The Complete Artificial Intelligence for Cyber Security 2024

Overview

Combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications What you'll learn:

Isolation ForestMarkov ChainsStatsmodelsNLP (Natural Language Processing)Linear RegressionLogistic RegressionNaïve BayesANN (Artificial Intelligence)Random ForestK-meansHMMEigenfaces and EigenvaluesSVM (Support Vector Machine)XGBOOSTPandasNumpymatplotlibIF-IDFTensorflowScikit-LearnCyber securityGoogle ColabData Pre-processing.Analysing Data.Data standardization.Splitting Data into Training Set and Test Set.One-hot Encoding.Understanding Machine Learning Algorithm.Training Neural Network.Model building.Analysing Results.Model compilation.A Comparison Of Categorical And Binary Problem.Make a Prediction.Testing Accuracy.Confusion Matrix.Keras. *** AS SEEN ON KICKSTARTER ***Learn key AI concepts and intuition training to get you quickly up to speed with all things AI. Covering:

How to start building AI with no previous coding experience using Python.How to solve AI problems in cyber security field.Here is what you will get with this course:

1.

Complete beginner to expert AI skills – Learn to code self-improving AI for a range of purposes. In fact, I will code together with you.

Every tutorial starts with a blank page and we write up the code from scratch. This way you can follow along and understand exactly how the code comes together and what each line means.2.

Coding step– Plus, you’ll get a template which shows all the steps and all detailed explanations on each step.3. Intuition Tutorials – Where most courses simply bombard you with dense theory and set you on your way, you will develop a deep understanding for not only what you’re doing, but why you’re doing it.

That’s why I don’t throw complex theories at you, but focus on building up your intuition in coding AI making for infinitely better results down the line.4. Real-world solutions – You’ll achieve your goal in not only 1 project but in more than 10.

Each module is comprised of varying structures and difficulties, meaning you’ll be skilled enough to build AI adaptable to any projects in real life, rather than just passing a glorified memory “test and forget” like most other courses. Practice truly does make perfect.5.

In-course support – I fully committed to making this the most accessible and results-driven AI course on the planet. This requires me to be there when you need my help.

That’s why I will support you in your journey, meaning you’ll get a response from me within 72 hours maximum.

Syllabus

• Introduction to AI and Cyber Security
Overview of AI in Cybersecurity
Importance and Applications of AI in Cybersecurity
Current Trends and Future Perspectives
• Understanding the Basics of Cybersecurity
Key Concepts in Cybersecurity
Types of Cyber Threats and Attacks
Cybersecurity Frameworks and Standards
• AI Fundamentals
Machine Learning vs. Deep Learning
Key Machine Learning Algorithms
Introduction to Neural Networks
• Data Collection and Preprocessing for Cybersecurity
Types of Data in Cybersecurity
Data Preprocessing Techniques
Feature Selection and Feature Engineering
• Machine Learning for Cyber Threat Detection
Supervised Learning for Threat Detection
Unsupervised Learning in Anomaly Detection
Deep Learning for Intrusion Detection
• Natural Language Processing in Cybersecurity
NLP Basics and its Role in Cybersecurity
Analyzing Threat Intelligence Data
Text Mining for Phishing Detection
• AI for Malware Analysis and Prevention
Static vs. Dynamic Malware Analysis
Machine Learning Techniques in Malware Detection
Real-time Malware Prevention Strategies
• AI in Network Security
Network Traffic Analysis using AI
Intrusion Detection Systems (IDS)
AI-driven Firewall Technologies
• Ethical Hacking and AI
Role of AI in Penetration Testing
Identifying AI-driven Vulnerabilities
Building AI Tools for Ethical Hacking
• Implementing AI-based Security Tools
Designing and Deploying AI Security Applications
Evaluating and Improving AI Systems in Cybersecurity
Case Studies of AI Successfully Mitigating Threats
• Privacy, Ethics, and the Future of AI in Cybersecurity
AI Ethics and Cybersecurity Challenges
Security Risks of AI Deployments
Future Developments and Innovations
• Capstone Project
Project Proposal and Design
Implementation of AI Solutions for Cybersecurity
Presentation and Evaluation of Projects

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Taught by

Hoang Quy La

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Subjects

Data Science