Napisane przez: charlie - 19-01-2026, 19:05 - Forum: Propozycje
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[center] Directory Opus 13.20.5 Beta Multilingual
Windows x64 | File size: 28.91 MB[/center]
Are you frustrated by the limitations of Windows Explorer? Directory Opus provides a complete Explorer Replacement with far more power and functionality than any other file manager available today. Just some of the features include
- Single or dual pane file display and folder trees
- Tabbed interface let you keep multiple folders open and switch quickly between them
- Unique Explorer Replacement mode provides a full replacement for Windows Explorer
- Quickly filter, sort, group and search your folders
- Color-code your files, assign status icons, star ratings, tags and descriptions
- View images, documents and more. Image marking lets you sort your photos quickly and easily
- Batch renaming including easy-to-use keyboard macros
- View and edit file metadata
- Support for FTP and archive formats like Zip, 7Zip and RAR
- Built-in tools including synchronize and duplicate file finder
- Calculate folder sizes and print or export folder listings
- Queue multiple file copies for improved performance
- Fully configurable user interface - colors, fonts, toolbars, keyboard hotkeys, and a full scripting interface let you tailor Opus exactly to suit your needs
- Efficient, multi-threaded, modern design. Supports the latest 4K monitors. What makes Opus unique?
Built for speed
Opus is written in native C++ multi-threaded code; compiled for the latest 64 bit CPUs, with high performance our number one design principle.
Fully configurable
Change the colors. Change the fonts. Change the toolbars and menus. Set up hotkeys. Opus adapts to how you want to use it.
Makes file management a breeze
Powerful searching, sorting, grouping, labelling and tagging features let you take control of your files like never before.
Endlessly extensible
Work with third-party tools as easily as with the built-in features. A full scripting interface, including scriptable dialogs, means your imagination is really the only limit.
Replace Windows Explorer and don't look back
Our unique Explorer Replacement mode provides a full replacement for Windows Explorer.
Single or dual pane file display and folder trees
Tabbed interface let you keep multiple folders open and switch quickly between them
Integrated viewer, metadata editor and utility panel
Built-in tools including synchronize and duplicate file finder
Leverage indexed search engines like Windows Search and Everything
A complete circuit analysis on DC circuits.
What you'll learn
Students can solve any DC circuit after completing this circuit.
Students also gain an understanding of how electric circuit works in general with supporting labs.
This course also includes practical information that are required in real life applications.
A great stepping stone for the electrical engineering career.
Requirements
Basic Calculus (Basic Math)
Description
This course teaches you the fundamental steps of Circuit Analysis.After this course, you will be able to solve any DC circuit you encounter. You will also learn basic circuit elements with their basic properties. Additionally, you lean basic laws with lots of theorems that will help you to solve problems. This is the most complete course on Udemy about DC CIRCUIT ANALYSIS. We are here to help you. In the first unit we will begin with basic concepts. After that we will see some laws that allows us to analyze our circuits. Plus, these laws will be applicable to different kinds of analysis, too.After basic laws, we will see Circuit theorems which are really helpful to minimize and simplify our circuits. After learning lots of analysis methods, theorems and laws, we will learn a active element called operational amplifiers. Then we will talk about capacitors and inductors in general as a supplimentary material for next units which are first-order and second-order circuit. A rough overwiev of the curriculum;1-) Basic Concepts-Si Units-Basic Concepts-Circuit Elements2-) Basic Laws-Ohm's Law-Nodes,Branches and Loops.-KCL, KVL-Series and Parallel Connection of Resistors.3-) Methods of Analysis-Nodal Analysis-Nodal Analysis with Voltage Sources-Mesh Analysis-Mesh Analysis with Current Sources4-) Circuit Theorems-Linearity-Superposition-Source Transformation-Thevenin's Theorem-Norton's Theorem-Max Power Transfer5-) Operational Amplifiers-Non-Ideal Op Amps-Ideal Op Amps-Inverting Op Amps-Non-Inverting Op Amps-Summing Op Amps-Difference Op Amps-Cascaded Op Amps6-) Capacitors and Inductors-Capacitors and General Properties of Them-Connection of Capacitors-Inductors and General Properties of Them-Connection of Inductors7-) First-Order Circuits-The Source Free Rc Circuits-The Source Free Rl Circuits-Singularity Functions-The Step Response of An Rc Circuit-The Step Response of An Rl Circuit8-)Second-Order Circuits-Finding the Initial Values-The Source Free Series Rlc Circuits-The Source Free Parallel Rlc Circuits-The Step Response of a Series Rlc Circuit-The Step Response of a Parallel Rlc CircuitYou can learn more about the curriculum in the introduction video and also you can ask your questions by mailing or messaging.Hope you enjoy your journey with us.Welcome to AFTERCLAP.
Who this course is for
People who contemplate a career in electric engineering or related engineering fields such as power and energy systems, systems and control, signal processing and telecommunication. In a clearer way, this course is an excellent opportunity for those who want to learn about basic DC circuits.
Napisane przez: charlie - 19-01-2026, 19:03 - Forum: Propozycje
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[center]
Databricks Certified: Generative Ai Engineer Associate
Published 1/2026
Created by Kuljot Singh Bakshi
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 40 Lectures ( 7h 12m ) | Size: 5.84 GB[/center]
Master RAG, Vector Search, Embeddings, MLflow, and GenAI workflows to pass the Databricks GenAI Engineer exam What you'll learn
✓ Understand the Databricks Generative AI architecture, including foundation models, embeddings, vector search, and Mosaic AI tooling.
✓ Build and deploy Retrieval-Augmented Generation (RAG) applications using Databricks, Vector Search, and MLflow.
✓ Apply prompt engineering techniques to improve LLM accuracy, grounding, and reliability in Databricks workloads.
✓ Use Databricks Vector Search and embeddings effectively for semantic search, document retrieval, and AI applications.
✓ Evaluate, monitor, and version GenAI models using MLflow, experiments, and production best practices.
✓ Implement responsible and secure GenAI solutions following Databricks governance, access control, and cost-aware design.
✓ Prepare confidently for the Databricks Certified GenAI Engineer Associate exam with exam-focused explanations and real-world examples. Requirements
● Basic understanding of Python programming (loops, functions, and working with notebooks).
● A Databricks Managed version by a Cloud Service Provider (CSP)
● A Databricks account or workspace access (Community Edition or enterprise) for hands-on practice.
● Interest in Generative AI and LLM-based applications - no prior GenAI experience is required. Description
This course is a complete, exam-aligned guide to the Databricks Certified Generative AI Engineer Associate certification, designed for professionals who want to build, deploy, and manage Generative AI applications on Databricks with confidence.
Generative AI on Databricks goes far beyond prompt writing. To succeed in real-world projects-and in the certification exam-you must understand how foundation models, embeddings, vector search, RAG pipelines, MLflow, and governance work together. This course focuses exactly on those skills.
You will learn how to design and implement Retrieval-Augmented Generation (RAG) systems, use Databricks Vector Search for semantic retrieval, manage embeddings effectively, and integrate LLMs into scalable data and analytics workflows. Every concept is explained with a clear mental model, followed by hands-on demonstrations using Databricks-native tools.
The course is structured to closely align with the official Databricks exam blueprint, helping you understand not just what to do, but why it works-an essential skill for both certification success and real-world engineering.
In this course, you will
• Understand Databricks' Generative AI architecture and ecosystem
• Build end-to-end RAG applications using embeddings and Vector Search
• Apply prompt engineering techniques for reliable and grounded outputs
• Track, evaluate, and manage GenAI models using MLflow
• Follow best practices for governance, security, and cost awareness
• Prepare confidently for the Databricks Certified GenAI Engineer Associate exam
Whether you are preparing for certification or looking to upskill in production-grade Generative AI on Databricks, this course provides a structured, practical, and exam-focused learning path. Who this course is for
■ Data engineers, analytics engineers, and machine learning practitioners who want to build GenAI applications on Databricks.
■ Professionals preparing for the Databricks Certified Generative AI Engineer Associate exam and looking for a structured, exam-aligned course.
■ Data scientists and ML engineers who want hands-on experience with RAG, embeddings, and Vector Search using Databricks.
■ Software engineers and platform engineers interested in integrating LLMs into data and analytics workflows.
■ Databricks users and cloud data professionals looking to upskill in Generative AI using Databricks-native tools.
Napisane przez: charlie - 19-01-2026, 19:02 - Forum: Propozycje
- Brak odpowiedzi
[center]
Data Analysis With Polars And Python
Published 1/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 22h 11m | Size: 14 GB[/center]
Master data analysis with the powerful Polars library! Up-to-date for 2026. All datasets included --- beginners welcome!
What you'll learn
Master data manipulation operations in Polars including sorting, filtering, grouping, pivoting, joining and more!
Understand Polar's functional, expression-based syntax for building up complex chains of logic
Use LazyFrames to create complex query plans that Polars can optimize for efficiency
Work with a variety of data including text, temporal, numeric, nested structures, and more
Requirements
Basic/intermediate experience with a spreadsheet software like Microsoft Excel/Google Sheets (common functions, vlookups, countif, pivot tables etc)
Basic experience with the Python programming language (we'll cover the basics if you're brand new!)
Strong knowledge of data types (strings, integers, floating points, booleans) etc
Description
Welcome to the most comprehensive Polars course on Udemy! Data Analysis with Polars and Python offers 22+ hours of in-depth video tutorials on the powerful Polars data analysis library. The course also includes a wide collection of datasets, quizzes, and coding challenges to aid your learning.Why Polars?The core of Polars is written in Rust, one of the fastest programming languages in the world. At the same time, the library enables us to write our code in Python, the most popular language in the world. We gain the best of both worlds -- the speed and efficiency of Rust and the simplicity and elegance of Python.Who is this Course For?The course is designed for learners of all skill levels, from experienced data analysts to students who have never programmed before. Lessons include:installing Python and Polars on your computerunderstanding the core mechanics of Pythonworking with the Jupyter Lab coding environmentWhether you've spent time in a spreadsheet software like Microsoft Excel/Google Sheets or another data analysis library like Pandas, Polars can help take your data analysis skills to the next level.What Topics Will We Cover?We'll cover the core objects of Polars including:SeriesDataFramesLazyFramesMost of our work will focus on the DataFrame, a 2-dimensional table of rows and columns. We'll cover data manipulation operations includingortingfilteringgroupingaggregatingde-duplicatingpivotingdeletingjoiningreplacingworking with text dataworking with temporal/datetime dataWe'll also cover some of Polar's unique column data types including:listsarraysstructsand more!Data Analysis with Polars and PythonI'm excited to share everything I've learned about Polars, a powerful library that is quickly emerging as a dominant competitor in Python's data science ecosystem. I look forward to seeing you in the course!
Who this course is for
Data analysts and business analysts
Excel/Google Sheets users who looking to learn a more powerful software for data analysis
Developers familiar with Pandas who want to explore the rising entrant in the Python data science ecosystem
Napisane przez: charlie - 19-01-2026, 19:01 - Forum: Propozycje
- Brak odpowiedzi
[center]
Customer Success Workflow Essentials: Scalable Cs Processes
Published 1/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 4m | Size: 1.1 GB[/center]
Master onboarding, adoption signals, risk intervention, and SOPs to drive retention and scale your CS team effectively.
What you'll learn
Build the foundational logic of scalable workflows as the mandatory first step before implementing AI-driven automation and complex CS tech stacks.
Design a frictionless Sales-to-CS handoff and drive customers toward "First Value Milestones" to secure high adoption and retention in the first 90 days.
Master proactive risk playbooks, including "Ghosting" re-engagement and "Path to Green" strategies based on real product usage signals, not just NPS.
Create minimalist, "Workflow-in-a-Box" SOPs that enable your team to scale without burnout or loss of service quality as your customer base grows.
Requirements
A basic understanding of the Customer Success Manager (CSM) role and the customer lifecycle.
Description
In today's ever-changing world of AI and automation, everyone is looking for a shortcut to efficiency. But know this: You cannot automate chaos. The absolute number one step to building effective AI workflows and leveraging automation is mastering the essentials of how to build a manual, scalable workflow first. If you don't understand the logic of triggers, actions, and outcomes, even the most advanced AI tools will only help you fail faster.In Customer Success Workflow Essentials, I provide the foundational blueprint you need before you even think about automation. This course is a practical, execution-focused guide for building a CS department that runs like a machine. We focus exclusively on the workflows, triggers, and playbooks that drive adoption, protect revenue, and serve as the perfect "logic map" for future AI implementation.What you will master in this course:The Foundation for Automation: Learn the anatomy of a workflow-Triggers, Actions, and Outcomes-so you can eventually hand these processes over to AI with 100% confidence.The Onboarding & Velocity Engine: Design a frictionless sales-to-CS handoff and drive customers to their "First Value Milestone" to ensure they don't churn in the first 90 days.Adoption Signals vs. Vanity Metrics: Stop obsessing over NPS and start tracking the "Golden Features" and usage signals that actually predict a renewal.Proactive Risk Playbooks: Deploy proven "Ghosting Playbooks" to re-engage silent accounts and "Path to Green" workflows to rescue high-risk customers.The Commercial Loop: Turn renewals into a "non-event" with a 90-day countdown and identify expansion triggers for upsell opportunities.Lightweight Documentation: Learn how to document your processes using "Minimum Viable SOPs" that your team will actually follow.Why take this course?As a senior CS leader who has built these workflows from scratch multiple times, I am teaching you the "Workflow-in-a-Box" system. You will walk away with a Capstone Project that functions as a live pilot for your company, complete with email templates, success plan canvases, and audit checklists. Whether you want to manage your accounts manually or prep your department for an AI transition, these are the essentials you cannot skip.Who this is for:CSMs looking to manage larger books of business with less stress.CS Leaders tasked with scaling a team or reducing churn.SaaS Founders building their first Success department who want to get the logic right before they automate.
Who this course is for
This course is designed for New and Mid-level CSMs who feel reactive and overwhelmed, CS Leaders tasked with building a department from scratch, and SaaS Founders looking to standardize their customer journey
Transform your images with next-generation Artificial Intelligence. Take your old, blurry or low-quality photos to a new level of sharpness and definition. The ResizeScaleAI uses advanced Artificial Intelligence technology to accurately increase the resolution of your images, preserving textures, fine details and superior visual quality. With intelligent facial restoration, the software reconstructs facial features naturally, recovering details that seemed unrecoverable, maintaining identity, proportions and realism. Whats New
Updates: official site does not provide any info about changes in this version
Napisane przez: Drograms - 19-01-2026, 19:00 - Forum: DPŚ
- Brak odpowiedzi
Anything you need, just email to: jim1829#hotmail.com change # into @
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If you need a latest software version, please email to: jim1829#hotmail.com change # into @
Anything you need, just email to: jim1829#hotmail.com change # into @
We supply too many latest softwares, the software list is not full, just email for more software.
Ctrl + F to search program with crack
If you need a latest software version, please email to: jim1829#hotmail.com change # into @
![[Obrazek: 06b5661edd74ed85d792eb33a185a5f9.png]](https://i126.fastpic.org/big/2026/0119/f9/06b5661edd74ed85d792eb33a185a5f9.png)
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ortingfilteringgroupingaggregatingde-duplicatingpivotingdeletingjoiningreplacingworking with text dataworking with temporal/datetime dataWe'll also cover some of Polar's unique column data types including:listsarraysstructsand more!Data Analysis with Polars and PythonI'm excited to share everything I've learned about Polars, a powerful library that is quickly emerging as a dominant competitor in Python's data science ecosystem. I look forward to seeing you in the course!![[Obrazek: _cf454674e4f64b663090b364ea0da899.png]](https://i126.fastpic.org/big/2026/0119/99/_cf454674e4f64b663090b364ea0da899.png)
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