(SCTP) WSQ Diploma in Infocomm Technology (Data) (Synchronous and Asynchronous E-Learning) (Full-Time) (TA-Eligible)
About This Course
The Professional Diploma in Data Science prepares learners for dynamic careers in the expanding field of data science, offering pathways to roles like Data Scientist, Data Analyst, Machine Learning Engineer, and Business Intelligence Professional. Graduates can thrive in sectors such as finance, healthcare, technology, and retail, contributing to organizational success by extracting insights from data and driving strategic decisions.
The course starts with Data Modelling & Visualization, where learners grasp analytics fundamentals and use Power BI to transform data and create impactful dashboards. The Generative AI module introduces learners to advanced AI tools, prompt engineering, and chatbot development, enhancing productivity with tools like Microsoft Power Virtual Agents. The Python for Data Science module covers Python programming essentials and automating workflows with Power Platform.
Data Science Principles establishes a foundation in AI and machine learning, while Machine Learning Algorithms and Methods explore regression, classification, clustering, and Azure AI Services. The Deep Learning module delves into advanced AI domains like computer vision, face recognition, and natural language processing.
The Agile Project Management module equips learners with tools for managing data science projects using Scrum methodologies. Finally, the Data Science Modelling Project serves as a capstone, where learners apply their knowledge to plan, prepare, and evaluate data models in a practical setting.
Through hands-on modules and real-world applications, learners develop the expertise to address complex data challenges, preparing them for impactful roles in data science and AI.
What You'll Learn
Module 1: Data Modelling & Visualization
Module 2: Python for Data Science
Module 3: Machine Learning Algorithms and methods
Module 4: Data science principles
Module 5: Generative Artificial Intelligence
Module 6: Deep Learning
Module 7: Agile Project Management
Module 8: Data Science Modelling Project
Knowledge Learning Outcomes
• Identify various techniques in data modelling, visualization, and analysis using Power BI.
• Describe the fundamentals and advanced concepts of Generative AI and its practical applications.
• Evaluate the business value of Power Platform and articulate its significance in process automation.
• Differentiate between key machine learning and deep learning algorithms, including classification, regression, and clustering methods.
• Analyze the use of Azure AI Services for implementing pre-built models.
• Summarize agile project management principles and their implementation in data science projects.
Skills Learning Outcomes
• Design and create dynamic reports and dashboards using Power BI for insightful data visualization.
• Develop generative AI applications using prompt engineering and Microsoft Generative AI tools.
• Utilize Power Automate core components to automate workflows and streamline business processes.
• Implement machine learning and deep learning models to solve real-world problems and optimize their performance.
• Utilize computer vision and natural language processing techniques for efficient AI application development.
• Execute a data science modelling project from planning to development, integrating diverse data science skills.
Entry Requirements
Academic Qualification: Minimum 1 credit in O Level or its equivalent
English Proficiency - IELTS 5.5 or its equivalent.
Experience: Minimum 1-year experience in any business process