Win More Sales, Build Stronger Relationships, and Deliver Impactful Results in a Remote-First World
What you'll learn
Learn how to approach selling in a hybrid environment (Online and in person)
Learn 12 Best Practice Principles for Virtual Selling
Learn the application of these principles by watching a Live Session
Understand how this fits alongside a Consultative Selling approach Requirements
Being in a Sales or Business Development role will enable you to put these skills into practice straight away. Description
Selling virtually isn't just a temporary fix-it's the new normal for high-performing sales professionals. In this course, you'll discover how to master the art of remote selling using proven frameworks, practical tools, and professional communication strategies that build trust, strengthen relationships, and drive consistent, measurable results.Whether you're leading complex sales conversations via Zoom, running virtual discovery meetings, or navigating gatekeepers online, this course equips you with the skills, tools, and confidence to excel in today's evolving digital landscape.You'll learn how to:Structure high-impact virtual meetings that keep buyers engagedBuild rapport and connection-without being in the same roomUncover deeper needs using strategic questioning techniquesPresent solutions with clarity and convictionClose deals faster with collaborative follow-ups and next stepsYou'll also gain insights into how to prepare effectively for remote conversations, maintain momentum throughout your pipeline, and use technology to your advantage without losing the human touch or professional credibility.We'll explore how to integrate virtual and in-person selling into a cohesive hybrid strategy-so you can meet customers where they are, reduce travel time, and maximise your effectiveness at every stage of the sales process.Ideal for B2B sales professionals, sales leaders, account managers, and business development teams who want to thrive in a remote-first and hybrid sales environment.If you're ready to modernise your sales approach and stay ahead of the curve, this course is for you. Overview
Section 1: Introduction
Lecture 1 Welcome to the Virtual Selling course
Lecture 2 Introduction to your trainer
Section 2: 3 Principles of Hybrid Selling
Lecture 3 3 Principles of Hybrid Selling
Section 3: The Top 12 Principles for Virtual Selling
Lecture 4 The Top 12 Principles of Virtual Selling
Lecture 5 Live Virtual Selling Workshop
Section 4: Reflection, Self Coaching & Professional Development
Lecture 6 Personal Reflection
Section 5: Congratulations & Next Steps - The full consultative selling approach
Lecture 7 Congratulations - what's next?
Sales Professionals,Business Development Managers,Key Account Managers,Customer Service Managers,Sales Managers,Sales Directors
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In this course, AI expert Pascal Bornet presents an exploration into agentic AI-systems that don't merely suggest but take autonomous action. Based on his book Agentic Artificial Intelligence and years of implementation experience across organizations, this course cuts through the hype to deliver practical, actionable insights.
Agentic AI is about building digital teammates that plan, decide, and execute multi-step tasks independently. This frees us from tedious work to focus on meaningful activities, creating faster operations, lower costs, and fewer mistakes.
Discover powerful new business models, learn to drive tangible organizational impact, and gain tools to supercharge productivity in this rapidly changing landscape. Homepage:
Turn AI into Action and Lead with Confidence: Practical Insights for Today's Business Leaders. A guide for leading AI
What you'll learn
Understand Core AI Concepts Without Technical Jargon
Identify and Prioritize High-Impact AI Opportunities
Develop an AI Strategy Aligned with Organizational Goals
Lead AI Projects with Confidence and Clarity
Implement Responsible AI Governance and Ethical Oversight
Prepare for the Future of Work and AI-Driven Leadership Requirements
No prerequisites other than the desire to lead in the AI Age! Description
Lead with Confidence in the AI AgeArtificial Intelligence is transforming every industry-from marketing and operations to HR and finance. But it's not just a tech trend. It's a leadership imperative.This course is your complete, non-technical guide to understanding AI, leading responsibly, and driving strategic value in your organization. Whether you're a senior executive, team leader, or aspiring manager, you'll gain the tools to make smarter decisions, guide your team through change, and turn AI into a business advantage.What You'll LearnHow AI works in business (without the jargon)How to identify and prioritize high-impact AI use casesHow to build an AI-ready organization and cultureHow to lead AI projects, even without a technical backgroundHow to navigate ethical, legal, and governance challengesHow to prepare for the future of AI-powered workWhy This Course?Real-world examples and use cases across departmentsPractical frameworks you can apply immediatelyEthics and governance built-in from the startFuture-ready mindset to guide transformation, not just react to itCourse CurriculumWelcome and FoundationsWhat You'll Learn in This CourseWhy AI Matters for Business Leaders TodayUnderstanding AI Without the JargonWhat Is AI, Really? (In Plain English)Machine Learning, Generative AI, NLP: What You Need to KnowKey AI Tools and Technologies in BusinessReal-World Business Use CasesAI in Marketing: Personalization, Targeting, and ContentAI in Operations: Forecasting, Automation, and EfficiencyAI in HR and Talent: Recruiting, Engagement, and ProductivityAI in Finance: Risk Analysis, Fraud Detection, and InsightsAI in Customer Service: Chatbots, Support, and Sentiment AnalysisBuilding an AI StrategyIdentifying the Right AI OpportunitiesAssessing Organizational ReadinessCreating a Roadmap for AI AdoptionHow to Build an AI-Ready CultureLeading AI Projects (Without Coding)Working with AI Vendors and Internal TeamsSetting Goals, Milestones, and KPIsCommon Pitfalls and How to Avoid ThemCase Study: Leading a Successful AI PilotEthics, Risk, and GovernanceBias, Transparency, and Fairness in AIRegulatory and Legal ConsiderationsCreating AI Governance StructuresHow to Ensure Responsible AI UseFuture-Proofing Your LeadershipHow AI Will Change Leadership and ManagementUpskilling for the AI AgeAI and the Future of Work: What to ExpectStaying Ahead: Trends to WatchFinal Thoughts and Next StepsRecap and Key TakeawaysNext Steps to Bring AI into Your OrganizationFinal Action PlanCourse Wrap-Up and Thank YouWho This Course Is ForBusiness leaders ready to make informed decisions about AIExecutives responsible for transformation, innovation, or strategyTeam managers who want to guide their staff through digital changeHR, finance, operations, and marketing leaders seeking AI literacyConsultants, entrepreneurs, and board members wanting AI insightTake the Lead in the Age of AIAI is no longer optional. The organizations-and leaders-who thrive will be those who embrace the technology with responsibility, clarity, and confidence.Enroll now and become the kind of leader who not only adapts to the future-but shapes it.Understand Core AI Concepts Without Technical JargonGain a clear, non-technical understanding of AI, including machine learning, natural language processing, and generative AI, and how these technologies apply to business challenges.Identify and Prioritize High-Impact AI OpportunitiesLearn how to recognize where AI can drive the most value in your organization and how to evaluate potential use cases for feasibility, ROI, and alignment with business goals.Develop an AI Strategy Aligned with Organizational GoalsBuild a practical roadmap for AI adoption-including data readiness, stakeholder alignment, and cultural transformation-tailored to your company's vision and capabilities.Lead AI Projects with Confidence and ClarityMaster the principles of leading AI initiatives, including setting KPIs, collaborating with technical and non-technical teams, and avoiding common project pitfalls.Implement Responsible AI Governance and Ethical OversightUnderstand how to address bias, ensure transparency, and build governance structures that support ethical and legally compliant AI use.Prepare for the Future of Work and AI-Driven LeadershipAnticipate how AI will reshape jobs, teams, and leadership roles-and develop the skills, mindset, and strategies needed to lead effectively in an AI-powered future. Overview
Section 1: Introduction
Lecture 1 Leading The AI Revolution
Lecture 2 Understanding AI Without the Jargon
Lecture 3 Building an AI Strategy
Lecture 4 Leading AI Projects
Lecture 5 Ethics and Governance Considerations
Lecture 6 Future-Proofing Your Leadership
Lecture 7 Real-World Business Use Cases
Lecture 8 Final Thoughts and Next Steps
Business leaders ready to make informed decisions about AI,Executives responsible for transformation, innovation, or strategy,Team managers who want to guide their staff through digital change,Consultants, entrepreneurs, and board members wanting AI insight
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Real-Time Hand Gesture & Traffic Sign Detection with Python, OpenCV & Deep Learning
What you'll learn
Learn hand gesture and traffic sign recognition for HCI, accessibility, road safety, and autonomous systems.
Set up Python with OpenCV, MediaPipe, TensorFlow for real-time gesture and sign recognition.
Explore gesture and traffic sign detection for control systems, virtual interfaces, and smart transportation.
Detect hand gestures using MediaPipe and classify signs using EfficientNet B0 in real-time.
Recognize gestures like Thumbs Up, Victory, Fist, and classify traffic signs with ML and landmarks.
Preprocess images and videos using resizing, normalization, and augmentation for better model input.
Visualize results with labels, confidence scores, and bounding boxes for easy interpretation.
Train EfficientNet B0 on traffic signs and optimize hyperparameters to improve accuracy.
Handle issues like lighting, occlusions, and low resolution for robust real-world performance.
Use gesture recognition for control, gaming, and accessibility; use sign detection for driving and safety.
Integrate both systems into real-time apps for smart interaction and decision-making.
Requirements
Basic understanding of Python programming (helpful but not mandatory).
A laptop or desktop computer with internet access[Windows OS with Minimum 4GB of RAM).
No prior knowledge of AI or Machine Learning is required-this course is beginner-friendly.
Enthusiasm to learn and build practical projects using AI and IoT tools.
Description
Welcome to the Real-Time AI Vision Systems Course: Hand Gesture & Traffic Sign Recognition with Python!In this comprehensive hands-on course, you'll master two powerful real-time AI systems: Hand Gesture Recognition using MediaPipe & OpenCV and Traffic Sign Detection using EfficientNet B0 & TensorFlow. Whether you're building gesture-controlled apps or intelligent transportation tools, this course equips you with the skills to bring AI into everyday applications.What You'll Learn - Hand Gesture Recognition:Set up your Python environment and install essential libraries like OpenCV and MediaPipe for gesture recognition tasks.Learn the fundamentals of hand gesture recognition and its applications in HCI, accessibility, gaming, and device control.Recognize gestures such as "Thumbs Down", "Victory", "Thumbs Up", "Pointing", "Fist Closed", and "Open Palm" in real-time video streams.Preprocess live video feeds for efficient gesture detection with minimal latency.Build a full gesture recognition pipeline to detect and classify hand movements frame-by-frame.Visualize recognition results with gesture labels, bounding boxes, and confidence scores.Tackle real-world challenges like lighting changes, occlusions, and gesture variation.Optimize the pipeline for smooth real-time performance and responsive interactions.Explore use cases in gesture-controlled devices, accessibility tools, gaming, and virtual interfaces.What You'll Learn - Traffic Sign Detection:Set up your Python environment with TensorFlow, OpenCV, and Matplotlib for image preprocessing and visualization.Use EfficientNet B0 for traffic sign classification, balancing speed and accuracy for real-time applications.Preprocess traffic sign images with normalization, resizing, and data augmentation techniques.Train and fine-tune the model to improve accuracy and handle imbalanced or noisy datasets.Implement real-time inference with overlays displaying traffic sign labels and meanings.Overcome practical challenges like lighting changes, occlusions, and low-resolution inputs.Deploy your model into real-time systems for driver assistance or smart transportation use cases.Apply your system to autonomous vehicles, road safety monitoring, and intelligent traffic management.By the end of this course, you'll have built two fully functional AI-powered systems: one for recognizing hand gestures and another for detecting traffic signs in real-time. You'll be ready to integrate these technologies into innovative applications that enhance interactivity, safety, and automation.Whether you're a student, professional, developer, or AI enthusiast, this step-by-step course will equip you to build impactful real-world solutions. Enroll today and start your journey into the world of AI-powered computer vision!
Who this course is for
Students looking to dive into AI and apply it to real-world problems like hand gesture recognition using MediaPipe and traffic sign detection using EfficientNet B0.nition using mediapipe library.
Working professionals aiming to upskill in AI, Machine Learning, and Python programming for image classification, real-time detection, and practical applications.
IoT and Embedded System enthusiasts who want to integrate AI into IoT solutions, including gesture control and smart transportation systems.
Autonomous vehicle and smart transportation enthusiasts interested in AI-powered traffic sign recognition and intelligent driver assistance systems.
Aspiring developers aiming to build a career in AI, machine learning, computer vision, or deep learning through hands-on training in model development and deployment. Homepage:
Intelligent Human Intrusion & Object Detection System using YOLOv7, Python & Computer Vision
What you'll learn
Learn object detection fundamentals and its applications in intrusion detection, surveillance, and real-world domains using AI and computer vision.
Set up a Python environment with essential libraries like Tkinter, OpenCV, and PyTorch for computer vision and object detection tasks.
Understand object detection concepts and how they're used in monitoring unauthorized intrusions via video streams in real-time scenarios.
Use YOLOv8 and YOLOv7-Tiny models for accurate, real-time object and human intrusion detection using lightweight and efficient algorithms.
Load and configure YOLOv8 and YOLOv7-Tiny pre-trained weights to enable real-time, high-accuracy detection of objects and intruders.
Preprocess video streams and images to integrate smoothly with YOLO models for real-time monitoring and effective object detection.
Write Python scripts to detect objects and intruders, extracting bounding boxes, class labels, and confidence scores for interpretation.
Visualize detection results by drawing bounding boxes, adding labels, and showing confidence scores on video frames for better insight.
Optimize YOLOv7-Tiny for real-time performance on devices with limited resources without compromising detection speed or accuracy.
Tackle challenges like low-light detection, occlusions, motion blur, small or overlapping objects in object and intrusion detection.
Apply AI-based intrusion detection in restricted zones, industries, homes, offices, and public places to improve safety and surveillance. Requirements
Basic understanding of Python programming (helpful but not mandatory).
A laptop or desktop computer with internet access[Windows OS with Minimum 4GB of RAM).
No prior knowledge of AI or Machine Learning is required-this course is beginner-friendly.
Enthusiasm to learn and build practical projects using AI and IoT tools. Description
Welcome to the Real-Time Intrusion & Object Detection with YOLOv8, YOLOv7-Tiny, and Python Course! In this comprehensive hands-on course, you'll learn how to build real-time human intrusion detection and object detection systems using the powerful YOLOv8 and YOLOv7-Tiny algorithms, Python, and Tkinter. This course combines the strengths of AI and computer vision to help you design efficient and interactive detection systems for various real-world applications.What You'll Learn:Set Up Your Python Development Environment: Learn to set up your development environment and install essential libraries like OpenCV, Tkinter, and PyTorch for building both intrusion and object detection systems.Utilize Pre-trained YOLOv8 & YOLOv7-Tiny Models: Master using pre-trained YOLOv8 for intrusion detection and YOLOv7-Tiny for object detection, both of which provide high accuracy even in complex environments.Preprocess Video Streams for Optimal Performance: Learn how to preprocess live video feeds and images for optimal performance with both models to ensure seamless and accurate detection.Build Interactive Tkinter GUIs: Create and implement Tkinter-based GUIs to visualize real-time detection results, displaying alerts and identified intruders or detected objects.Address Real-World Challenges: Tackle common challenges in both object and intrusion detection, such as low-light conditions, occlusions, and high-traffic environments, ensuring the accuracy and reliability of your system.Optimize for Real-Time Performance: Master techniques to ensure fast and efficient processing of live video streams for real-time monitoring in both intrusion detection and object tracking scenarios.Handle Complex Surveillance Environments: Learn how to manage detection in diverse environments, including varying lighting, camera angles, and crowded areas to ensure robust and accurate tracking results.By the End of This Course:You'll have developed a fully functional AI-powered system that detects unauthorized human activity and objects in real time, using interactive visualization through Tkinter-based GUIs. Whether you're working on security solutions for restricted areas, industrial sites, or public spaces, you will have a comprehensive understanding of deploying advanced AI models in real-world applications.This course is perfect for beginners or those with experience in computer vision and AI, and it will equip you with practical knowledge to build cutting-edge surveillance and detection systems.Enroll now and unlock the potential of YOLOv8 & YOLOv7-Tiny for impactful detection solutions! Overview
Section 1: Introduction of the Object Detection using yolov7
Lecture 1 Course Overview and Features
Section 2: Environment Setup for Python Development
Lecture 2 Installing Python
Lecture 3 VS Code Setup for Python Development
Section 3: Object Detection Project Overview
Lecture 4 Object Detection Project Overview
Section 4: Understanding Key Packages for Object Detection
Lecture 5 Understanding Key Packages for Object Detection
Section 5: Understanding the YOLOv7-tiny Model Weights
Lecture 6 Detailed Explanation of the YOLOv7-tiny.pt File
Section 6: Real-Time Object Detection with YOLOv7-tiny
Lecture 7 Implementing YOLOv7-tiny for Live Video Analysis
Section 7: Building a Tkinter GUI for Real-Time Object Detection
Lecture 8 Integrating YOLOv7-tiny with a Tkinter GUI
Section 8: Executing Real-Time Model Inference for Object Detection
Lecture 9 Performing Real-Time Object Detection with YOLOv7-tiny
Section 9: Environment Setup for Python Development
Lecture 10 Installing Python
Lecture 11 VS Code Setup for Python Development
Section 10: Launching VS Code from the Command Line
Lecture 12 Using CMD to Open VS Code
Section 11: Managing Folders and Files of the Project
Lecture 13 Understanding Folder and File Structure
Section 12: Understanding and Setting Up Required Packages
Lecture 14 Understanding Key Packages for Intrusion Detection System
Section 13: Accessing and Using Polygon Coordinates for Tracking
Lecture 15 Polygon Coordinate File Access and Parsing
Section 14: Key Variables and Their Role in YOLOv8
Lecture 16 Understanding and Customizing Key Variables in YOLOv8
Section 15: Model Inference for Intrusion Detection
Lecture 17 Model Inference Code Explanation for Intrusion Detection
Section 16: Tkinter Implementation for Real-Time Intrusion Detection
Lecture 18 Tkinter Implementation for Real-Time Intrusion Detection
Section 17: Getting Polygon Coordinates Using Roboflow for Intrusion Detection
Lecture 19 Getting Polygon Coordinates Using Roboflow
Section 18: Intrusion Detection Code Execution
Lecture 20 Intrusion Detection Code Execution
Section 19: Wrapping Up
Lecture 21 Course Wrap-Up
Students eager to learn AI with hands-on projects in intrusion and object detection using YOLOv8 and YOLOv7 pre-trained models.,Professionals seeking to upskill in AI, ML, and Python for real-world applications in security and object detection.,IoT enthusiasts looking to embed AI into smart systems and enhance IoT solutions with detection and automation features.,Aspiring developers aiming to start a career in AI, ML, or computer vision using YOLO and real-time detection models.
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It's designed for high conversions, using clear sections, benefit-driven language, and beginner-friendly tone.
What you'll learn
Build an AI-powered content system that generates captions, posts, videos, and visuals from one core idea
Use ChatGPT for writing captions across formats: educational, viral, emotional, storytelling, and promotional
Design fast and professional visuals using Canva AI and Midjourney
Turn text into short, engaging videos with AI avatars, voices, and effects
Create product copy, landing pages, and branded messaging using AI
Adapt your content for TikTok, Facebook, Instagram, and LinkedIn
Build a unique brand voice using AI tools
Use Notion templates and prompt libraries to manage 30-day content calendars
Produce more content in less time-without creative burnout
Requirements
No prior experience with AI tools is required.
Basic digital skills.
Access to a computer or tablet with internet connection.
Free accounts on selected AI tools.
A willingness to learn and experiment.
Description
This course is designed to help content creators work faster, create better visuals, and publish more consistently using the power of AI. Whether you're a freelancer, a KOL, an online business owner, or just starting out, this course gives you the tools and workflow to act as a one-person content agency.From writing captions and blog posts, to designing stunning visuals, producing short videos, and managing your social media calendar-everything is powered by real AI tools like ChatGPT, Canva AI, CapCut, Midjourney, and HeyGen.Each lesson is 100% practical. You'll apply what you learn instantly, turning one idea into multiple content formats and building a system that runs like a team-without hiring one.By the end of the course, you'll save up to 80% of your content creation time and double or triple your posting frequency-without compromising quality.You'll also get access to templates, prompt libraries, and a step-by-step workflow that helps you stay creative and consistent across all platforms. No prior experience is needed-just a willingness to learn and apply. This course empowers you to master the tools that top creators use every day, making content creation fun, fast, and scalable. Whether you're building a brand or growing a business, this course will get you there.
Who this course is for
Content creators, influencers, freelancers, and marketers
Online sellers who want to create content without outsourcing
Beginners who want to learn structured, modern content creation with AI
Anyone who wants to streamline and scale content creation using smart tools Homepage:
Securing cloud resources can be overwhelming for beginners, especially when navigating tools like Microsoft Defender for Cloud and understanding compliance requirements. In this course, Azure Security Fundamentals, you'll learn to enhance the security and compliance of Azure environments. First, you'll explore how to leverage Microsoft Defender for Cloud to monitor and protect your resources from threats. Next, you'll discover how to configure encryption for data at rest and in transit to safeguard sensitive information. Finally, you'll learn how to ensure regulatory compliance using Azure tools like Compliance Manager and Azure Policy. When you're finished with this course, you'll have the skills and knowledge of Azure security needed to protect your cloud resources and meet compliance standards with confidence. Homepage:
Advance your SOC skills with real-time detection, automated response, and forensic techniques for modern cyber defense.
What you'll learn
How to integrate secure coding practices into the Software Development Life Cycle (SDLC) using models like SEI-CMMI.
How to apply Kali Linux and Bash scripting to automate risk assessments, implement defenses, and support incident response.
Techniques to analyze and defend against mobile device threats, including OWASP mobile risks and iOS/Android hacking methods.
How to build and manage a Blue Team, focusing on recruitment, soft skills, leadership, and digital forensic investigation.
Requirements
Familiarity with networking, Linux basics, and common cybersecurity tools.
Prior exposure to threat detection, incident response, or risk management is helpful but not required.
Description
Welcome to Blue Team - Domain 5: Security Operations & Incident Response, the final domain in your Certcop Blue Team journey. This course focuses on bridging cybersecurity operations with secure software development, risk mitigation, mobile security, and effective Blue Team management.You'll begin with a deep understanding of the Software Development Life Cycle (SDLC), including secure coding practices, data warehousing, and maturity models like SEI-CMMI. From there, you'll gain hands-on skills in Kali Linux and Bash scripting, applying scripts to assess vulnerabilities, automate risk mitigation, and enhance network defense strategies.Next, we dive into the fast-evolving world of mobile device hacking, where you'll explore the OWASP Mobile Top 10, mobile attack vectors, Android/iOS vulnerabilities, and jailbreaking techniques-all from a defender's perspective.You'll also learn how to recruit, structure, and manage a successful Blue Team, identifying critical technical and soft skills, balancing in-house vs. outsourced talent, and fostering leadership and collaboration.Finally, we revisit Digital Forensics-including evidence collection, forensic tools, and investigative processes-ensuring you're equipped to respond and investigate effectively after an incident.Whether you're a current SOC analyst, Blue Team lead, or cybersecurity student preparing for Certcop certification, this course gives you the advanced knowledge and practical insights needed to defend modern digital environments with confidence.
Who this course is for
SOC analysts, Blue Team members, and security engineers looking to expand into secure development, mobile defense, and scripting.
IT professionals and system administrators aiming to transition into cybersecurity or strengthen their incident response skills. Homepage:
Building insightful dashboards often requires moving beyond basic charts to more advanced, customized visualizations that highlight trends, comparisons, and patterns effectively.
In this course, Build Advanced Charts in Tableau Desktop, you'll gain the ability to create expressive, interactive, and data-rich visualizations that bring clarity to your analysis.
First, you'll explore how to build charts for analyzing data distributions and relationships, such as histograms, box plots, and scatter plots with context-enhancing elements like trend lines and mark adjustments.
Next, you'll discover how to construct multi-dimensional and multi-metric charts - such as dual-axis views, bullet graphs, and combo charts - that present layered insights in a single view.
Finally, you'll learn how to create advanced categorical visualizations and customize charts with logic, parameters, and interactivity, including dynamic reference lines, calculated annotations, and contextual drill-downs using Viz in Tooltip.
When you're finished with this course, you'll have the skills and knowledge of advanced Tableau Desktop visualizations needed to build impactful, interactive charts that convey deeper data stories. Homepage:
What you'll learn
Understand Redux Internals: Grasp the core principles of Redux (store, actions, reducers, dispatch, subscriptions) by building them step-by-step.
Build a State Management Library: Create a lightweight, functional Redux-like library from scratch using vanilla JavaScript.
Implement Middleware: Develop custom middleware (e.g., logging, async thunks) to extend the library's functionality.
Combine Reducers: Learn to modularize state management by combining multiple reducers into a single state tree.
Requirements
Basic JavaScript Knowledge
Basic Redux Knowledge
Description
Unlock the power of state management by building your own Redux core library from the ground up! In this hands-on course, you'll dive deep into the internals of Redux, one of the most popular state management libraries for JavaScript applications. Designed for intermediate JavaScript developers, this course takes you step-by-step through creating a lightweight, fully functional Redux-like library, giving you a profound understanding of how state management works under the hood.What You'll LearnMaster Redux Fundamentals: Understand core concepts like the store, actions, reducers, dispatch, and subscriptions by implementing them yourself.Build a Custom Library: Create a minimal, production-ready state management library in vanilla JavaScript, complete with middleware and combined reducers.Enhance with Middleware: Add powerful features like logging and async action handling to your library.Modularize State: Learn to manage complex state with combineReducers for scalable applications.Who This Course Is ForAll levels of JavaScript developers who want to deeply understand state management.React developers looking to master Redux's internals for better debugging and customization.Aspiring library creators curious about building their own tools.Developers preparing for technical interviews where state management questions are common.Why Take This Course?Unlike typical Redux courses that focus on using the library, this course empowers you to build it, demystifying its magic. By creating your own state management solution, you'll gain confidence in handling complex app logic, debugging Redux apps, and even designing custom libraries.Enroll now and start building your own Redux core library today! Transform your JavaScript skills and take control of state like never before.Prerequisites: Basic JavaScript (ES6+) knowledge.
Who this course is for
Beginner, Intermediate or Advanced JavaScript Developers Homepage:
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