Certificate Programme in AI Fundamentals
-- viewing nowArtificial Intelligence (AI) is revolutionizing industries worldwide, and AI Fundamentals is the key to unlocking its potential. Designed for beginners and professionals alike, this Certificate Programme in AI Fundamentals provides a comprehensive introduction to the basics of AI, including machine learning, natural language processing, and computer vision.
4,808+
Students enrolled
GBP £ 149
GBP £ 215
Save 44% with our special offer
About this course
Learn from industry experts and gain hands-on experience with AI tools and technologies, such as Python, TensorFlow, and Keras.
Develop a strong foundation in AI principles and apply them to real-world problems, enhancing your career prospects in data science, machine learning, and more.
Take the first step towards a career in AI and explore the Certificate Programme in AI Fundamentals today!
100% online
Learn from anywhere
Shareable certificate
Add to your LinkedIn profile
2 months to complete
at 2-3 hours a week
Start anytime
No waiting period
Course details
• Machine Learning Fundamentals
This unit covers the basics of machine learning, including supervised and unsupervised learning, regression, classification, clustering, and neural networks. It also introduces the concept of deep learning and its applications in AI. • Artificial Neural Networks
This unit delves deeper into the world of neural networks, exploring their structure, training algorithms, and applications in image and speech recognition, natural language processing, and more. Primary keyword: Artificial Neural Networks, Secondary keywords: Deep Learning, Neural Networks. • Natural Language Processing (NLP)
This unit focuses on the intersection of computer science and linguistics, covering topics such as text preprocessing, sentiment analysis, named entity recognition, and language models. Primary keyword: Natural Language Processing, Secondary keywords: NLP, Text Analysis. • Computer Vision Fundamentals
This unit introduces the basics of computer vision, including image processing, object detection, segmentation, and recognition. It also covers the use of deep learning techniques in computer vision applications. Primary keyword: Computer Vision, Secondary keywords: Image Processing, Object Detection. • Deep Learning Fundamentals
This unit covers the basics of deep learning, including convolutional neural networks, recurrent neural networks, and transfer learning. It also introduces the concept of attention mechanisms and their applications in NLP and computer vision. Primary keyword: Deep Learning, Secondary keywords: Convolutional Neural Networks, Recurrent Neural Networks. • Reinforcement Learning
This unit explores the concept of reinforcement learning, including Markov decision processes, Q-learning, and policy gradients. It also covers the applications of reinforcement learning in robotics, game playing, and finance. Primary keyword: Reinforcement Learning, Secondary keywords: Markov Decision Processes, Q-Learning. • Ethics in AI
This unit discusses the ethical implications of AI, including bias, fairness, transparency, and accountability. It also covers the importance of human-centered design and the need for diverse and inclusive AI development teams. Primary keyword: Ethics in AI, Secondary keywords: Bias, Fairness, Transparency. • AI for Business
This unit explores the applications of AI in business, including predictive analytics, customer service, and process automation. It also covers the importance of data quality, privacy, and security in AI-driven business decisions. Primary keyword: AI for Business, Secondary keywords: Predictive Analytics, Customer Service. • Human-Computer Interaction
This unit focuses on the design of user interfaces for AI systems, including voice assistants, chatbots, and virtual reality applications. It also covers the importance of user experience, accessibility, and usability in AI-driven systems. Primary keyword: Human-Computer Interaction, Secondary keywords: User Experience, Accessibility. • AI and Data Science
This unit explores the intersection of AI and data science, including data preprocessing, feature engineering, and model evaluation. It also covers the importance of data quality, visualization, and storytelling in AI-driven data science applications. Primary keyword: AI and Data Science, Secondary keywords: Data Preprocessing, Feature Engineering.
This unit covers the basics of machine learning, including supervised and unsupervised learning, regression, classification, clustering, and neural networks. It also introduces the concept of deep learning and its applications in AI. • Artificial Neural Networks
This unit delves deeper into the world of neural networks, exploring their structure, training algorithms, and applications in image and speech recognition, natural language processing, and more. Primary keyword: Artificial Neural Networks, Secondary keywords: Deep Learning, Neural Networks. • Natural Language Processing (NLP)
This unit focuses on the intersection of computer science and linguistics, covering topics such as text preprocessing, sentiment analysis, named entity recognition, and language models. Primary keyword: Natural Language Processing, Secondary keywords: NLP, Text Analysis. • Computer Vision Fundamentals
This unit introduces the basics of computer vision, including image processing, object detection, segmentation, and recognition. It also covers the use of deep learning techniques in computer vision applications. Primary keyword: Computer Vision, Secondary keywords: Image Processing, Object Detection. • Deep Learning Fundamentals
This unit covers the basics of deep learning, including convolutional neural networks, recurrent neural networks, and transfer learning. It also introduces the concept of attention mechanisms and their applications in NLP and computer vision. Primary keyword: Deep Learning, Secondary keywords: Convolutional Neural Networks, Recurrent Neural Networks. • Reinforcement Learning
This unit explores the concept of reinforcement learning, including Markov decision processes, Q-learning, and policy gradients. It also covers the applications of reinforcement learning in robotics, game playing, and finance. Primary keyword: Reinforcement Learning, Secondary keywords: Markov Decision Processes, Q-Learning. • Ethics in AI
This unit discusses the ethical implications of AI, including bias, fairness, transparency, and accountability. It also covers the importance of human-centered design and the need for diverse and inclusive AI development teams. Primary keyword: Ethics in AI, Secondary keywords: Bias, Fairness, Transparency. • AI for Business
This unit explores the applications of AI in business, including predictive analytics, customer service, and process automation. It also covers the importance of data quality, privacy, and security in AI-driven business decisions. Primary keyword: AI for Business, Secondary keywords: Predictive Analytics, Customer Service. • Human-Computer Interaction
This unit focuses on the design of user interfaces for AI systems, including voice assistants, chatbots, and virtual reality applications. It also covers the importance of user experience, accessibility, and usability in AI-driven systems. Primary keyword: Human-Computer Interaction, Secondary keywords: User Experience, Accessibility. • AI and Data Science
This unit explores the intersection of AI and data science, including data preprocessing, feature engineering, and model evaluation. It also covers the importance of data quality, visualization, and storytelling in AI-driven data science applications. Primary keyword: AI and Data Science, Secondary keywords: Data Preprocessing, Feature Engineering.
Career path
| **Career Role** | **Salary Range (£)** | **Job Market Trends** |
|---|---|---|
| Artificial Intelligence/Machine Learning Engineer | £12,000 - £20,000 | High demand, high salary |
| Data Scientist | £9,000 - £15,000 | Growing demand, moderate salary |
| Business Intelligence Developer | £7,000 - £12,000 | Moderate demand, moderate salary |
| Quantitative Analyst | £6,000 - £10,000 | Low to moderate demand, low salary |
| Robotics Engineer | £5,500 - £9,000 | Moderate demand, moderate salary |
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.
Why people choose us for their career
Loading reviews...
Frequently Asked Questions
Debug: False
Course fee
MOST POPULAR
Fast Track
GBP £149
Complete in 1 month
Accelerated Learning Path
- 3-4 hours per week
- Early certificate delivery
- Open enrollment - start anytime
Standard Mode
GBP £99
Complete in 2 months
Flexible Learning Pace
- 2-3 hours per week
- Regular certificate delivery
- Open enrollment - start anytime
What's included in both plans:
- Full course access
- Digital certificate
- Course materials
All-Inclusive Pricing • No hidden fees or additional costs
Get course information
Earn a career certificate
CERTIFICATE PROGRAMME IN AI FUNDAMENTALS
is awarded to
Learner Name
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
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
