AI Engineer Programme
Transform your career with our comprehensive AI engineering training. Master Python, machine learning, and ethical AI development while building real-world applications that solve complex problems. This complete diploma takes you from fundamentals through advanced techniques, culminating in a professional portfolio of working AI systems.
Here's what you'll learn:
Enroll in this learning track and beging your journey to improving your skills.
AI Engineering Programme Introduction (AIPI01)
This introduction previews your journey from beginner to job-ready AI engineer. Discover the complete learning path, and understand how each module systematically develops your skills in Python, machine learning, and AI development.
AI Engineering Fundamentals (AIE01)
Explore what AI truly is, understand the career paths, and discover the essential skills and techniques that define modern AI engineering. Learn about foundation models, neural networks, and the core technologies powering today's AI revolution.
Data Analysis Fundamentals (DAF02)
This introductory course teaches students the basic concepts of data analysis, helping them understand fundamental terminology, principles, and approaches used in working with data.
Notebooks and IDEs (NAI01)
Learn how to use Jupyter Notebooks and Integrated Development Environments (IDEs) for writing and running code. Understand the features and benefits of these essential tools for data analysis and software development.
Python Fundamentals (PAI02)
Take your data analysis skills to the next level by mastering Python programming. This essential course allows you to gain skills that is critical for building powerful analytical solutions and becoming a professional analyst.
Python Streamlit Project (PSP01)
Introduction to building interactive data applications with Streamlit. Learn to create web apps using Python without frontend experience. Transform data scripts into shareable dashboards and visualization tools quickly and easily.
Python for Data (PDA03)
Learn how to use Python for data analysis. This course covers essential Python libraries and techniques for data manipulation, cleaning, and visualisation. You'll gain the ability to extract meaningful insights from data.
Sentiment Analysis Project (SAP01)
Build your first AI application from scratch. Load and work with pretrained models, evaluate performance on real data, and deploy an interactive web application. Learn model fine-tuning, visualisation techniques, and AI development considerations.
AI Prompt Engineering (APE01)
Learn basic techniques for writing clear, effective prompts that generate useful AI responses. Explore essential principles of prompt structure and discover practical applications for everyday tasks.
Retrieval-Augmented Generation (RAG01)
Master RAG systems that combine language models with external knowledge. Learn document processing, embeddings, and vector databases. Build your first intelligent RAG application using industry-standard tools and techniques.
Machine Learning Fundamentals (MLF02)
Master core machine learning principles and practices. Explore supervised, unsupervised, and reinforcement learning approaches. Learn to build models, handle real-world challenges, and understand the ML workflow from data preparation to deployment.
Machine Learning Project (MLP01)
Apply your ML fundamentals to build a complete working model. Set up your environment, explore and prepare datasets, implement training-testing splits, and evaluate model performance. Gaining hands-on experience with the machine learning workflow.
AI and Data Ethics (AIDE01)
Explore critical ethical considerations in AI development. Learn to identify and mitigate bias, ensure fairness and transparency, protect privacy, and maintain accountability. Understand the societal impact of AI systems and develop best practices.