Visit This Web URL https://masterytrail.com/product/accredited-expert-level-ibm-watson-ai-for-cybersecurity-advanced-video-course Lesson 1: Introduction to IBM Watson AI
1.1 Overview of IBM Watson AI
1.2 History and Evolution of Watson
1.3 Key Components of Watson AI
1.4 Applications of Watson AI in Cybersecurity
1.5 Setting Up Your Watson Environment
1.6 Introduction to Watson Studio
1.7 Introduction to Watson Machine Learning
1.8 Introduction to Watson Knowledge Studio
1.9 Introduction to Watson Discovery
1.10 Hands-On: Creating Your First Watson Project
Lesson 2: Fundamentals of Cybersecurity
2.1 Basic Concepts of Cybersecurity
2.2 Types of Cyber Threats
2.3 Cybersecurity Frameworks (e.g., NIST, ISO 27001)
2.4 Role of AI in Cybersecurity
2.5 Traditional vs. AI-Driven Cybersecurity
2.6 Introduction to Threat Intelligence
2.7 Cybersecurity Lifecycle
2.8 Importance of Incident Response
2.9 Case Studies: Successful AI Implementations
2.10 Hands-On: Analyzing a Cybersecurity Incident
Lesson 3: Watson for Cybersecurity Overview
3.1 Introduction to Watson for Cybersecurity
3.2 Key Features of Watson for Cybersecurity
3.3 How Watson Enhances Threat Detection
3.4 Watson's Role in Incident Response
3.5 Integrating Watson with Existing Security Tools
3.6 Use Cases of Watson for Cybersecurity
3.7 Benefits of Using Watson for Cybersecurity
3.8 Challenges and Limitations
3.9 Future Trends in AI-Driven Cybersecurity
3.10 Hands-On: Setting Up Watson for Cybersecurity
Lesson 4: Data Collection and Preprocessing
4.1 Types of Data in Cybersecurity
4.2 Sources of Cybersecurity Data
4.3 Data Collection Techniques
4.4 Data Preprocessing Steps
4.5 Handling Missing Data
4.6 Data Normalization and Standardization
4.7 Feature Engineering for Cybersecurity Data
4.8 Data Anonymization and Privacy
4.9 Tools for Data Preprocessing
4.10 Hands-On: Preprocessing Cybersecurity Data
Lesson 5: Threat Detection with Watson AI
5.1 Introduction to Threat Detection
5.2 Traditional Threat Detection Methods
5.3 AI-Driven Threat Detection
5.4 Watson's Threat Detection Capabilities
5.5 Building a Threat Detection Model
5.6 Evaluating Threat Detection Models
5.7 False Positives and False Negatives
5.8 Advanced Threat Detection Techniques
5.9 Integrating Watson with SIEM Systems
5.10 Hands-On: Implementing Threat Detection with Watson
Lesson 6: Anomaly Detection in Cybersecurity
6.1 Introduction to Anomaly Detection
6.2 Types of Anomalies in Cybersecurity
6.3 Anomaly Detection Techniques
6.4 Watson's Anomaly Detection Capabilities
6.5 Building an Anomaly Detection Model
6.6 Evaluating Anomaly Detection Models
6.7 Handling Imbalanced Data
6.8 Real-Time Anomaly Detection
6.9 Integrating Anomaly Detection with SOCs
6.10 Hands-On: Implementing Anomaly Detection with Watson
Lesson 7: Intrusion Detection Systems (IDS)
7.1 Introduction to IDS
7.2 Types of IDS (Network IDS, Host IDS)
7.3 IDS vs. IPS (Intrusion Prevention Systems)
7.4 AI-Driven IDS
7.5 Watson's IDS Capabilities
7.6 Building an IDS with Watson
7.7 Evaluating IDS Performance
7.8 Integrating IDS with Other Security Tools
7.9 Case Studies: Successful IDS Implementations
7.10 Hands-On: Implementing IDS with Watson
Lesson 8: Malware Detection and Analysis
8.1 Introduction to Malware
8.2 Types of Malware
8.3 Traditional Malware Detection Methods
8.4 AI-Driven Malware Detection
8.5 Watson's Malware Detection Capabilities
8.6 Building a Malware Detection Model
8.7 Evaluating Malware Detection Models
8.8 Malware Analysis Techniques
8.9 Integrating Malware Detection with SOCs
8.10 Hands-On: Implementing Malware Detection with Watson
Lesson 9: Phishing Detection and Prevention
9.1 Introduction to Phishing
9.2 Types of Phishing Attacks
9.3 Traditional Phishing Detection Methods
9.4 AI-Driven Phishing Detection
9.5 Watson's Phishing Detection Capabilities
9.6 Building a Phishing Detection Model
9.7 Evaluating Phishing Detection Models
9.8 Phishing Prevention Techniques
9.9 Integrating Phishing Detection with Email Security
9.10 Hands-On: Implementing Phishing Detection with Watson
Lesson 10: Network Security with Watson AI
10.1 Introduction to Network Security
10.2 Types of Network Attacks
10.3 Traditional Network Security Methods
10.4 AI-Driven Network Security
10.5 Watson's Network Security Capabilities
10.6 Building a Network Security Model
10.7 Evaluating Network Security Models
10.8 Network Traffic Analysis
10.9 Integrating Network Security with SOCs
10.10 Hands-On: Implementing Network Security with Watson
Lesson 11: Endpoint Security with Watson AI
11.1 Introduction to Endpoint Security
11.2 Types of Endpoint Threats
11.3 Traditional Endpoint Security Methods
11.4 AI-Driven Endpoint Security
11.5 Watson's Endpoint Security Capabilities
11.6 Building an Endpoint Security Model
11.7 Evaluating Endpoint Security Models
11.8 Endpoint Threat Detection and Response
11.9 Integrating Endpoint Security with SOCs
11.10 Hands-On: Implementing Endpoint Security with Watson
Lesson 12: Application Security with Watson AI
12.1 Introduction to Application Security
12.2 Types of Application Vulnerabilities
12.3 Traditional Application Security Methods
12.4 AI-Driven Application Security
12.5 Watson's Application Security Capabilities
12.6 Building an Application Security Model
12.7 Evaluating Application Security Models
12.8 Secure Software Development Lifecycle (SDLC)
12.9 Integrating Application Security with DevOps
12.10 Hands-On: Implementing Application Security with Watson
Lesson 13: Cloud Security with Watson AI
13.1 Introduction to Cloud Security
13.2 Types of Cloud Security Threats
13.3 Traditional Cloud Security Methods
13.4 AI-Driven Cloud Security
13.5 Watson's Cloud Security Capabilities
13.6 Building a Cloud Security Model
13.7 Evaluating Cloud Security Models
13.8 Cloud Security Best Practices
13.9 Integrating Cloud Security with SOCs
13.10 Hands-On: Implementing Cloud Security with Watson
Lesson 14: Identity and Access Management (IAM) with Watson AI
14.1 Introduction to IAM
14.2 Types of IAM Systems
14.3 Traditional IAM Methods
14.4 AI-Driven IAM
14.5 Watson's IAM Capabilities
14.6 Building an IAM Model
14.7 Evaluating IAM Models
14.8 Multi-Factor Authentication (MFA)
14.9 Integrating IAM with SOCs
14.10 Hands-On: Implementing IAM with Watson
Lesson 15: Incident Response with Watson AI
15.1 Introduction to Incident Response
15.2 Incident Response Lifecycle
15.3 Traditional Incident Response Methods
15.4 AI-Driven Incident Response
15.5 Watson's Incident Response Capabilities
15.6 Building an Incident Response Model
15.7 Evaluating Incident Response Models
15.8 Incident Response Best Practices
15.9 Integrating Incident Response with SOCs
15.10 Hands-On: Implementing Incident Response with Watson
Lesson 16: Threat Intelligence with Watson AI
16.1 Introduction to Threat Intelligence
16.2 Types of Threat Intelligence
16.3 Traditional Threat Intelligence Methods
16.4 AI-Driven Threat Intelligence
16.5 Watson's Threat Intelligence Capabilities
16.6 Building a Threat Intelligence Model
16.7 Evaluating Threat Intelligence Models
16.8 Threat Intelligence Sharing
16.9 Integrating Threat Intelligence with SOCs
16.10 Hands-On: Implementing Threat Intelligence with Watson
Lesson 17: Vulnerability Management with Watson AI
17.1 Introduction to Vulnerability Management
17.2 Types of Vulnerabilities
17.3 Traditional Vulnerability Management Methods
17.4 AI-Driven Vulnerability Management
17.5 Watson's Vulnerability Management Capabilities
17.6 Building a Vulnerability Management Model
17.7 Evaluating Vulnerability Management Models
17.8 Vulnerability Scanning and Assessment
17.9 Integrating Vulnerability Management with SOCs
17.10 Hands-On: Implementing Vulnerability Management with Watson
Lesson 18: Security Orchestration, Automation, and Response (SOAR) with Watson AI
18.1 Introduction to SOAR
18.2 Components of SOAR
18.3 Traditional SOAR Methods
18.4 AI-Driven SOAR
18.5 Watson's SOAR Capabilities
18.6 Building a SOAR Model
18.7 Evaluating SOAR Models
18.8 SOAR Best Practices
18.9 Integrating SOAR with SOCs
18.10 Hands-On: Implementing SOAR with Watson
Lesson 19: Advanced Machine Learning Techniques for Cybersecurity
19.1 Introduction to Advanced ML Techniques
19.2 Supervised Learning in Cybersecurity
19.3 Unsupervised Learning in Cybersecurity
19.4 Reinforcement Learning in Cybersecurity
19.5 Deep Learning in Cybersecurity
19.6 Transfer Learning in Cybersecurity
19.7 Ensemble Learning in Cybersecurity
19.8 Model Interpretability and Explainability
19.9 Ethical Considerations in AI for Cybersecurity
19.10 Hands-On: Implementing Advanced ML Techniques with Watson
Lesson 20: Natural Language Processing (NLP) for Cybersecurity
20.1 Introduction to NLP in Cybersecurity
20.2 Text Classification for Threat Detection
20.3 Sentiment Analysis for Threat Intelligence
20.4 Named Entity Recognition (NER) for Cybersecurity
20.5 Topic Modeling for Threat Intelligence
20.6 Chatbots for Incident Response
20.7 NLP for Phishing Detection
20.8 NLP for Malware Analysis
20.9 NLP for Log Analysis
20.10 Hands-On: Implementing NLP Techniques with Watson
Lesson 21: Advanced Data Visualization for Cybersecurity
21.1 Introduction to Data Visualization
21.2 Importance of Data Visualization in Cybersecurity
21.3 Types of Visualizations for Cybersecurity Data
21.4 Tools for Data Visualization
21.5 Creating Interactive Dashboards
21.6 Visualizing Threat Intelligence Data
21.7 Visualizing Incident Response Data
21.8 Visualizing Network Traffic Data
21.9 Visualizing Log Data
21.10 Hands-On: Creating Cybersecurity Visualizations with Watson
Lesson 22: Integrating Watson with Security Information and Event Management (SIEM) Systems
22.1 Introduction to SIEM Systems
22.2 Components of SIEM Systems
22.3 Traditional SIEM Methods
22.4 AI-Driven SIEM
22.5 Watson's SIEM Integration Capabilities
22.6 Building a SIEM Integration Model
22.7 Evaluating SIEM Integration Models
22.8 SIEM Best Practices
22.9 Case Studies: Successful SIEM Integrations
22.10 Hands-On: Integrating Watson with SIEM Systems
Lesson 23: Integrating Watson with Security Orchestration and Automation (SOA) Platforms
23.1 Introduction to SOA Platforms
23.2 Components of SOA Platforms
23.3 Traditional SOA Methods
23.4 AI-Driven SOA
23.5 Watson's SOA Integration Capabilities
23.6 Building a SOA Integration Model
23.7 Evaluating SOA Integration Models
23.8 SOA Best Practices
23.9 Case Studies: Successful SOA Integrations
23.10 Hands-On: Integrating Watson with SOA Platforms
Lesson 24: Integrating Watson with Threat Intelligence Platforms (TIPs)
24.1 Introduction to TIPs
24.2 Components of TIPs
24.3 Traditional TIP Methods
24.4 AI-Driven TIP
24.5 Watson's TIP Integration Capabilities
24.6 Building a TIP Integration Model
24.7 Evaluating TIP Integration Models
24.8 TIP Best Practices
24.9 Case Studies: Successful TIP Integrations
24.10 Hands-On: Integrating Watson with TIPs
Lesson 25: Integrating Watson with Vulnerability Management Platforms (VMPs)
25.1 Introduction to VMPs
25.2 Components of VMPs
25.3 Traditional VMP Methods
25.4 AI-Driven VMP
25.5 Watson's VMP Integration Capabilities
25.6 Building a VMP Integration Model
25.7 Evaluating VMP Integration Models
25.8 VMP Best Practices
25.9 Case Studies: Successful VMP Integrations
25.10 Hands-On: Integrating Watson with VMPs
Lesson 26: Integrating Watson with Identity and Access Management (IAM) Platforms
26.1 Introduction to IAM Platforms
26.2 Components of IAM Platforms
26.3 Traditional IAM Methods
26.4 AI-Driven IAM
26.5 Watson's IAM Integration Capabilities
26.6 Building an IAM Integration Model
26.7 Evaluating IAM Integration Models
26.8 IAM Best Practices
26.9 Case Studies: Successful IAM Integrations
26.10 Hands-On: Integrating Watson with IAM Platforms
Lesson 27: Advanced Threat Hunting with Watson AI
27.1 Introduction to Threat Hunting
27.2 Traditional Threat Hunting Methods
27.3 AI-Driven Threat Hunting
27.4 Watson's Threat Hunting Capabilities
27.5 Building a Threat Hunting Model
27.6 Evaluating Threat Hunting Models
27.7 Threat Hunting Techniques
27.8 Integrating Threat Hunting with SOCs
27.9 Case Studies: Successful Threat Hunting Implementations
27.10 Hands-On: Implementing Threat Hunting with Watson
Lesson 28: Advanced Forensic Analysis with Watson AI
28.1 Introduction to Forensic Analysis
28.2 Traditional Forensic Analysis Methods
28.3 AI-Driven Forensic Analysis
28.4 Watson's Forensic Analysis Capabilities
28.5 Building a Forensic Analysis Model
28.6 Evaluating Forensic Analysis Models
28.7 Forensic Analysis Techniques
28.8 Integrating Forensic Analysis with SOCs
28.9 Case Studies: Successful Forensic Analysis Implementations
28.10 Hands-On: Implementing Forensic Analysis with Watson
Lesson 29: Advanced Risk Management with Watson AI
29.1 Introduction to Risk Management
29.2 Traditional Risk Management Methods
29.3 AI-Driven Risk Management
29.4 Watson's Risk Management Capabilities
29.5 Building a Risk Management Model
29.6 Evaluating Risk Management Models
29.7 Risk Management Techniques
29.8 Integrating Risk Management with SOCs
29.9 Case Studies: Successful Risk Management Implementations
29.10 Hands-On: Implementing Risk Management with Watson
Lesson 30: Advanced Compliance Management with Watson AI
30.1 Introduction to Compliance Management
30.2 Traditional Compliance Management Methods
30.3 AI-Driven Compliance Management
30.4 Watson's Compliance Management Capabilities
30.5 Building a Compliance Management Model
30.6 Evaluating Compliance Management Models
30.7 Compliance Management Techniques
30.8 Integrating Compliance Management with SOCs
30.9 Case Studies: Successful Compliance Management Implementations
30.10 Hands-On: Implementing Compliance Management with Watson
Lesson 31: Advanced Cybersecurity Analytics with Watson AI
31.1 Introduction to Cybersecurity Analytics
31.2 Traditional Cybersecurity Analytics Methods
31.3 AI-Driven Cybersecurity Analytics
31.4 Watson's Cybersecurity Analytics Capabilities
31.5 Building a Cybersecurity Analytics Model
31.6 Evaluating Cybersecurity Analytics Models
31.7 Cybersecurity Analytics Techniques
31.8 Integrating Cybersecurity Analytics with SOCs
31.9 Case Studies: Successful Cybersecurity Analytics Implementations
31.10 Hands-On: Implementing Cybersecurity Analytics with Watson
Lesson 32: Advanced Cybersecurity Reporting with Watson AI
32.1 Introduction to Cybersecurity Reporting
32.2 Traditional Cybersecurity Reporting Methods
32.3 AI-Driven Cybersecurity Reporting
32.4 Watson's Cybersecurity Reporting Capabilities
32.5 Building a Cybersecurity Reporting Model
32.6 Evaluating Cybersecurity Reporting Models
32.7 Cybersecurity Reporting Techniques
32.8 Integrating Cybersecurity Reporting with SOCs
32.9 Case Studies: Successful Cybersecurity Reporting Implementations
32.10 Hands-On: Implementing Cybersecurity Reporting with Watson
Lesson 33: Advanced Cybersecurity Dashboards with Watson AI
33.1 Introduction to Cybersecurity Dashboards
33.2 Traditional Cybersecurity Dashboard Methods
33.3 AI-Driven Cybersecurity Dashboards
33.4 Watson's Cybersecurity Dashboard Capabilities
33.5 Building a Cybersecurity Dashboard Model
33.6 Evaluating Cybersecurity Dashboard Models
33.7 Cybersecurity Dashboard Techniques
33.8 Integrating Cybersecurity Dashboards with SOCs
33.9 Case Studies: Successful Cybersecurity Dashboard Implementations
33.10 Hands-On: Implementing Cybersecurity Dashboards with Watson
Lesson 34: Advanced Cybersecurity Alerts with Watson AI
34.1 Introduction to Cybersecurity Alerts
34.2 Traditional Cybersecurity Alert Methods
34.3 AI-Driven Cybersecurity Alerts
34.4 Watson's Cybersecurity Alert Capabilities
34.5 Building a Cybersecurity Alert Model
34.6 Evaluating Cybersecurity Alert Models
34.7 Cybersecurity Alert Techniques
34.8 Integrating Cybersecurity Alerts with SOCs
34.9 Case Studies: Successful Cybersecurity Alert Implementations
34.10 Hands-On: Implementing Cybersecurity Alerts with Watson
Lesson 35: Advanced Cybersecurity Automation with Watson AI
35.1 Introduction to Cybersecurity Automation
35.2 Traditional Cybersecurity Automation Methods
35.3 AI-Driven Cybersecurity Automation
35.4 Watson's Cybersecurity Automation Capabilities
35.5 Building a Cybersecurity Automation Model
35.6 Evaluating Cybersecurity Automation Models
35.7 Cybersecurity Automation Techniques
35.8 Integrating Cybersecurity Automation with SOCs
35.9 Case Studies: Successful Cybersecurity Automation Implementations
35.10 Hands-On: Implementing Cybersecurity Automation with Watson
Lesson 36: Advanced Cybersecurity Orchestration with Watson AI
36.1 Introduction to Cybersecurity Orchestration
36.2 Traditional Cybersecurity Orchestration Methods
36.3 AI-Driven Cybersecurity Orchestration
36.4 Watson's Cybersecurity Orchestration Capabilities
36.5 Building a Cybersecurity Orchestration Model
36.6 Evaluating Cybersecurity Orchestration Models
36.7 Cybersecurity Orchestration Techniques
36.8 Integrating Cybersecurity Orchestration with SOCs
36.9 Case Studies: Successful Cybersecurity Orchestration Implementations
36.10 Hands-On: Implementing Cybersecurity Orchestration with Watson
Lesson 37: Advanced Cybersecurity Playbooks with Watson AI
37.1 Introduction to Cybersecurity Playbooks
37.2 Traditional Cybersecurity Playbook Methods
37.3 AI-Driven Cybersecurity Playbooks
37.4 Watson's Cybersecurity Playbook Capabilities
37.5 Building a Cybersecurity Playbook Model
37.6 Evaluating Cybersecurity Playbook Models
37.7 Cybersecurity Playbook Techniques
37.8 Integrating Cybersecurity Playbooks with SOCs
37.9 Case Studies: Successful Cybersecurity Playbook Implementations
37.10 Hands-On: Implementing Cybersecurity Playbooks with Watson
Lesson 38: Advanced Cybersecurity Workflows with Watson AI
38.1 Introduction to Cybersecurity Workflows
38.2 Traditional Cybersecurity Workflow Methods
38.3 AI-Driven Cybersecurity Workflows
38.4 Watson's Cybersecurity Workflow Capabilities
38.5 Building a Cybersecurity Workflow Model
38.6 Evaluating Cybersecurity Workflow Models
38.7 Cybersecurity Workflow Techniques
38.8 Integrating Cybersecurity Workflows with SOCs
38.9 Case Studies: Successful Cybersecurity Workflow Implementations
38.10 Hands-On: Implementing Cybersecurity Workflows with Watson
Lesson 39: Advanced Cybersecurity Integrations with Watson AI
39.1 Introduction to Cybersecurity Integrations
39.2 Traditional Cybersecurity Integration Methods
39.3 AI-Driven Cybersecurity Integrations
39.4 Watson's Cybersecurity Integration Capabilities
39.5 Building a Cybersecurity Integration Model
39.6 Evaluating Cybersecurity Integration Models
39.7 Cybersecurity Integration Techniques
39.8 Integrating Cybersecurity Integrations with SOCs
39.9 Case Studies: Successful Cybersecurity Integration Implementations
39.10 Hands-On: Implementing Cybersecurity Integrations with Watson
Lesson 40: Future Trends in AI-Driven Cybersecurity
40.1 Emerging Threats in Cybersecurity
40.2 Advances in AI for Cybersecurity
40.3 The Role of Quantum Computing in Cybersecurity
40.4 The Impact of 5G on Cybersecurity
40.5 The Future of Watson AI in Cybersecurity
40.6 Ethical Considerations in AI-Driven Cybersecurity
40.7 Regulatory Challenges in AI-Driven Cybersecurity
40.8 Preparing for the Future of Cybersecurity
40.9 Case Studies: Innovative AI-Driven Cybersecurity Solutions