Through our exploration of AI and ML, we delve into prominent subfields such as Computer Vision, Natural Language Processing, and Optimisation to understand their significance and practical applications. We examine the intricacies of classification, equipping participants with the knowledge to build predictive models, and explore this by collecting our own dataset and training a classification model.
The course then delves into Neural Networks, a cornerstone of modern AI, and walks participants through a hands-on activity to comprehend their architecture. We also explore the realm of clustering – asking a machine to uncover hidden patterns and structures within data with no prior knowledge - and walk through an example showcasing how machine learning can be used to detect fraudulent transactions using the Python programming language (don’t worry, no prior programming experience is required!)
We then dive into Generative AI – advanced chatbots with responses that are shockingly human-like – to understand its mechanisms and explore applications such as copywriting, tech support, and code generation. By the end of this course, participants will possess foundational knowledge in AI and ML, allowing them to apply their knowledge to real-world problems and partake in AI and ML discussions with colleagues and stakeholders.
Intro to Artificial Intelligence and Machine Learning
• What is AI? ML? DL?
• Computer Vision, Natural Language Processing, and Optimisation
Supervised Learning
• Classification
• Neural Networks
• Hands-on: Collecting a data set and training a machine learning model
• Hands-on: Neural Networks – an interactive exploration of how a neural network works
Unsupervised Learning
• Clustering
• Demo: Using Python to detect fraud using supervised and unsupervised learning
Ethical and Societal Concerns
• Model Bias, Privacy and Security, Incorrect Predictions, and other concerns
Generative AI
• How do Large Languages Models work?
• Hands-on: Optimising interactions with Generative AIs such as ChatGPT/Bing/Bard
• Hands-on: Generating copywriting, ideas, and code with Generative AIs
Wrap Up
• Looking Ahead: how will AI impact the coming decades?
Note:
You may consider enrolling for Day 2 course, Robotics Process Automation (DGT047B) of the course upon completion of Day 1
OR opt for a 2-day course that covers both foundation and intermediate levels of Artificial Intelligence, Machine Learning, and Robotic Process Automation (DGT047C).
| Programme | 2024 Dates |
DGT047A: Artificial Intelligence and Machine Learning (Classroom)
(1-DAY)
Level: Foundation | - 21 Mar 2024
- 4 Nov 2024
Please click here to find out more. |
DGT047B: Robotics Process Automation Learning (Classroom)
(1-DAY)
Level: Intermediate | - 22 Mar 2024
- 5 Nov 2024
Please click here to find out more. |
DGT047C: Artificial Intelligence and Machine Learning (Classroom)
(2-DAY)
Level: Foundation to Intermediate | - 21 & 22 Mar 2024
- 4 & 5 Nov 2024
Please click here to find out more. |
Training Methodology
This course will alternate periods of lecture with demonstrations and hands-on activities. We believe strongly in differentiated, hands-on learning. For a learner, no amount of listening to lectures about “how to program” can beat the learning experience of putting hands onto keyboards and creating meaningful, tangible projects. We aim to design our lessons and workshops to be hands-on, highly participative, and with tangible, concrete outcomes, so that participants will be engaged at all times: programming, tinkering with hardware, looking up solutions, or trying to solve a problem. Such hands-on workshops are naturally more time-consuming to prepare and more difficult to deliver, but we strongly believe that this is the best way for participants to learn the material effectively, and will elicit the best learning outcomes.
Our goal is to ensure participants have enough skills to embark on future projects of their own, rather than just copying and pasting code to see things work. In our classes, learners will be carefully guided through the basic concepts, before being challenged to apply these concepts to create applications they can be proud of and, more importantly, use for future reference.
Our curriculum is designed by a team of trained teachers with real classroom teaching experience in MOE schools, and taught by trainers who possess actual programming experience from developing electronics and applications for startups and companies. We aim to adapt the best teaching materials available from all over the world, while supplementing them with best practices from our industry experience, to create the most effective programming courses for learners of all levels.
Closing Date for Registration
1 week before programme or until full enrolment