Artificial intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold. - Ray Kurzweil

Intensive Foundation in Artificial Intelligence and Cyber Security

Delivery Language - English.
Sector: STEM
​

​Who study this qualification:
​
The International Foundation Year in Artificial Intelligence and Cyber Security leads to a wide range of undergraduate engineering and science degrees at various UK Universities. 

This course is for

• Ambitious students aiming to study at a top-ranking university
• Those who are passionate about science and engineering
• Students who are interested in a practical way of learning

Admission Criteria

Student must have completed a GCSE Qualification or equivalent and achieved a grade C or above in English and Maths subjects.
​It is expected that a student would normally have the maturity to undertake this programme at the age of 17.

​What units are covered

Units

---

• ​English for Academic Purpose
• Information Technology
• Introduction to Data Analytics 
• Introduction to Research
  
• Introduction to Artificial Intelligence 
• ​Introduction to Cybersecurity

Course Content​
​

Our International Intensive Foundation in Artificial Intelligence and Cyber Security covers a wide array of fundamental subjects essential for students aiming to pursue further studies in engineering and science. The course content includes the following topics:

​Module 1: English for Academic Purpose

1. Fundamentals of Academic Writing
   • Structuring essays, reports, and research papers
   • Citation and referencing styles (APA, MLA, etc.)
   • Developing a strong thesis statement
2. Reading Strategies for Academic Texts
   • Skimming, scanning, and critical reading
   • Note-taking techniques
   • Analyzing and synthesizing information from academic sources
3. Effective Communication in Academic Settings
   • Formal vs. informal language
   • Academic vocabulary and language usage
   • Participating in seminars and presentations
4. Academic Listening and Speaking Skills
   • Note-taking during lectures
   • Effective presentation skills
   • Engaging in academic discussions and debates

Module 3: Introduction to Data Analytics

1. Understanding Data
   • Types of data: structured and unstructured
   • Data collection, cleaning, and preprocessing
2. Exploratory Data Analysis (EDA)
   • Data visualization techniques
   • Descriptive statistics
3. Introduction to Statistical Analysis
   • Probability theory
   • Hypothesis testing and significance
4. Tools for Data Analytics
   • Introduction to software like Python, R, or Excel for data analysis
   • Basic programming concepts for data manipulation

Module 5: Communication Skills

1. Effective Verbal Communication
   • Active listening and responding
   • Non-verbal communication cues
2. Written Communication
   • Email etiquette and formal writing
   • Crafting persuasive written content
3. Interpersonal Skills
   • Conflict resolution and negotiation
   • Building and maintaining professional relationships
4. Public Speaking and Presentation Skills
   • Overcoming stage fright
   • Structuring and delivering engaging presentations

Module 2: Information Technology

1. Introduction to Information Technology
   • Evolution and importance of IT
   • Basic components and functions of computer systems
2. Operating Systems and Software Applications
   • Overview of popular operating systems
   • Understanding software applications and their uses
3. Network Fundamentals
   • Basics of computer networks
   • Internet protocols and connectivity
4. Database Management
   • Introduction to databases
   • Structured Query Language (SQL) basics

Module 4: Introduction to Artificial Intelligence

1. Overview of AI
   • History and evolution of AI
   • Types of AI: narrow vs. general intelligence
2. Machine Learning Fundamentals
   • Supervised, unsupervised, and reinforcement learning
   • Feature engineering and model selection
3. Natural Language Processing (NLP) and Computer Vision
   • Basics of NLP and its applications
   • Understanding computer vision and image processing
4. Ethical Considerations in AI
   
   • Bias and fairness in AI algorithms
   • Privacy and security concerns

Module 6: Introduction to Cybersecurity

1. Cyber Threat Landscape
   • Types of cyber threats (malware, phishing, etc.)
   • Understanding vulnerabilities
2. Cyber Defense Strategies
   • Basics of encryption and cryptography
   • Network security principles (firewalls, intrusion detection)
3. Security Policies and Compliance
   • Importance of security policies
   • Regulatory compliance (GDPR, HIPAA, etc.)
4. Incident Response and Risk Management
   • Incident handling procedures
   • Risk assessment and mitigation techniques

​

This foundation course is designed to equip students with a strong base in these fundamental subjects, preparing them for more advanced studies in AI and Cyber Security at the undergraduate level. The focus is on providing a solid understanding of the principles and applications that underpin these fields.

Register for the programme

Key facts

​Group Size

​Max 10 students

Age

18+

​Level

Level 3

​Course Length

8 months Hybrid
3 months online and 5 months on London Canary Wharf Campus

​Hours per week

​15 hours per week

Course format

Usually, 2 days per week (15 hours/week) on a Blended mode.
 
1 day face to face (7.5 hours) and 1 day remote (7.5 hours) via Zoom.

Includes

​Monthly diagnostic test | Monthly 1:1 tutorial | Progress report

How it is delivered

The programme will typically be delivered as a short part time or full time course. This is a flexible programme delivered part time and full time. 

All of our study materials are evaluated by industry experts to ensure it reflects the current market demands. 

• Hybrid/Blended Delivery
• Remote Delivery

<

>

Usually, 2 days per week (15 hours/week) on a Blended mode.
 
1 day face to face (7.5 hours) and 1 day remote (7.5 hours) via Zoom.

Face to face arrangements: 

​Max 15 students are grouped into 1 classroom.
 
Lesson length: 10am-12pm (1st session), 12pm-1pm (Break), 1pm-3pm (2nd Session), 3pm-5.30pm (1:1 tutorials)

Current students are on a remote mode, studying 15 hours per week with one synchronous Zoom sessions every week (as required).
 
Students are on self-progress mode where they decide when to complete their programme of study. Williams College ensures all the units are taught adequately and students are responsible to complete the assessment within the prescribed time.

Register today

How it is assessed
​

All units will be internally assessed by Williams college. All units are assignment based. 

To complete the programme, students will need to show that they meet each of the assessment criteria detailed within each unit, to the required standard for the level of the unit.

---