By completing this module, you will:

• Understand the data mining process for extracting knowledge from large datasets
• Grasp the fundamentals of text mining, pattern identification, and decision support

• Implement scalable pattern discovery techniques using transactional data

• Critically analyze the role of business data in organizational decision-making

• Understand and apply business analytics within management functions

• Apply appropriate data management and analysis techniques using Excel and Power BI

• Assess and evaluate strategies for modeling and visualizing real-world data

• Compare methodologies from academic sources on deploying statistical models
• Propose data-driven solutions to complex business problems
• Analyze strategies for computational analysis of large data volumes
• Evaluate scholarly methods and best practices for managing big data
• Propose solutions to challenges in storing and processing massive datasets
• Identify and discuss key ethical issues like bias, fairness, and privacy
• Understand the social and economic implications of data science applications
• Recognize stakeholder roles and apply ethical decision-making frameworks

By completing this module, you will:

• Understand and apply data mining techniques to uncover insights from complex datasets
• Build and evaluate machine learning models for business applications
• Utilize natural language processing to analyze text data and automate language-based tasks
• Analyze, manage, and interpret Big Data using modern frameworks and architectures
• Recognize and address privacy concerns and ethical issues in data handling
• Apply the skills to solve real-world analytical problems in various industries

By completing this module, you will:

• Understand and apply key data mining techniques for large-scale text analysis
• Develop skills in machine learning algorithms for classification, regression, and forecasting
• Build and train deep learning models for NLP using modern tools like BERT and TensorFlow
• Process and analyze large volumes of unstructured language data using big data technologies
• Identify ethical challenges and apply privacy-preserving strategies in NLP-driven systems
• Gain hands-on experience with end-to-end NLP workflows using real-world datasets

By completing this module, you will:

• Understand key techniques in data mining and apply them to extract knowledge from large datasets
• Gain hands-on experience in model training, validation, and testing using ML algorithms
• Design computer vision systems using CNNs, YOLO, and other deep learning models
• Analyze and manage large-scale data using Big Data frameworks and tools
• Compare methods of handling high-volume, high-velocity data for real-time decision-making
• Apply ethical reasoning to data science practices and address privacy concerns
• Communicate the social and ethical implications of AI and data-driven systems
• Propose scalable and responsible solutions to complex data problems

By completing this module, you will:

• Assess, analyse, and critique strategies for real-world data analytics challenges
• Compare and evaluate scholarly methodologies and industry-standard practices
• Formulate and execute actionable solutions for complex, evolving analytics problems
• Conduct literature reviews, hypothesis testing, and build ML-based models
• Develop interactive tools (e.g., dashboards) and deliver insights with clarity and precision
• Communicate research outcomes clearly to diverse audiences, including stakeholders and executives