Artificial Intelligence, Cybersecurity and Machine learning tools
This six-month short-term course offers a comprehensive introduction to the foundational concepts of artificial intelligence (AI), cybersecurity, and machine learning tools. Students will explore the core principles of AI, including machine learning algorithms and data analysis techniques, while gaining practical skills in safeguarding digital assets and understanding cybersecurity frameworks. The course is designed to provide hands-on experience with industry-standard tools and methodologies, preparing participants for real-world applications and challenges in these rapidly evolving fields. .
- Duration 6 Months
- Skill level Beginner
- Language English
- Assessments Yes
Course Overview
1. Introduction to Artificial Intelligence (AI)
• Overview of AI concepts and applications.
• History and evolution of AI.
• Types of AI (narrow AI, general AI, and super AI).
• Ethical considerations in AI development and deployment.
2. Fundamentals of Machine Learning (ML)
• Introduction to machine learning and its applications.
• Supervised, unsupervised, and reinforcement learning.
• Introduction to Basic ML algorithms
3. Deep Learning and Neural Networks
• Introduction to deep learning and neural networks.
• Building and training neural networks with TensorFlow or PyTorch.
• Convolutional Neural Networks (CNNs) for image recognition.
• Recurrent Neural Networks (RNNs) for sequence data.
4. Cybersecurity Fundamentals
• Overview of cybersecurity principles and threats.
• Common Cyber-attacks (Malware, Phishing, DoS, DDoS, etc.).
• Introduction to Social Engineering
• Security protocols and encryption techniques.
• Risk management and mitigation strategies.
5. Network Security and Cryptography
• Introduction to network security.
• Securing network infrastructure (Firewalls, Intrusion Detection Systems).
• Cryptography fundamentals (symmetric and asymmetric encryption, hashing).
• Secure communication protocols (SSL/TLS, SSH).
6. AI in Cybersecurity
• Applications of AI and machine learning in cybersecurity.
• Using ML for threat detection and malware analysis.
• AI-powered intrusion detection systems.
• Ethical considerations in AI-driven cybersecurity.
7. Practical Applications of AI and ML Tools
• Hands-on exercises using popular AI and ML libraries (e.g., scikit-learn, Keras).
• Building and training ML models for classification and regression tasks.
• Implementing AI algorithms for data analysis and prediction.
8. Cybersecurity Tools and Technologies
• Overview of cybersecurity tools and software.
• Intrusion detection and prevention systems (IDS/IPS).
• Vulnerability assessment and penetration testing tools.
• Security information and event management (SIEM) systems.
9. Emerging Trends and Future Directions
• Exploration of emerging trends in AI, ML, and cybersecurity.
• The impact of AI on the future of cybersecurity.
• Career opportunities and further study paths in AI, ML, and cybersecurity.
10. Certification and Continuing Education
• Award of certificate upon successful completion of the course.
• Resources for continued learning and professional development in AI, ML, and cybersecurity.
Facilitators
- Dr.A. SenthilKumar
- Dr. M. Ashok Kumar
- Miss. Liwa’ul Hamdi Labaran
- Mr. Abdullahi Sani
- Mr. Ibrahim Yekeen Olamilekan
- Mr. Victor Lawani
- Mr. Abel Onyoh
- Mr. Henry Dekeh Vicent
Contact Information
Reach us through below details.