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Cybersecurity Roadmap | |-- Fundamentals | |-- Introduction to Cybersecurity | | |-- Importance and Principles of Cybersecurity | | |-- Types of Cybersecurity (Network, Information, Application, Cloud, etc.) | | |-- Cybersecurity Threat Landscape (Malware, Phishing, Ransomware, etc.) | |-- Network Security | | |-- Firewalls and VPNs | | |-- Intrusion Detection Systems (IDS) | | |-- Intrusion Prevention Systems (IPS) | | |-- Network Access Control | |-- Threats and Vulnerabilities | |-- Types of Cyber Threats | | |-- Malware (Viruses, Worms, Trojans, etc.) | | |-- Phishing and Social Engineering | | |-- Denial of Service (DoS) Attacks | | |-- Insider Threats | |-- Vulnerability Assessment | | |-- Vulnerability Scanning | | |-- Penetration Testing (Ethical Hacking) | | |-- Security Audits and Assessments | |-- Encryption and Cryptography | |-- Introduction to Cryptography | | |-- Symmetric and Asymmetric Encryption | | |-- Hashing Algorithms (SHA, MD5, etc.) | | |-- Public Key Infrastructure (PKI) | |-- Encryption Protocols | | |-- SSL/TLS | | |-- IPsec | |-- Identity and Access Management (IAM) | |-- Authentication Mechanisms | | |-- Password Policies and Multi-Factor Authentication (MFA) | | |-- Biometric Authentication | |-- Access Control Models | | |-- Role-Based Access Control (RBAC) | | |-- Attribute-Based Access Control (ABAC) | | |-- Mandatory Access Control (MAC) | |-- Incident Response and Forensics | |-- Incident Response Process | | |-- Detection, Containment, Eradication, Recovery | | |-- Incident Response Teams (CSIRT) | |-- Digital Forensics | | |-- Evidence Collection and Preservation | | |-- Data Recovery | | |-- Forensic Tools (Autopsy, EnCase, etc.) | |-- Security Operations | |-- Security Monitoring | | |-- Security Information and Event Management (SIEM) | | |-- Log Management and Analysis | | |-- Threat Intelligence | |-- Security Operations Center (SOC) | | |-- SOC Roles and Responsibilities | | |-- Incident Management | |-- Cloud Security | |-- Cloud Security Principles | | |-- Shared Responsibility Model | | |-- Data Protection in Cloud Environments | |-- Cloud Security Tools | | |-- Cloud Access Security Brokers (CASB) | | |-- Security in Cloud Platforms (AWS, Azure, Google Cloud) | |-- Application Security | |-- Secure Software Development | | |-- Secure Coding Practices | | |-- Software Development Life Cycle (SDLC) | | |-- Secure Code Reviews | |-- Web Application Security | | |-- OWASP Top 10 | | |-- SQL Injection, Cross-Site Scripting (XSS), CSRF | |-- Compliance and Regulations | |-- Cybersecurity Standards | | |-- ISO/IEC 27001, NIST Cybersecurity Framework | | |-- CIS Controls, SOC 2 | |-- Data Privacy Regulations | | |-- GDPR | | |-- HIPAA, CCPA, PCI DSS | |-- Advanced Topics | |-- Advanced Persistent Threats (APT) | | |-- Detection and Mitigation | | |-- Threat Hunting | |-- Blockchain Security | | |-- Cryptographic Principles | | |-- Smart Contracts and Security | |-- IoT Security | | |-- Securing IoT Devices | | |-- Network Segmentation for IoT | |-- Emerging Trends | |-- AI and Machine Learning in Cybersecurity | | |-- AI-Based Threat Detection | | |-- Automating Incident Response | |-- Zero Trust Architecture | | |-- Principles of Zero Trust | | |-- Implementing Zero Trust in an Organization | |-- Soft Skills | |-- Communication and Collaboration | | |-- Reporting Security Incidents | | |-- Collaboration with Other Departments | |-- Ethical Hacking | | |-- Red Teaming and Blue Teaming | | |-- Bug Bounty Programs Free CyberSecurity Course For FREE Link 1 :https://bit.ly/3pXTXBZ Link 2 :https://bit.ly/3NV6n5S link 3 :https://bit.ly/3BfUukD link 4 :https://bit.ly/3OiMUNC link 5 :https://bit.ly/46Ltbxk Join @free4unow_backup for more free resources. ENJOY LEARNING 👍👍 #cybersecurity

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Big Data Roadmap | |-- Fundamentals | |-- Introduction to Big Data | | |-- Characteristics of Big Data (Volume, Velocity, Variety, Veracity, Value) | | |-- Big Data vs. Traditional Data Processing | |-- Mathematics and Programming for Big Data | | |-- Basic Probability and Statistics | | |-- Python (Pandas, NumPy) | | |-- Java/Scala (Optional) | |-- Big Data Tools and Frameworks | |-- Apache Hadoop | | |-- Hadoop HDFS (Distributed File System) | | |-- MapReduce | | |-- Hadoop Ecosystem (Hive, Pig, HBase, etc.) | |-- Apache Spark | | |-- RDDs and DataFrames | | |-- SparkSQL | | |-- Spark Streaming | | |-- MLlib (Machine Learning with Spark) | |-- Data Storage Solutions | |-- Distributed Databases | | |-- Apache HBase | | |-- Cassandra | | |-- Amazon DynamoDB | |-- NoSQL Databases | | |-- MongoDB | | |-- Couchbase | |-- Data Lakes | | |-- Amazon S3 | | |-- Hadoop HDFS | |-- Data Processing Frameworks | |-- Batch Processing | | |-- Apache Hadoop MapReduce | | |-- Apache Flink | |-- Stream Processing | | |-- Apache Kafka | | |-- Apache Storm | | |-- Apache Samza | |-- Data Analysis and Visualization | |-- Data Analysis Tools | | |-- Apache Hive | | |-- Apache Drill | |-- Data Visualization | | |-- Apache Zeppelin | | |-- Tableau (for big data) | | |-- Power BI | |-- Cloud-Based Big Data Tools | |-- Amazon Web Services (AWS) | | |-- Amazon EMR | | |-- AWS Redshift | | |-- AWS Glue | |-- Microsoft Azure | | |-- Azure HDInsight | | |-- Azure Synapse Analytics | |-- Google Cloud | | |-- Google BigQuery | | |-- Google Dataflow | |-- Machine Learning with Big Data | |-- Machine Learning Algorithms for Big Data | | |-- Collaborative Filtering | | |-- Dimensionality Reduction (PCA, LDA) | |-- Apache Mahout | | |-- Machine Learning on Hadoop | |-- Deep Learning on Big Data | | |-- TensorFlow on Spark | |-- Big Data Analytics | |-- Real-Time Analytics | | |-- Apache Kafka + Apache Storm | | |-- Apache Flink | |-- Predictive Analytics | | |-- Time Series Forecasting | | |-- Predictive Modeling with Spark MLlib | |-- Security and Privacy | |-- Big Data Security | | |-- Data Encryption | | |-- Authentication and Authorization in Hadoop | | |-- Secure Data Transmission | |-- Privacy Concerns | | |-- GDPR Compliance | | |-- Anonymization and Data Masking | |-- Certifications | |-- Cloudera Certified Associate (CCA) | |-- Google Cloud Certified - Professional Data Engineer | |-- Microsoft Certified: Azure Data Engineer

Cloud Computing Roadmap | |-- Fundamentals | |-- Introduction to Cloud Computing | | |-- Cloud Models (IaaS, PaaS, SaaS) | | |-- Cloud Deployment Models (Public, Private, Hybrid) | | |-- Virtualization Concepts | |-- Cloud Platforms | |-- Amazon Web Services (AWS) | | |-- EC2, S3, IAM, Lambda | | |-- AWS Networking and VPC | | |-- AWS Elastic Beanstalk | | | |-- Microsoft Azure | | |-- Azure Compute Services (VMs, Functions, App Services) | | |-- Azure Storage (Blob, SQL) | | |-- Azure Active Directory | | | |-- Google Cloud Platform (GCP) | | |-- Compute Engine, App Engine | | |-- Google Cloud Storage | | |-- BigQuery | |-- Cloud Computing Services | |-- Cloud Storage | | |-- Object Storage (S3, Google Cloud Storage) | | |-- Block Storage (EBS, Azure Disk Storage) | | | |-- Compute Resources | | |-- Virtual Machines (VMs) | | |-- Containers and Kubernetes | | |-- Serverless Computing (Lambda, Azure Functions) | |-- Networking and Security | |-- Cloud Networking | | |-- Virtual Private Cloud (VPC) | | |-- Load Balancers | | |-- Cloud DNS | | | |-- Cloud Security | | |-- Identity and Access Management (IAM) | | |-- Encryption (In-Transit, At-Rest) | | |-- Security Best Practices | |-- Cloud Automation and DevOps | |-- Infrastructure as Code | | |-- AWS CloudFormation | | |-- Terraform | |-- CI/CD in the Cloud | | |-- Jenkins, GitLab CI, AWS CodePipeline | |-- Containerization and Orchestration | | |-- Docker | | |-- Kubernetes | |-- Cloud Monitoring and Optimization | |-- Monitoring Tools | | |-- AWS CloudWatch | | |-- Azure Monitor | |-- Cost Management | | |-- AWS Cost Explorer | | |-- Google Cloud Billing | |-- Advanced Topics | |-- AI and Machine Learning in Cloud | | |-- AWS SageMaker | | |-- Azure Machine Learning | |-- Edge Computing | | |-- AWS Greengrass | |-- Cloud Security Architectures FREE COURSES TO LEARN CLOUD COMPUTING👇👇 Intro to Cloud Computing FREE UDACITY COURSE https://imp.i115008.net/2rXxJM Introduction to Cloud Computing FREE UDEMY COURSE https://bit.ly/3sGKjkA Free AWS Certified Cloud Practitioner 2019 https://bit.ly/3GMG9wJ Handbook of Cloud Computing https://studytm.files.wordpress.com/2014/03/hand-book-of-cloud-computing.pdf Google Cloud Computing FREE COURSE https://inthecloud.withgoogle.com/cloud-learning-paths-22/register.html Cloud Computing for Dummies FREE BOOK https://github.com/manjunath5496/AWS-Books/blob/master/azw(12).pdf ENJOY LEARNING 👍👍

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Web Development Roadmap | |-- Fundamentals | |-- Web Basics | | |-- Internet and HTTP/HTTPS Protocols | | |-- Domain Names and Hosting | | |-- Client-Server Architecture | | | |-- HTML (HyperText Markup Language) | | |-- Structure of a Web Page | | |-- Semantic HTML | | |-- Forms and Validations | | | |-- CSS (Cascading Style Sheets) | | |-- Selectors and Properties | | |-- Box Model | | |-- Responsive Design (Media Queries, Flexbox, Grid) | | |-- CSS Frameworks (Bootstrap, Tailwind CSS) | | | |-- JavaScript (JS) | | |-- ES6+ Features | | |-- DOM Manipulation | | |-- Fetch API and Promises | | |-- Event Handling | | |-- Version Control Systems | |-- Git Basics | |-- GitHub/GitLab | |-- Branching and Merging | |-- Front-End Development | |-- Advanced JavaScript | | |-- Modules and Classes | | |-- Error Handling | | |-- Asynchronous Programming (Async/Await) | | | |-- Frameworks and Libraries | | |-- React (Hooks, Context API) | | |-- Angular (Components, Services) | | |-- Vue.js (Directives, Vue Router) | | | |-- State Management | | |-- Redux | | |-- MobX | | |-- Back-End Development | |-- Server-Side Languages | | |-- Node.js (Express.js) | | |-- Python (Django, Flask) | | |-- PHP (Laravel) | | |-- Ruby (Ruby on Rails) | | | |-- Database Management | | |-- SQL Databases (MySQL, PostgreSQL) | | |-- NoSQL Databases (MongoDB, Firebase) | | | |-- Authentication and Authorization | | |-- JWT (JSON Web Tokens) | | |-- OAuth 2.0 | | |-- APIs and Microservices | |-- RESTful APIs | |-- GraphQL | |-- API Security (Rate Limiting, CORS) | |-- Full-Stack Development | |-- Integrating Front-End and Back-End | |-- MERN Stack (MongoDB, Express.js, React, Node.js) | |-- MEAN Stack (MongoDB, Express.js, Angular, Node.js) | |-- JAMstack (JavaScript, APIs, Markup) | |-- DevOps and Deployment | |-- Build Tools (Webpack, Vite) | |-- Containerization (Docker, Kubernetes) | |-- CI/CD Pipelines (Jenkins, GitHub Actions) | |-- Cloud Platforms (AWS, Azure, Google Cloud) | |-- Hosting (Netlify, Vercel, Heroku) | |-- Web Performance Optimization | |-- Minification and Compression | |-- Lazy Loading | |-- Code Splitting | |-- Caching (Service Workers) | |-- Web Security | |-- HTTPS and SSL | |-- Cross-Site Scripting (XSS) | |-- SQL Injection Prevention | |-- Content Security Policy (CSP) | |-- Specializations | |-- Progressive Web Apps (PWAs) | |-- Single-Page Applications (SPAs) | |-- Server-Side Rendering (Next.js, Nuxt.js) | |-- WebAssembly | |-- Trends and Advanced Topics | |-- Web 3.0 and Decentralized Apps (dApps) | |-- Motion UI and Animations | |-- AI Integration in Web Apps | |-- Real-Time Applications Web Development Resources 👇👇 Intro to HTML and CSS Intro to Backend Intro to JavaScript Web Development for Beginners Object-Oriented JavaScript Best Web Development Resources Join @free4unow_backup for more free resources. ENJOY LEARNING 👍👍

Machine Learning Roadmap | |-- Fundamentals | |-- Mathematics | | |-- Linear Algebra | | |-- Calculus (Gradients, Optimization) | | |-- Probability and Statistics | | |-- Matrix Operations | | | |-- Programming | | |-- Python (NumPy, Pandas, Scikit-learn) | | |-- R (Optional for Statistical Modeling) | | |-- SQL (For Data Extraction) | |-- Data Preprocessing | |-- Data Cleaning | |-- Feature Engineering | | |-- Encoding Categorical Data | | |-- Feature Scaling (Standardization, Normalization) | | |-- Handling Missing Values | |-- Dimensionality Reduction (PCA, LDA) | |-- Supervised Learning | |-- Regression | | |-- Linear Regression | | |-- Polynomial Regression | | |-- Ridge and Lasso Regression | |-- Classification | | |-- Logistic Regression | | |-- Decision Trees | | |-- Support Vector Machines (SVM) | | |-- Ensemble Methods (Random Forest, Gradient Boosting, XGBoost) | |-- Unsupervised Learning | |-- Clustering | | |-- K-Means | | |-- Hierarchical Clustering | | |-- DBSCAN | |-- Dimensionality Reduction | | |-- Principal Component Analysis (PCA) | | |-- t-SNE | |-- Association Rules (Apriori, FP-Growth) | |-- Reinforcement Learning | |-- Markov Decision Processes | |-- Q-Learning | |-- Deep Q-Learning | |-- Policy Gradient Methods | |-- Model Evaluation and Optimization | |-- Train-Test Split and Cross-Validation | |-- Performance Metrics | | |-- Accuracy, Precision, Recall, F1-Score | | |-- ROC-AUC | | |-- Mean Squared Error (MSE), R-squared | |-- Hyperparameter Tuning | | |-- Grid Search | | |-- Random Search | | |-- Bayesian Optimization | |-- Deep Learning | |-- Neural Networks | | |-- Perceptrons | | |-- Backpropagation | |-- Convolutional Neural Networks (CNN) | | |-- Image Classification | | |-- Object Detection (YOLO, SSD) | |-- Recurrent Neural Networks (RNN) | | |-- LSTM | | |-- GRU | |-- Transformers (Attention Mechanisms, BERT, GPT) | |-- Tools and Frameworks (TensorFlow, PyTorch) | |-- Advanced Topics | |-- Transfer Learning | |-- Generative Adversarial Networks (GANs) | |-- Reinforcement Learning with Neural Networks | |-- Explainable AI (SHAP, LIME) | |-- Applications of Machine Learning | |-- Recommender Systems (Collaborative Filtering, Content-Based) | |-- Fraud Detection | |-- Sentiment Analysis | |-- Predictive Maintenance | |-- Autonomous Vehicles | |-- Deployment of Models | |-- Flask, FastAPI | |-- Cloud Deployment (AWS SageMaker, Azure ML) | |-- Containerization (Docker, Kubernetes) | |-- Model Monitoring and Retraining Best Resources to learn Machine Learning 👇👇 Learn Python for Free Prompt Engineering Course Prompt Engineering Guide Data Science Course Google Cloud Generative AI Path Machine Learning with Python Free Course Machine Learning Free Book Deep Learning Nanodegree Program with Real-world Projects AI, Machine Learning and Deep Learning Join @free4unow_backup for more free courses ENJOY LEARNING👍👍

Data Analytics Roadmap | |-- Fundamentals |   |-- Mathematics |   |   |-- Descriptive Statistics |   |   |-- Inferential Statistics |   |   |-- Probability Theory |   | |   |-- Programming |   |   |-- Python (Focus on Libraries like Pandas, NumPy) |   |   |-- R (For Statistical Analysis) |   |   |-- SQL (For Data Extraction) | |-- Data Collection and Storage |   |-- Data Sources |   |   |-- APIs |   |   |-- Web Scraping |   |   |-- Databases |   | |   |-- Data Storage |   |   |-- Relational Databases (MySQL, PostgreSQL) |   |   |-- NoSQL Databases (MongoDB, Cassandra) |   |   |-- Data Lakes and Warehousing (Snowflake, Redshift) | |-- Data Cleaning and Preparation |   |-- Handling Missing Data |   |-- Data Transformation |   |-- Data Normalization and Standardization |   |-- Outlier Detection | |-- Exploratory Data Analysis (EDA) |   |-- Data Visualization Tools |   |   |-- Matplotlib |   |   |-- Seaborn |   |   |-- ggplot2 |   | |   |-- Identifying Trends and Patterns |   |-- Correlation Analysis | |-- Advanced Analytics |   |-- Predictive Analytics (Regression, Forecasting) |   |-- Prescriptive Analytics (Optimization Models) |   |-- Segmentation (Clustering Techniques) |   |-- Sentiment Analysis (Text Data) | |-- Data Visualization and Reporting |   |-- Visualization Tools |   |   |-- Power BI |   |   |-- Tableau |   |   |-- Google Data Studio |   | |   |-- Dashboard Design |   |-- Interactive Visualizations |   |-- Storytelling with Data | |-- Business Intelligence (BI) |   |-- KPI Design and Implementation |   |-- Decision-Making Frameworks |   |-- Industry-Specific Use Cases (Finance, Marketing, HR) | |-- Big Data Analytics |   |-- Tools and Frameworks |   |   |-- Hadoop |   |   |-- Apache Spark |   | |   |-- Real-Time Data Processing |   |-- Stream Analytics (Kafka, Flink) | |-- Domain Knowledge |   |-- Industry Applications |   |   |-- E-commerce |   |   |-- Healthcare |   |   |-- Supply Chain | |-- Ethical Data Usage |   |-- Data Privacy Regulations (GDPR, CCPA) |   |-- Bias Mitigation in Analysis |   |-- Transparency in Reporting Free Resources to learn Data Analytics skills👇👇 1. SQL https://mode.com/sql-tutorial/introduction-to-sql https://t.me/sqlspecialist/738 2. Python https://www.learnpython.org/ https://t.me/pythondevelopersindia/873 https://bit.ly/3T7y4ta https://www.geeksforgeeks.org/python-programming-language/learn-python-tutorial 3. R https://datacamp.pxf.io/vPyB4L 4. Data Structures https://leetcode.com/study-plan/data-structure/ https://www.udacity.com/course/data-structures-and-algorithms-in-python--ud513 5. Data Visualization https://www.freecodecamp.org/learn/data-visualization/ https://t.me/Data_Visual/2 https://www.tableau.com/learn/training/20223 https://www.workout-wednesday.com/power-bi-challenges/ 6. Excel https://excel-practice-online.com/ https://t.me/excel_data https://www.w3schools.com/EXCEL/index.php Join @free4unow_backup for more free courses Like for more ❤️ ENJOY LEARNING 👍👍