Pinal Dave | Duration: 2:28 h | Video: H264 1024x768 | Audio: AAC 48 kHz 2ch | 269 MB | Language: English
Document databases like MongoDB are built around JSON-like documents and provide natural flexibility for developers. In this course, you'll explore the basics of and CRUD operation with the help of various easy to understand demonstrations.
Every single day we come across lots of data and every bit of data needs a place to be stored.
In this course, Foundations of Document Databases with MongoDB, you'll learn foundational knowledge in MongoDB, a general-purpose, document-based, distributed database built for modern application developers and for the cloud era.
• First, you'll explore what a document database is and how it differs from relational SQL.
• Next, you'll discover why we should use MongoDB.
• Finally, you'll get an idea of how to get started with MongoDB, efficiently.
By the end of this course, you will be confident to get started with your very first MongoDB setup. I will provide all the necessary information and code samples so you can get started immediately. Homepage:
Learn how to setup and use all of Flipper Zero's modules
What you'll learn
Flipper Zero Setup
Flipper Zero Modules
Flipper Zero NFC
Flipper Zero Sub-GHz
Flipper Zero WiFi Requirements
Basic Understanding of Computers Description
Unlock the full potential of your Flipper Zero with this comprehensive course designed to take you from a beginner to an expert user. Whether you're just unboxing your Flipper Zero or looking to delve deep into its advanced functionalities, this course has you covered.In this course, you'll start by setting up your Flipper Zero step-by-step, ensuring you understand the basics and initial configuration. We'll guide you through essential concepts, from navigating the interface to exploring all built-in capabilities. Moving forward, you will learn how to effectively use your Flipper Zero across various scenarios, including RFID, NFC, and infrared hacking.Discover how to extend the power of your device with additional hardware modules, custom scripts, and community firmware to unlock features not available out of the box. Gain practical knowledge in using the Flipper Zero for real-world applications, including penetration testing, wireless signal capture, and automation.Each module of the course includes hands-on demonstrations, tips, and exercises to solidify your skills. By the end of this course, you'll be fully equipped to maximize your Flipper Zero's capabilities and creatively apply it in cybersecurity, tinkering, or fun DIY projects.Join now and become proficient with the ultimate hacker's Swiss Army knife! Overview
Section 1: Introduction
Lecture 1 Introduction
Section 2: Flipper Zero WiFi Evil Portal
Lecture 2 Evil Portal[ESP32]
Section 3: Flipper Zero WiFi DeAuth
Lecture 3 Flipper Zero WiFi[ESP32] DeAuth
Section 4: Flipper Zero Bad USB
Lecture 4 Flipper Zero Bad USB
Lecture 5 Flipper Zero Bad USB Reverse Shell
Section 5: Flipper Zero Bluetooth
Lecture 6 Flipper Zero Bluetooth Spam
Section 6: Flipper Zero RFID and NFC Reader
Lecture 7 Card Reading
Keen to use Flipper Zero to its Full Potential,Learn WiFi Security,Learn Physical Security
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Domain-Driven Design (or DDD for short) is one of the most popular approaches to software development, and that's for a very good reason. As described excellently by Martin Fowler, it "is an approach to software development that centres the development on programming a domain model with a rich understanding of the processes and rules of a domain". Building software that way, especially when dealing with a complex domain, leads to aligned business people and developers and better software that does precisely what the business needs. Ever since its formal definition by Eric Evans all the way back in 2003, developers have used it to create software based on a well-developed model of design. In this Getting Started course, Amichai Mantinband will break down Domain-Driven Design into a very easily digestible concept using his real-world experience. Homepage:
Learn the secrets to writing a bestselling novel with expert techniques in storytelling, character development, and more
What you'll learn
Analyze current market trends to identify profitable fiction genres and subgenres.
Develop memorable protagonists and multi-dimensional antagonists with engaging character arcs.
Structure a gripping narrative with effective plot twists and intricate subplots.
Write natural, dynamic conversations that convey character voice and story exposition.
Create vivid settings that enhance atmosphere and become integral to the story.
Craft attention-grabbing opening lines and intriguing synopses to captivate readers.
Balance likeability and flaws in characters to ensure relatability and depth.
Resolve conflicts with satisfying endings that leave lasting impressions on readers.
Incorporate research to create authentic locations and immersive story environments.
Establish a professional author brand to effectively promote your writing online.
Build tension in the opening chapters to immediately engage and hook readers.
Network within the writing community to gain insights and opportunities for growth. Requirements
No prior experience in writing or publishing is required, making this course perfect for beginners and aspiring authors alike.
Bringing your own story ideas or creative concepts is helpful but not mandatory.
All you need is a passion for storytelling and a desire to improve your writing skills.
Personalized support is available throughout the course to address your questions and provide expert guidance.
You can access the novel-writing course on any internet-connected device, enabling you to learn at your own pace and convenience. Description
Novel writing is an art that blends creativity, technique, and an understanding of what captivates readers. To craft a bestselling novel, you need more than just an idea-you need compelling characters, intricate plots, engaging dialogue, and a story that resonates with your audience. Successful authors master the delicate balance of storytelling and market awareness, creating works that not only entertain but also leave a lasting impact. Whether you dream of penning a literary classic or dominating the commercial fiction charts, understanding what makes a novel truly stand out is the first step.Our course equips you with the tools and techniques to turn your ideas into masterpieces. It explores the art and craft of storytelling, guiding you through every step of the novel-writing process. You'll learn how to analyse market trends, develop unforgettable characters, structure gripping plots, and create authentic settings. This course goes beyond storytelling to help you build your author brand and effectively market your work. By honing these essential skills, you'll have the confidence and tools to navigate the path to becoming a published and successful author.This course is tailored to those passionate about storytelling and determined to bring their creative vision to life. With a step-by-step approach, practical examples, and strategies for market success, it's perfect for aspiring authors who want to make their mark. Start your journey towards becoming a bestselling author today-enrol now and let your stories inspire the world!By the end of this How to Write a Bestselling Novel, you'll be equipped to:Craft compelling characters and intricate plots that captivate readers from start to finish.Develop authentic settings and write vivid descriptions to immerse your audience.Create attention-grabbing opening lines and irresistible hooks for a powerful start.Enhance your storytelling with natural dialogue and well-structured narratives.Build a professional author brand and leverage marketing strategies to promote your work.Curriculum of How to Write a Bestselling Novel Skills Bootcamp:Module 1: Understanding the MarketAnalyzing Current Trends in FictionIdentifying Popular Genres and SubgenresRecognizing Reader PreferencesEvaluating Market Gaps and OpportunitiesModule 2: Crafting Compelling CharactersDeveloping Memorable ProtagonistsCreating Multi-dimensional AntagonistsEstablishing Engaging Supporting CharactersBalancing Likeability and Flaws in CharactersModule 3: Building a Captivating PlotStructuring a Gripping NarrativeImplementing Effective Plot TwistsDeveloping Subplots for ComplexityResolving Conflict with Satisfying EndingsModule 4: Mastering DialogueWriting Natural and Dynamic ConversationsConveying Character Voice through DialogueBalancing Exposition and ConversationCrafting Memorable Lines and QuotesModule 5: Setting the SceneCreating Vivid and Evocative DescriptionsIncorporating Setting as a CharacterBalancing Atmosphere and ToneResearching and Authenticating LocationsModule 6: Crafting an Irresistible HookDesigning Attention-Grabbing Opening LinesBuilding Tension in the First ChaptersCreating Intriguing Queries and SynopsesEngaging Readers with Compelling PremisesModule 7: Building Your Author BrandEstablishing an Authorial Online PresenceUtilizing Social Media for Book PromotionNetworking within the Writing CommunityDesigning Professional Author Websites Overview
Section 1: Understanding the Market
Lecture 1 Introduction
Lecture 2 Analyzing Current Trends in Fiction
Lecture 3 Identifying Popular Genres and Subgenres
Lecture 4 Recognizing Reader Preferences
Lecture 5 Evaluating Market Gaps and Opportunities
Section 2: Crafting Compelling Characters
Lecture 6 Introduction
Lecture 7 Developing Memorable Protagonists
Lecture 8 Creating Multi-dimensional Antagonists
Lecture 9 Establishing Engaging Supporting Characters
Lecture 10 Balancing Likeability and Flaws in Characters
Section 3: Building a Captivating Plot
Lecture 11 Introduction
Lecture 12 Structuring a Gripping Narrative
Lecture 13 Implementing Effective Plot Twists
Lecture 14 Developing Subplots for Complexity
Lecture 15 Resolving Conflict with Satisfying Endings
Section 4: Mastering Dialogue
Lecture 16 Introduction
Lecture 17 Writing Natural and Dynamic Conversations
Lecture 18 Conveying Character Voice through Dialogue
Lecture 19 Balancing Exposition and Conversation
Lecture 20 Crafting Memorable Lines and Quotes
Section 5: Setting the Scene
Lecture 21 Introduction
Lecture 22 Creating Vivid and Evocative Descriptions
Lecture 23 Incorporating Setting as a Character
Lecture 24 Balancing Atmosphere and Tone
Lecture 25 Researching and Authenticating Locations
Section 6: Crafting an Irresistible Hook
Lecture 26 Introduction
Lecture 27 Designing Attention-Grabbing Opening Lines
Lecture 28 Building Tension in the First Chapters
Lecture 29 Creating Intriguing Queries and Synopses
Lecture 30 Engaging Readers with Compelling Premises
Section 7: Building Your Author Brand
Lecture 31 Introduction
Lecture 32 Establishing an Authorial Online Presence
Lecture 33 Utilizing Social Media for Book Promotion
Lecture 34 Networking within the Writing Community
Lecture 35 Designing Professional Author Websites
Aspiring authors who want to write and publish their first novel.,Experienced writers looking to refine their storytelling techniques and craft.,Creative individuals seeking to turn their story ideas into compelling narratives.,Professionals aiming to break into the literary world with a bestselling novel.,Writers interested in exploring market trends and reader preferences to enhance their appeal.,Anyone passionate about storytelling and eager to improve their writing skills.,Individuals who want to learn how to build a strong author brand and promote their work effectively.
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Transform Your Workplace with Inclusive Leadership: Master Diversity, Equity, and Bias-Free Decision-Making
What you'll learn
Understand the principles of inclusive leadership and its impact on workplace success.
Identify and address unconscious bias in hiring, promotions, and decision-making.
Foster diversity, equity, and inclusion (DEI) to create a positive company culture.
Develop equitable leadership practices to ensure fairness and transparency.
Build psychological safety to encourage open communication and trust.
Measure and sustain DEI initiatives for long-term success. Requirements
No prior experience is needed-just a passion for creating an inclusive and thriving workplace. Description
In today's rapidly evolving workplace, fostering diversity, equity, and inclusion is no longer optional-it's essential. "Inclusive Leadership: Mastering Diversity & Equity in Action" is the definitive course for HR professionals and organizational leaders aiming to drive meaningful, lasting change. This immersive program equips you with practical tools, actionable strategies, and the mindset to lead inclusively in an increasingly diverse world.Discover the core principles of inclusive leadership and learn how to cultivate a workplace culture that values and respects every individual. This course offers an in-depth exploration of key topics, including unconscious bias, equity in leadership practices, and building psychological safety within teams. Through interactive components such as quizzes, role-playing exercises, and scenario-based learning, you'll transform theoretical knowledge into impactful actions.Key learning outcomes include:Understanding Inclusive Leadership: Define what it means to lead inclusively and uncover the traits of successful inclusive leaders.Mastering Diversity, Equity, and Inclusion (DEI): Explore the interconnectedness of DEI and organizational culture, and how inclusive leadership drives engagement, innovation, and trust.Identifying and Addressing Bias: Learn to recognize unconscious bias and implement strategies to mitigate its impact on recruitment, promotions, and decision-making processes.Promoting Equity in Leadership: Develop fair and transparent practices to ensure equitable opportunities for all.Building Psychological Safety: Foster an environment where team members feel safe, respected, and empowered to share ideas and concerns.Sustaining Change: Measure the success of your DEI initiatives and ensure continuous improvement through metrics, tools, and sustainable practices.What You'll Get:Interactive quizzes to test your knowledge and reinforce learning.Practical resources, including a Bias Mitigation Toolkit, Inclusive Leadership Checklist, and Development Plan.Real-world case studies and examples that bring concepts to life.A downloadable action plan to guide your inclusive leadership journey.Who Should Enroll?This course is perfect for HR professionals, team leaders, executives, and anyone passionate about creating an inclusive workplace. Whether you're looking to drive cultural transformation or refine your leadership style, this course provides the essential framework to achieve your goals.Why Enroll Now?The future of leadership is inclusive. Gain the competitive edge to lead with empathy, adaptability, and purpose. Equip yourself with the tools to foster a thriving, equitable workplace where everyone can succeed. Enroll today and take the first step toward becoming an impactful, inclusive leader!Start leading inclusively, start driving change. Overview
Section 1: Foundations of Inclusive Leadership
Lecture 1 What is Inclusive Leadership?
Lecture 2 The Importance of Diversity, Equity, and Inclusion (DEI)
Section 2: Overcoming Bias and Promoting Equity in Leadership
Lecture 3 Identifying and Addressing Bias in the Workplace
Lecture 4 Promoting Equity in Leadership Practices
Section 3: Leading Inclusively: Key Leadership Behaviors
Lecture 5 Key Behaviors of Inclusive Leaders
Lecture 6 Building Psychological Safety in Teams
Section 4: Measuring Success and Sustaining Change
Lecture 7 Measuring the Effectiveness of Inclusive Leadership
Lecture 8 Sustaining Inclusive Leadership Practices
HR professionals aiming to drive impactful diversity and equity initiatives.,Team leaders and managers looking to enhance collaboration and team dynamics.,Executives focused on building a more inclusive and innovative organizational culture.,Anyone passionate about fostering equity, inclusion, and belonging in the workplace.
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Comprehensive Guide to Understanding, Operating, and Maintaining Well Control Systems in the Oil & Gas Industry
What you'll learn
Learn the fundamentals of well control and its importance in drilling operations.
Identify key components of well control equipment like BOPs and choke manifolds.
Understand the functions and operations of well control systems
Master maintenance and inspection procedures for well control equipment.
Explore international safety standards and regulatory compliance.
Gain skills in troubleshooting and responding to equipment failures
Understand the integration of well control equipment in drilling operations. Requirements
Interest in oil and gas safety standards and procedures
Basic understanding of drilling operations and petroleum engineering concepts.
Familiarity with industry terminology related to well control and equipment.
Access to a computer or device to view course materials.
No prior experience with well control equipment is required, but helpful for advanced topics. Description
Are you ready to take your knowledge of well control equipment to the next level? This course provides an in-depth understanding of the tools and systems that are critical to maintaining safety and efficiency in the high-stakes world of oil and gas drilling operations. Well control is one of the most important aspects of the drilling process, designed to prevent blowouts and ensure the safety of personnel, the environment, and assets. In this course, you will dive into the fundamentals of well control equipment, exploring the function, operation, and maintenance of key components such as blowout preventers (BOPs), choke manifolds, and diverter systems. Through a structured and comprehensive curriculum, this course is suitable for both industry newcomers and seasoned professionals looking to refresh or deepen their expertise. You'll not only understand how these systems work but also gain practical insights into troubleshooting and responding to emergencies. We will also cover international safety standards, regulatory requirements, and the integration of well control equipment into drilling operations, giving you a holistic perspective on this critical field. **What you'll learn**: - The fundamental principles of well control and its importance in drilling operations. - The design, components, and functions of well control equipment like BOPs and choke manifolds. - Step-by-step guidance on operating and maintaining well control systems. - Industry best practices for inspection and preventive maintenance. - How to troubleshoot equipment malfunctions and manage emergency situations effectively. - An overview of global safety standards and compliance frameworks. - Integration of well control equipment into overall drilling operations. **Who is this course for?** This course is tailored for a wide range of learners, including: - Entry-level drilling engineers, petroleum engineers, and technicians. - Oil and gas safety and compliance professionals. - Students pursuing degrees in petroleum engineering or drilling technology. - Industry professionals preparing for certification exams in well control. - Anyone with an interest in oilfield safety and operational excellence. **Why enroll in this course?** - Gain a comprehensive understanding of well control systems critical to the oil and gas industry. - Learn from real-world examples and case studies designed to bridge theory and practice. - Develop skills to enhance safety, efficiency, and compliance in drilling operations. - Prepare for industry certifications and advance your career. - Study at your own pace with lifetime access to course materials and updates. Join today and gain the skills to ensure safer, more efficient drilling operations while enhancing your career prospects in the dynamic oil and gas sector! Overview
Section 1: Introduction
Lecture 1 Introduction
Section 2: Fundamentals of Well Control Equipment
Lecture 2 Fundamentals of Well Control Equipment
Section 3: Blowout Preventers (BOPs)
Lecture 3 Blowout Preventers (BOPs)
Section 4: Choke Manifolds and Diverter Systems
Lecture 4 Choke Manifolds and Diverter Systems
Section 5: Maintenance and Inspection
Lecture 5 Maintenance and Inspection
Section 6: Safety Standards and Compliance
Lecture 6 Safety Standards and Compliance
Section 7: Real-World Applications
Lecture 7 Real-World Applications
Section 8: Certification Preparation
Lecture 8 Certification Preparation
Section 9: Conclusion
Lecture 9 Conclusion
Entry-level drilling engineers and petroleum engineers.,Well control technicians and equipment operators.,Safety and compliance professionals in the oil and gas industry.,Students pursuing studies in petroleum engineering or drilling technology.,Professionals seeking to enhance their knowledge of well control systems.,Individuals preparing for certification exams in well control,Anyone interested in oilfield safety and operational excellence
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Kodeco - Deploying Android Apps Using GitHub Actions
Kodeco - Deploying Android Apps Using GitHub Actions
Subhrajyoti Sen | Duration: 0:36 h | Video: H264 1920x1080 | Audio: AAC 48 kHz 2ch | 185 MB | Language: English
Learn how to automate the process of generating signed builds, and releasing them to Firebase App Distribution and the Google Play Store.
This course is for Android developers who want to automate the release of their apps to Firebase App Distribution and the Google Play Store. Covered concepts
• Creating complex GitHub workflows
• Running different types of tests from CLI
• Signing a build from CLI
• Uploading build artifacts to GitHub
• Distributing APK to testers using Firebase App • Distribution
• Uploading builds to the Google Play Store Homepage:
Kodeco - Jetpack Compose Tutorial for Android: Getting Started
Kodeco - Jetpack Compose Tutorial for Android: Getting Started
Joey deVilla | Duration: 0:50 h | Video: H264 1920x1080 | Audio: AAC 48 kHz 2ch | 514 MB | Language: English
In this Jetpack Compose tutorial, you'll learn to use the new declarative UI framework being developed by the Android team by creating a cookbook app.
Released in July 2021, Jetpack Compose is a UI toolkit that updates the process of building Android apps. Instead of XML, you use Kotlin code to declaratively specify how the UI should look and behave in various states. You don't have to worry how the UI moves among those states - Jetpack Compose takes care of that. You'll find it familiar if you're acquainted with declarative web frameworks such as React, Angular or Vue.
The Jetpack Compose approach is a significant departure from Android's original XML UI toolkit, now called Views. Views was modeled after old desktop UI frameworks and dates to Android's beginning. In Views, you use a mechanism such as findViewById() or view binding to connect UI elements to code. This imperative approach is simple but requires defining how the program moves among states and how the UI should look and behave in those states.
Jetpack Compose is built with Kotlin, and it takes advantage of the features and design philosophy of Kotlin language. It's designed for use in applications written in Kotlin. With Jetpack Compose, you no longer have to context-switch to XML when designing your app's UI; you do everything in Kotlin.
In this tutorial, you'll build two Jetpack Compose apps
• A simple test run app, which you'll build from scratch, starting with File → New.
• A more complex cookbook app that will display a list of recipe cards containing images and text. You'll build this using a starter project. Homepage:
Unlock the power of Machine Learning! Learn supervised, unsupervised and reinforcement learning with hands-on examples
What you'll learn
Supervised Machine Learning Algorithms and examples
Unsupervised Machine Learning Algorithms and examples
Reinforcement Algorithms and examples Requirements
Basic understanding of Python Programming Language Description
Are you curious about Machine Learning but have no prior experience? This course is perfect for you! Designed specifically for beginners, we break down the complexities of Machine Learning into simple, easy-to-understand concepts.Through real-world examples and practical exercises, you'll explore the foundations of supervised learning, unsupervised learning, and reinforcement learning. Whether you're a student, a professional looking to upskill, or simply a tech enthusiast, this course will provide you with the skills to kickstart your Machine Learning journey.Learn how to perform Exploratory Data Analysis with Python - Pandas, Seaborn, Matplotlib etc. after performing EDA learn how to apply ML algorithms on the datasets, create models and evaluate them.Supervised Learning:Understand how algorithms learn from labeled data to make predictions.Explore linear regression, logistic regression, decision trees, and more.Hands-on example: Predicting house prices, Titanic Survival prediction, etc..Unsupervised Learning:Learn to uncover hidden patterns in data without predefined labels.Topics include clustering.Hands-on example: Customer segmentation for marketing.Reinforcement Learning:Discover how agents learn to make decisions through rewards and penalties.Key concepts: Q-learning.Hands-on example.Key FeaturesBeginner-friendly, no ML knowledge required.Step by step tutorials on installing required IDEs and libraries.Step-by-step coding demonstrations in Python.Downloadable resources and cheat sheets for quick reference. Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 What is Machine Learning - Theory
Lecture 3 Supervised Machine Learning - Classification - Theory
Lecture 4 Regression in Machine Learning - Theory and Maths
Lecture 5 What is Unsupervised Machine Learning - Theory
Lecture 6 Reinforcement Machine Learning - Theory
Section 2: IDE Installation and Usage
Lecture 7 How to install Python with System Environmental Variables for Data Science
Lecture 8 How Install Anaconda Navigator for Data Science and use it
Lecture 9 How to install Jupyter Notebook in computer for Data Analytics and Machine Learn
Lecture 10 How to use Google Colab for Data Analysis and Machine Learning with Python
Section 3: Exploratory Data Analysis with Example
Lecture 11 Exploratory Data Analysis on Titanic - Part 1 - Univariate Analysis
Lecture 12 Exploratory Data Analysis on Titanic - Part 2- Biivariate Analysis
Section 4: Regression Examples Using Python
Lecture 13 Linear Regression on One Variable Example
Lecture 14 Multiple Linear Regression Example
Lecture 15 What is Logistic Regression in Machine Learning - theory
Lecture 16 Logistic Regression on Study Hours vs Pass Fail Data
Section 5: Support Vector Machine Theory and Classification Example
Lecture 17 Support Vector Machine Algorithm - Theory
Lecture 18 Support Vector Machine Algorithm IRIS Data Classification using Python
Section 6: Random Forest Algorithm
Lecture 19 Random Forest Algorithm - Theory
Lecture 20 Random Forest Algorithm Example Using Python
Section 7: Decision Tree Algorithm
Lecture 21 Decision Tree Algorithm Theory
Lecture 22 Decision Tree Algorithm implementation with Python on Titanic Dataset
Section 8: Unsupervised Machine Learning - Example
Lecture 23 K Means Clustering Algorithm Part 1 - Theory ( Unsupervised)
Lecture 24 K means clustering algorithm example using Python - Part 2
Section 9: Q Learning Algorithm - Reinforcement Learning
Lecture 25 What is Q Learning Algorithm in Reinforcement Learning - Theory
Lecture 26 Q Learning Using Python Gym Module - Part 1
Lecture 27 Solving Problem Without Reinforcement Learning
Lecture 28 Applying Q Learning on Taxi V3 Environment - Using Python
Beginner Python Developers Curious about Machine Learning
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Transform Marketing Campaigns with Data-Driven Machine Learning Insights
What you'll learn
How to Build Machine Learning Models for Google Ads Campaign Management
Case Study of 360 degree Customer Marketing and Machine Learning to Boost Sales
Case Study for Google Ads Campaign Management
Case Study for Google Ads Campaign Optimization
Case Study for Google Ads Campaign Selection - Facebook Ads, Google Ads
Case Study for Google Ads Campaign Trends Analysis and Compare Benchmarks Ads
Analyze campaign metrics: Interpret ad spends, keyword performance, and conversions using data visualizations
Predict campaign outcomes: Build ML models to forecast campaign performance and impressions
Apply ML algorithms: Use Random Forest and Gradient Boosting for campaign optimization
Perform cohort analysis: Segment and retain customers with marketing cohort and RFM techniques
Optimize revenue: Compare campaigns to maximize ROI and refine budget allocations
Explain model results: Visualize and interpret trends and outcomes of campaign predictions
Boost profits: Create profit models using SMOTE, cost analysis, and machine learning
Identify campaign trends: Leverage historical data to guide future ad strategies
Create data pipelines: Preprocess, engineer features, and scale datasets for ML models.
Build propensity models: Predict purchase likelihood for targeted marketing efforts Requirements
Basic Knowledge of Python
Fundamentals of Machine Learning Description
In the age of data-driven marketing, campaigns thrive on insights and intelligent optimization. This course, Machine Learning for Campaign Management, is designed to empower marketers, data analysts, and aspiring data scientists with the tools and techniques to transform marketing campaigns using machine learning. From campaign trend analysis to revenue optimization, this comprehensive course covers every facet of campaign management.Course Highlights:1. Introduction: Understand your campaign's landscape with an in-depth analysis of Google Ad spends, top-performing keywords, and campaign trends. Learn how to visualize campaign spend results effectively.2. Campaign Prediction Using Machine Learning: Discover the power of predictive models. Learn how to preprocess datasets, build ensemble models, and execute campaign pipelines to anticipate campaign performance and optimize conversion rates.3. Campaign Trend Analysis: Identify and analyze emerging campaign trends. Gain hands-on experience building and visualizing trend models to make informed decisions.4. Campaign Comparison - Revenue Optimization: Master comparative analysis techniques to forecast budget vs. conversion rates and visualize benchmarks to optimize revenue across multiple campaigns.5. Campaign Impression Prediction: Dive deep into data pipelines and build machine learning models using Random Forest and Gradient Boosting to predict impressions for platforms like Instagram, Google, and Facebook.6. Click Prediction Using Random Forest Models: Leverage Random Forest models to predict click rates. Learn to build and execute model pipelines, scale datasets, and deliver actionable insights.7. Marketing Cohort Analysis: Explore cohort analysis to understand customer retention and segmentation. Use advanced techniques like K-Means clustering and RFM (Recency, Frequency, Monetary) scoring to visualize and interpret marketing data.8. Profit Booster Model: Build profit-centric models that incorporate logistic regression, XGBoost, and profit estimation equations. Learn to use SMOTE for handling imbalanced datasets and develop profit curves for enhanced decision-making.9. Propensity Model for Product Purchase: Build propensity models to predict customer purchase behavior and develop targeted marketing strategies.This course blends theoretical knowledge with practical implementations, ensuring that you gain hands-on experience in campaign prediction, optimization, and analysis. By the end of this course, you'll be equipped with the expertise to design data-driven marketing campaigns that achieve maximum profitability and efficiency.Enroll now to transform your approach to campaign management with the power of Machine Learning! Overview
Section 1: Introduction
Lecture 1 Overview of Company's Google Ad Spends
Lecture 2 Overview of Company's Google Ad Spends Continued
Lecture 3 Analysis of the Trend Campaigns
Lecture 4 Plot Chart for Top Keywords Campaigns
Lecture 5 Plot Chart for Top Ad Spends on Campaigns
Lecture 6 Visualize Campaign Ad Spend Results
Section 2: Campaign Prediction using Machine Learning
Lecture 7 Campaign Prediction Overview
Lecture 8 Why Perform Campaign Optimization
Lecture 9 Overview of Campaign Conversion Prediction
Lecture 10 Import Datasets
Lecture 11 Perform Data Proceprocessing
Lecture 12 Scale the Dataset
Lecture 13 Build Ensemble Model Prediction
Lecture 14 Execute Campaign Model Pipeline
Lecture 15 Build Campaign Performance
Lecture 16 Run the AI Model
Lecture 17 Campaign Performance Part 1
Lecture 18 Campiagn Performance Results Part 2
Lecture 19 Campaign Performance Results Part 3
Lecture 20 Campaign Performance Results Part 4
Section 3: Campaign Trend Analysis
Lecture 21 Campaign Trends Overview
Lecture 22 Build Campaign Trends
Lecture 23 Visualize Campaign Trends
Section 4: Campaigns Comparison - Revenue Optimization
Lecture 24 Overview of Campaign Comparison
Lecture 25 Revenue Optimization for Campaigns
Lecture 26 Budget Vs Conversion Forecasting Part 1
Lecture 27 Budget Vs Conversion Forecasting Part 2
Lecture 28 Budget Vs Conversion Forecasting Part 3
Lecture 29 Campaign Management
Lecture 30 Campaign Management - Visualize Benchmark Vs Campaigns
Section 5: Campaign Impression Prediction
Lecture 31 Import and Visualize Dataset
Lecture 32 Visualize Correlation between dependent and independent variables
Lecture 33 Build Data Pipeline - drop columns from the dataset
Lecture 34 Build Data Pipeline - Create Other buckets
Lecture 35 Build Data Pipeline - One Hot Encoding
Lecture 36 Build Data Pipeline Continued
Lecture 37 Split Pipeline
Lecture 38 Build ML Model - Random Forest
Lecture 39 Build ML Model - Execute and Review Results
Lecture 40 Save the ML Model - create pickle file
Lecture 41 Print Prediction Results
Lecture 42 Linear Vs Random Forest model results
Lecture 43 Gradient Boosting Model
Lecture 44 Gradient Boosting Model Continued
Lecture 45 Make Predictions for Instagram, Google, FaceBook Ads
Section 6: Click Prediction using Random Forest Machine Learning Model
Lecture 46 Overview of the Click Prediction Model
Lecture 47 Build ML Model Data Pipeline
Lecture 48 Train Test Split the dataset
Lecture 49 Scale the dataset
Lecture 50 Scale the dataset Continued
Lecture 51 Build Model Pipeline
Lecture 52 Build Model Pipeline Continued Part 1
Lecture 53 Build Model Pipeline Continued Part 2
Lecture 54 Execute Random Forest Regressor Model
Lecture 55 Create Model Results
Lecture 56 Test Prediction Results
Section 7: Marketing Cohort Analysis
Lecture 57 Overview of Marketing Cohort Analysis
Lecture 58 What is Cohort Analysis?
Lecture 59 Clean Dataset
Lecture 60 Import Dataset
Lecture 61 Visualize Data
Lecture 62 Remove Outliers
Lecture 63 Kde Plot for Distribution of Unit Price
Lecture 64 Cohort Type Lecture
Lecture 65 Plot Retention Rate of the Customer
Lecture 66 Plot Customer Vs Revenue Chart Part 1
Lecture 67 Plot Customer Vs Revenue Chart Part 2
Lecture 68 Create Pareto Chart Continued
Lecture 69 Aggregate Dataset
Lecture 70 K-Means Clustering Algorithm Part 1
Lecture 71 K-Means Clustering Algorithm Part 2
Lecture 72 K-Means Clustering Algorithm Part 3
Lecture 73 K-Means Clustering Algorithm Part 4
Lecture 74 What is Recency, Frequency, Monetary (RFM) Value
Lecture 75 Prepare RFM Table Part 1
Lecture 76 Prepare RFM Table Part 2
Lecture 77 Build RFM Score
Lecture 78 Visualize RFM Matrix
Section 8: Profit Booster Model
Lecture 79 Build Profit Booster Model
Lecture 80 Overview of Profit Booster Model
Lecture 81 Import and Enrich the Dataset
Lecture 82 Filter the Dataset
Lecture 83 Preprocessing of the Dataset
Lecture 84 Implement SMOTE
Lecture 85 Profit Estimation Equation
Lecture 86 Confusion Matrix - Logistic Regression, XGB Model
Lecture 87 Find Cumulative Cost of Errors
Lecture 88 Build Machine Learning Models - DummyClassifier, XGB Models
Lecture 89 Build Profit Curve and Review Results
Section 9: Propensity Model for Product Purchase
Lecture 90 Introduction
Lecture 91 Import Dataset
Lecture 92 Visualize Data
Lecture 93 Feature Selection Lasso-Ridge Regularization
Lecture 94 Feature Selection and Elimination
Lecture 95 Display Selected Features
Lecture 96 Display Selected Features Continued
Lecture 97 Build Model Pipeline
Lecture 98 Build Model Pipeline Continued
Lecture 99 Build Deep learning Model
Lecture 100 Voting Classifier
Lecture 101 Implement Voting Classifier
Lecture 102 Model Predictions
Beginner Python developer who are ready to Build Machine Learning Apps,Digital Marketers seeking to enhance campaign performance through data-driven insights and predictive modeling,Marketing Analysts who want to leverage machine learning to analyze campaign trends and optimize revenue strategies,Data Scientists interested in applying advanced ML techniques to solve real-world marketing challenges,Business Professionals aiming to improve ad spend efficiency, customer retention, and revenue generation,Students and Beginners exploring how machine learning applies to marketing and campaign management,Entrepreneurs and Small Business Owners looking to optimize their marketing efforts for better ROI
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