Certified Specialist Programme in AI in Social Engineering
-- viewing nowThe Artificial Intelligence in Social Engineering (AISE) programme is designed for professionals and enthusiasts who want to understand the intersection of AI and social engineering. Developed for AI and cybersecurity experts, this programme explores the latest techniques and tools used in social engineering attacks.
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About this course
Through interactive modules and real-world case studies, learners will gain a deep understanding of how AI is used to manipulate individuals and organizations.
Learn how to identify and mitigate AI-powered social engineering threats, and stay ahead of the evolving threat landscape.
Explore the AISE programme today and take the first step in protecting your organization from AI-driven social engineering attacks.
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Course details
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Social Engineering Fundamentals - This unit covers the basics of social engineering, including its definition, types, and techniques used by attackers to manipulate individuals into divulging confidential information or performing certain actions. •
Phishing and Spear Phishing - This unit focuses on the different types of phishing attacks, including email phishing, SMS phishing, and voice phishing, as well as spear phishing techniques used to target specific individuals or organizations. •
Pretexting and Baiting - This unit explores pretexting and baiting techniques used by attackers to trick victims into divulging sensitive information or performing certain actions, including the use of fake scenarios and enticing offers. •
Social Engineering in the Workplace - This unit examines the impact of social engineering on organizations, including the consequences of successful attacks, and provides guidance on how to prevent and mitigate social engineering threats in the workplace. •
AI and Machine Learning in Social Engineering - This unit discusses the role of artificial intelligence (AI) and machine learning (ML) in social engineering, including the use of AI-powered tools to analyze and predict human behavior, and the potential for ML-based attacks to evade detection. •
Cybersecurity Awareness and Training - This unit highlights the importance of cybersecurity awareness and training in preventing social engineering attacks, including the development of effective training programs and the role of leadership in promoting a culture of cybersecurity. •
Social Engineering Countermeasures and Mitigation - This unit provides guidance on how to prevent and mitigate social engineering attacks, including the implementation of security controls, such as multi-factor authentication and email filtering, and the use of security awareness training. •
Threat Intelligence and Incident Response - This unit explores the role of threat intelligence and incident response in detecting and responding to social engineering attacks, including the use of threat intelligence platforms and incident response playbooks. •
AI-Powered Social Engineering Detection and Prevention - This unit discusses the use of AI-powered tools to detect and prevent social engineering attacks, including the use of machine learning algorithms to analyze network traffic and identify suspicious activity. •
Social Engineering in the Cloud and Mobile Environment - This unit examines the unique challenges of social engineering in cloud and mobile environments, including the use of cloud-based services and mobile devices to deliver social engineering attacks.
Social Engineering Fundamentals - This unit covers the basics of social engineering, including its definition, types, and techniques used by attackers to manipulate individuals into divulging confidential information or performing certain actions. •
Phishing and Spear Phishing - This unit focuses on the different types of phishing attacks, including email phishing, SMS phishing, and voice phishing, as well as spear phishing techniques used to target specific individuals or organizations. •
Pretexting and Baiting - This unit explores pretexting and baiting techniques used by attackers to trick victims into divulging sensitive information or performing certain actions, including the use of fake scenarios and enticing offers. •
Social Engineering in the Workplace - This unit examines the impact of social engineering on organizations, including the consequences of successful attacks, and provides guidance on how to prevent and mitigate social engineering threats in the workplace. •
AI and Machine Learning in Social Engineering - This unit discusses the role of artificial intelligence (AI) and machine learning (ML) in social engineering, including the use of AI-powered tools to analyze and predict human behavior, and the potential for ML-based attacks to evade detection. •
Cybersecurity Awareness and Training - This unit highlights the importance of cybersecurity awareness and training in preventing social engineering attacks, including the development of effective training programs and the role of leadership in promoting a culture of cybersecurity. •
Social Engineering Countermeasures and Mitigation - This unit provides guidance on how to prevent and mitigate social engineering attacks, including the implementation of security controls, such as multi-factor authentication and email filtering, and the use of security awareness training. •
Threat Intelligence and Incident Response - This unit explores the role of threat intelligence and incident response in detecting and responding to social engineering attacks, including the use of threat intelligence platforms and incident response playbooks. •
AI-Powered Social Engineering Detection and Prevention - This unit discusses the use of AI-powered tools to detect and prevent social engineering attacks, including the use of machine learning algorithms to analyze network traffic and identify suspicious activity. •
Social Engineering in the Cloud and Mobile Environment - This unit examines the unique challenges of social engineering in cloud and mobile environments, including the use of cloud-based services and mobile devices to deliver social engineering attacks.
Career path
**Certified Specialist Programme in AI in Social Engineering**
**Career Roles and Job Market Trends in the UK**
| **Role** | **Description** | **Industry Relevance** |
|---|---|---|
| **Artificial Intelligence (AI) Specialist** | Design and implement AI solutions to drive business growth and improve customer experiences. | High demand in industries like finance, healthcare, and retail. |
| **Machine Learning (ML) Engineer** | Develop and train ML models to analyze complex data and make informed business decisions. | In high demand in industries like technology, finance, and healthcare. |
| **Data Scientist** | Extract insights from large datasets to inform business strategy and drive growth. | High demand in industries like finance, healthcare, and retail. |
| **Business Intelligence (BI) Analyst** | Develop and maintain BI solutions to drive business growth and improve decision-making. | In demand in industries like finance, retail, and healthcare. |
| **Natural Language Processing (NLP) Specialist** | Develop and implement NLP solutions to analyze and generate human language. | In high demand in industries like technology, finance, and healthcare. |
Entry requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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CERTIFIED SPECIALIST PROGRAMME IN AI IN SOCIAL ENGINEERING
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who has completed a programme at
London School of Planning and Management (LSPM)
Awarded on
05 May 2025
Blockchain Id: s-1-a-2-m-3-p-4-l-5-e
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