who this course is for
■ Undergraduate and graduate students in Chemical Engineering, Process Engineering, Energy Engineering, and related fields.
■ Engineers and technical professionals working in the chemical, process, energy, and oil & gas industries.
■ Professionals seeking to start or improve their skills in Aspen HYSYS steady-state simulation.
■ Recent graduates and researchers looking to develop practical, industry-relevant process simulation skills.
■ Professionals who need to apply process modeling and analysis using industry-standard tools.
Homepage
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https://www.udemy.com/course/aspen-hysys-process-simulation

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ASP.NET Core Web API Fundamentals
Released/Updated: Feb 28, 2025
Duration: 8h 32m 24s | .MP4 1920×1080, 30 fps(r) | AAC, 48000 Hz, 2ch | 2.3 GB
Genre: eLearning | Language: English​

In this course, you’ll learn how to build an API with ASP.NET Core that connects to a database via Entity Framework Core from scratch.
What you’ll learn

ASP.NET Core is a great platform for building APIs with. In this course, ASP.NET Core Web API Fundamentals, you’ll learn how to build an API with ASP.NET Core that connects to a database via Entity Framework Core. First, you’ll learn how to get started with API building in ASP.NET Core. Next, you’ll discover how to get and manipulate data from services, use the built-in dependency injection system, and work with configuration files. Finally, you’ll learn how to connect to a database through Entity Framework Core and how to document your API. When you’re finished with this course, you will be able to build an API from scratch with ASP.NET Core.

More Info

Please check out others courses in your favourite language and bookmark them
– – – –

Artstation – ZBrush For Ideation 300+ Video Series
MP4 | Video: MPEG4 Video (H264) 1920×1080 30fps 776kbps | Audio: AAC 44100Hz stereo 125kbps | Duration: 30hr+ | 18.2 GB
Genre: eLearning | Language: English​

40+ New and updated videos for the series, adding relevant new 2021 functionality to existing videos, including an entirely new hour-long intro (Unit01 Videos 001-009)! Dynamic cloth, new zmodeler functionality, microPoly, and nanomesh updates make creation and exploration in ZBrush even easier than ever before!! I also went ahead and put an hour and forty minute making of the "mailbox" marketing art for the 2021 release just for fun!

2021.5 &.6 Update

19 New and updated videos, more than 4.5 hours covering new curve functionality (repel strength, bend start/end, extrude profile, snake curve brushes), as well as the new mesh from mask brushes and thick skin functionality!

More info

Artificial Intelligence: Reinforcement Learning in Python
Duration: 14h 42m | .MP4 1920×1080 30fps(r) | AAC, 44100Hz, 2ch | 3.82 GB
Genre: eLearning | Language: English​

Complete guide to Reinforcement Learning, with Stock Trading and Online Advertising Applications
What you’ll learn

• Apply gradient-based supervised machine learning methods to reinforcement learning
• Understand reinforcement learning on a technical level
• Understand the relationship between reinforcement learning and psychology
• Implement 17 different reinforcement learning algorithms
• Understand important foundations for OpenAI ChatGPT, GPT-4

Requirements

• Calculus (derivatives)
• Probability / Markov Models
• Numpy, Matplotlib
• Beneficial to have experience with at least a few supervised machine learning methods
• Gradient descent
• Good object-oriented programming skills

Description
Ever wondered how AI technologies likeOpenAIChatGPTandGPT-4really work? In this course, you will learn the foundations of these groundbreaking applications.

When people talk aboutartificial intelligence, they usually don’t mean supervised and unsupervisedmachine learning.

These tasks are pretty trivial compared to what we think of AIs doing – playing chess and Go, driving cars, and beating video games at a superhuman level.

Reinforcement learninghas recently become popular for doing all of that and more.

Much likedeep learning, a lot of the theory was discovered in the 70s and 80s but it hasn’t been until recently that we’ve been able to observe first hand the amazing results that are possible.

In 2016 we sawGoogle’sAlphaGobeat the world Champion in Go.

We saw AIs playing video games like Doom and Super Mario.

Self-driving cars have started driving on real roads with other drivers and even carrying passengers (Uber), all without human assistance.

If that sounds amazing, brace yourself for the future because the law of accelerating returns dictates that this progress is only going to continue to increase exponentially.

Learning about supervised and unsupervised machine learning is no small feat. To date I have over TWENTY FIVE (25!) courses just on those topics alone.

And yet reinforcement learning opens up a whole new world. As you’ll learn in this course, the reinforcement learning paradigm is very from both supervised and unsupervised learning.

It’s led to new and amazing insights both in behavioral psychology and neuroscience. As you’ll learn in this course, there are many analogous processes when it comes to teaching an agent and teaching an animal or even a human. It’s the closest thing we have so far to a true artificial general intelligence. What’s covered in this course?

The multi-armed bandit problem and the explore-exploit dilemma

Ways to calculate means and moving averages and their relationship to stochastic gradient descent

Markov Decision Processes (MDPs)

Dynamic Programming

Monte Carlo

Temporal Difference (TD) Learning (Q-Learning and SARSA)

Approximation Methods (i.e. how to plug in a deep neural network or other differentiable model into your RL algorithm)

How to use OpenAI Gym, with zero code changes

Project: Apply Q-Learning to build a stock trading bot

If you’re ready to take on a brand new challenge, and learn about AI techniques that you’ve never seen before in traditional supervised machine learning, unsupervised machine learning, or even deep learning, then this course is for you.

See you in class!

"If you can’t implement it, you don’t understand it"

Or as the great physicist Richard Feynman said: "What I cannot create, I do not understand".

My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratch

Other courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code?

After doing the same thing with 10 datasets, you realize you didn’t learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times.

Suggested Prerequisites:

Calculus

Probability

Object-oriented programming

Python coding: if/else, loops, lists, dicts, sets

Numpy coding: matrix and vector operations

Linear regression

Gradient descent

WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:

Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)

UNIQUE FEATURES

Every line of code explained in detail – email me any time if you disagree

No wasted time "typing" on the keyboard like other courses – let’s be honest, nobody can really write code worth learning about in just 20 minutes from scratch

Not afraid of university-level math – get important details about algorithms that other courses leave out

Who this course is for:

• Anyone who wants to learn about artificial intelligence, data science, machine learning, and deep learning
• Both students and professionals

More Info

Free Download Artificial Intelligence Set Up Your Business With AI Help
Published 4/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 25m | Size: 1.46 GB
Setting up your own business has never been easier thanks to artificial intelligence. We show you the steps A-Z with AI

What you’ll learn
Translate ideas to functioning app!
Translate ideas to functioning website!
Set up payment system and get paid!
Create an app without IT skills!
Requirements
No IT skills needed. All are welcome.
Description
This course contains the use of artificial intelligence.
Artificial Intelligence: Set Up Your Business With AI Help
WHO IS IT FOR?
Setting up your own business used to be costly and difficult! You needed a lot of money, expertise and time to translate your idea into a website or app and install a payment system.
However, thanks to artificial intelligence, all of this can be done without IT knowledge and with almost no budget at all! AI can help you turn your idea into app and website functionality in seconds and for pennies. Do you want to get paid by customers? No need to invest in expensive payment solutions. AI can do that for you in seconds and for a few pennies. This is an exciting time to be alive. Many of the entrepreneurship dreams that you "parked" due to lack of time, money and expertise, can be revived. In this course, we help you set up your own business by showing you how AI can help you with all the steps. We use one AI application called Lovable.
YOUR TRAINERS
This course is a cooperation of Six Sigma Academy Amsterdam (SSAA), a well established and accredited training provider with almost 250,000 students worldwide and Melissa, a seasoned AI entrepreneur and consultant.
EXTRA
• 30 day money back guarantee by Udemy
• Certificate of completion at the end
• Lifelong access to materials
Who this course is for
You want to learn how to launch your own business by using AI.

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Free Download Artificial intelligence accountability by dr.pavan duggal
Published 4/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 41m | Size: 2.92 GB
AI Accountability: Explainability, Risk Management, Liability & Ethical AI Governance

What you’ll learn
learners will be able to define key terms such as "AI accountability," "transparency," "responsibility," and "governance," and apply apply these concepts
Learners will be able to map key stakeholders (developers, data teams, product managers, regulators, and end‑users) and explain who is accountable at each stage
Learners will be able to identify typical risks (e.g., bias, discrimination, lack of explainability and safety failures
Learners will be able to outline simple accountability frameworks such as audit trails, model documentation and oversight procedures
Requirements
No programming experience required. You can learn everything that you need to learn about AI Accountability
Description
As Artificial Intelligence systems increasingly influence decisions across governance, business, and society, the need for accountability has never been more critical. This course Artificial Intelligence Accountability by Dr. Pavan Duggal provides a structured understanding of how responsibility, transparency, and oversight can be established in AI-driven environments.
The course explores the key dimensions of AI accountability, including liability, algorithmic transparency, explainability, auditability, and traceability. Learners will gain insight into how accountability is embedded across the entire AI lifecycle from design and development through to deployment and real-world application. The course further examines the legal and regulatory landscape surrounding responsible AI, covering risk assessment, compliance obligations, and governance frameworks that are becoming central to AI regulation worldwide.
Special focus is given to practical challenges: identifying liability when AI systems cause harm, ensuring fairness and non-discrimination, and building effective mechanisms for redress and oversight. Emerging global approaches to AI accountability and the need for robust institutional frameworks are also examined in depth.
Designed for legal professionals, policymakers, regulators, technology stakeholders, and general users alike, this course bridges the gap between theory and practice. By the end, learners will be equipped to critically assess AI systems, implement meaningful accountability measures, and contribute to building trustworthy, responsible AI ecosystems.
Who this course is for
This course is for anyone who wants to understand how to make artificial intelligence systems transparent, responsible, and answerable when things go wrong. Who this course is for: AI practitioners and developers who build or deploy machine‑learning models and want to integrate accountability into their design, testing, and deployment workflows. Product managers, data scientists, and tech leads who need to manage AI projects with ethical and governance considerations, including risk assessment and documentation. Policy makers, compliance officers, and regulators interested in how to oversee AI systems, set guardrails, and ensure organizations fulfill their accountability obligations. Business leaders and executives who use AI tools in operations, marketing, HR, or customer service and need to understand their responsibilities and potential liabilities. Students and professionals in law, ethics, public policy, or social sciences who want to grasp the practical side of AI accountability and how it connects to real‑world governance and regulation. In short, this course is ideal for learners who care about "who is responsible when AI causes harm" and want concrete principles and tools to foster accountable AI in their work

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