Cyber Security Artificial Intelligence Strategist (CSAI)

$580.00

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Description

  • Duration: 4 Day / 32 Hours
  • Certification: Participants will receive a Certificate of Competency upon successfully completing the course and passing the examination
  • Who Should Attend: Cyber Security Professionals, Business Leaders, Artificial Intelligence (AI) Professionals, IT Professionals, Business Professionals, Computer Scientists, Programmers, and Anyone interested in pursuing a career in the areas of Cyber Security, Data Analytics, and Artificial Intelligence (AI).

Course Objective

Acquire advanced knowledge and skills in cyber security and artificial intelligence, and address the various types of cyber threats using Artificial Intelligence (AI)

Learn how to use Python and its extensive libraries and develop data analysis and machine learning skills to detect anomalies and identify potential threats.

Pre-Requisite

No pre-requisite. Cyber Security Artificial Intelligence Strategist (CSAI) is suitable for everyone.

Examination

Participants are required to attempt an examination upon completion of the course. This exam tests a candidate’s knowledge and skills related to Cyber Security, Artificial Intelligence, and Data Analytics based on the syllabus covered

Participants are expected to score a minimum of 70% to pass the examination

Course Outline


Module 1
Introduction to Cyber Security Artificial Intelligence

Cybersecurity and artificial intelligence (AI) are two areas that are becoming increasingly intertwined. AI has the potential to enhance cybersecurity efforts by automating tasks such as threat detection, analysis, and response.

Topics Covered

  • Introduction to Cyber Security and Artificial Intelligence (AI)
  • Intersection of Cyber Security and Artificial Intelligence (AI)
  • Introduction to Artificial Intelligence (AI) (Machine Learning, Deep Learning, Natural Language Processing (NLP))
  • Common Artificial Intelligence Algorithms and Techniques
  • Artificial Intelligence (AI) Models and Architectures
  • Threat Detection with Artificial Intelligence (AI)

Module 2
Python Programming For Cyber Security Professionals

Python is a versatile language that offers a wide range of libraries and tools that are particularly useful for cybersecurity tasks such as network analysis, web application testing, cryptography, and threat intelligence.

Topics Covered

  • Introduction to Python Programming for Cyber Security
  • Python Sytax, Data Types, Operators, Expressions, Control Structures (if-else, for, while loops)
  • Essential Python Libraries for (AI) (NumPy, Pandas, and Matplotlib)
  • Working with Data Structures in Python
  • Data Visualization using Matplotlib

Module 3
Application of Machine Learning in Cyber Security

Machine learning is used in a wide range of cybersecurity applications, including intrusion detection, malware analysis, behavioral analysis, network traffic analysis, and user behavior analytics.

Topics Covered

  • Train-Test-Splitting of Data
  • Standardization of Data
  • Principal Component Analysis
  • Using Markov Chains to Generate Text
  • xGBoost Classifier
  • Time Series Analysis using Statsmodel
  • Detecting Anomaly with Isolation
  • Natural Language Processing
  • Model Performance Evaluation

Module 4
Detection of Email Threats with Artificial Intelligence (AI)

Artificial Intelligence (AI) has emerged as a powerful tool for detecting email threats and protecting against them. AI-based email threat detection systems can analyze large volumes of email traffic and identify suspicious or malicious messages in real-time.

Topics Covered

  • Spam Detection with Perceptrons
  • Spam Detection with SVMs
  • Phishing Detection with Logistic Regression
  • Using Naïve Bayes for Spam Detection

Module 5
Malware Threat Detection

Machine learning and artificial intelligence techniques have emerged as a powerful tool for detecting and mitigating malware threats. Machine learning algorithms can analyze large datasets to identify patterns and anomalies that may indicate a potential malware threat.

Topics Covered

  • What is Malware Analysis
  • Classification of Malware Families
  • Decision Tree Malware Detection
  • Detecting Metamorphic Malware with HMMs
  • Deep Learning for Malware Detection

Module 6
Network Anomaly Detection

AI-powered network anomaly detection systems have significantly improved the ability of organizations to identify and respond to network-based threats, enhancing their overall cybersecurity posture.

Topics Covered

  • Identifying the Various Network Anomaly Detection Techniques
  • Classification of Network Attacks
  • Detecting Botnet Topology
  • Machine Learning Algorithms for Botnet Detection

Module 7
User Authentication Security With Artificial Intelligence

AI-powered authentication systems can also detect anomalies in user behavior that may indicate a potential security threat, such as account takeover attempts or insider threats.

Topics Covered

  • What is Authentication Detection
  • Identification and Prevention of Authentication Abuse
  • Account Reputation Scoring
  • Subscribe to Slack Events
  • Subscribe to Bot Events
  • Post Deployment Verification: Slack Bot

Module 8
Generative Adversarial Network (GAN) for Cyber Security

GANs have emerged as a powerful tool for cybersecurity applications, including the generation of realistic data for penetration testing and the detection of cyber attacks.

Topics Covered

  • What is Generative Adversarial Network (GAN)
  • Common Python Libraries for GAN
  • Network Attack via Model Substitution
  • IDS evasion via GAN
  • Facial Recognition Attacks with GAN

Module 9
Penetration Testing with Artificial Intelligence (AI)

With the advancements in Artificial Intelligence (AI), Penetration Testing can be taken to the next level by incorporating AI algorithms and techniques.

Topics Covered

  • Key Requirements to Perform Penetration
  • Testing with AI

  • CAPTCHA breaker
  • Using Neural Network-assisted Fuzzing
  • DeepExploits
  • Web Vulnerability Scanner using AI
  • IOT Device Type Identification using AI
    Malicious URL Detector
  • Deep Learning Based Automatic Detection

Cyber Security Artificial Intelligence Professional (CSAI) involves rigorous usage of real-time case studies, hands-on exercises and group discussion

Some Reasons Why Learners Choose CASUGOL

  • International Certification Body

  • Presence in 38 Countries

  • Developed by Industry Experts

  • More than 42,000 professionals passed through our education system

  • Flexible program design for all individuals

  • Learn from internationally renowned leading industry experts, academics, and researchers

  • Support for participants during and after training

  • Enhance competency of workforce and improve individual career prospect

  • Customization of programs for specific industry, organization, government agencies, statutory boards

  • Learn in a highly interactive, supportive and encouraging environment

  • Regular invitation to attend courses / workshops / seminars / events at complimentary rate


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Certificate Verification

All certificates issued by CASUGOL are to individuals who have successfully completed CASUGOL Certification Programs / Executive Workshops and have fulfilled all requirements by demonstrating proficiency in applying the knowledge and skills acquired.

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