Welcome To The Fortified

 

Unlock Insights From Vast Data  Sets 

 

Leading the way in Data Science 

Introduction to Data Science
System Architecture and Design Principles focus on the essential framework of IoT systems, covering key components, protocols, and data flow. Learn how to design robust, scalable, and secure architectures that connect devices, optimize communication, and streamline operations for smarter, more efficient IoT solutions.
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Data Collection and Preprocessing
IoT Networking covers the essential communication protocols and technologies that enable seamless connectivity between IoT devices. Explore wireless networks, sensors, and cloud integration to ensure reliable data exchange and efficient device management. Master the networking skills crucial for building scalable, secure IoT ecosystems.
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Data Visualization
Internet Connectivity Principle Applications delve into the core technologies that connect IoT devices to the internet. Learn about IP addressing, communication protocols, and cloud-based solutions that drive real-time data exchange. This module focuses on practical applications, ensuring efficient, secure, and scalable IoT deployments across various industries.
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Statistical Analysis
IoT Physical Devices & Endpoints explores the hardware components that make up an IoT system. Gain insights into sensors, actuators, embedded systems, and gateways that collect and transmit data. Understand how these devices interact to create a seamless, intelligent network, enabling real-world applications of IoT.
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Machine Learning Techniques
Applications of IoT showcase the transformative impact of IoT across industries such as healthcare, smart cities, agriculture, manufacturing, and transportation. Discover how connected devices enable automation, improve efficiency, and provide real-time insights, driving innovation and enhancing productivity in various sectors.
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Big Data and Data Engineering
Applications of IoT showcase the transformative impact of IoT across industries such as healthcare, smart cities, agriculture, manufacturing, and transportation. Discover how connected devices enable automation, improve efficiency, and provide real-time insights, driving innovation and enhancing productivity in various sectors.
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Advanced Topics in Data Science
Applications of IoT showcase the transformative impact of IoT across industries such as healthcare, smart cities, agriculture, manufacturing, and transportation. Discover how connected devices enable automation, improve efficiency, and provide real-time insights, driving innovation and enhancing productivity in various sectors.
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Capstone Project
Applications of IoT showcase the transformative impact of IoT across industries such as healthcare, smart cities, agriculture, manufacturing, and transportation. Discover how connected devices enable automation, improve efficiency, and provide real-time insights, driving innovation and enhancing productivity in various sectors.
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  • Perform data collection, cleaning, and analysis 
  • Build predictive models using machine learning algorithms 
  • Use visualization tools to communicate insights effectively 
  • Make data-driven decisions in business contexts 
  • Aspiring Data Scientists and Analysts 
  • IT Professionals Looking to Upskill 
  • Business Leaders Interested in Data-Driven Decision-Making 
  • Fresh Graduates Eager to Break Into the Data Science Field

Course Outline

  • Overview of cybersecurity concepts and importance
  • Introduction to Linux operating system
  • Overview and installation of Kali Linux
  • Basic Linux commands and navigation
  • Networking commands
  • User and group management
  • File and folder permissions
  • Services and process management
  • Aliases and password recovery
  • Understanding ethical hacking principles
  • Legal and ethical considerations
  • Hacking phases and methodologies
  • Information gathering and reconnaissance
  • OSINT (Open Source Intelligence) techniques
  • Reconnaissance tools (e.g., Nmap, Recon-ng)
  • Footprinting and scanning methods
  • Identifying vulnerabilities and weaknesses
  • Scanning and enumeration tools (e.g., Nmap, Nessus, OpenVas)
  • Understanding CVE, CWE, CVSS
  • Safe exploitation of vulnerabilities
  • Gaining access and maintaining control using Metasploit
  • Privilege escalation and lateral movement
  • Understanding OWASP Top Ten vulnerabilities
  • Web application penetration testing techniques
  • Module 06: Wireless and Mobile Security
  • Wireless network vulnerabilities
  • Secure wireless network configuration
  • Mobile device security threats
  • Security protocols for mobile platforms
  •  Packet sniffing techniques and tools
  • Understanding and mitigating DDoS attacks
  • Social engineering tactics
  • Defense strategies against social engineering
  •  Types of firewalls and their configurations
  • Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS)
  • Basics of cryptography and encryption methods
  • Implementing security protocols
  • Introduction to digital forensics
  • Forensic investigation process
  • Legal considerations and chain of custody
  • Tools used in digital forensics
  • Operating system forensics
  • Network traffic analysis
  • Web and email forensics
  • Investigating activities on the Dark Web
  • Understanding SIEM solutions
  • Implementing SIEM for threat detection
  • Log management and analysis
  • Correlating events for incident response
  • Creating SIEM use cases for threat detection
  • Custom correlation rules
  • Incident detection and response workflows
  • Threat hunting techniques using SIEM
  • Security analytics and anomaly detection
  • Identifying advanced threats and persistent adversaries