Data Science

Level 7 Postgraduate Diploma in Data Science - 120 Credits

Module 1: Advanced Data Analytics (20 credits)

  • Exploring advanced statistical methods for data analysis.
  • Hypothesis testing, regression analysis, and time series analysis.
  • Applications of data analytics in real-world scenarios.

Module 2: Machine Learning and Deep Learning (20 credits)

  • In-depth study of machine learning algorithms, including neural networks.
  • Deep learning architectures and frameworks (e.g., TensorFlow, PyTorch).
  • Model optimization, transfer learning, and generative models.

Module 3: Big Data and Cloud Computing (20 credits)

  • Managing and processing big data using cloud platforms.
  • Distributed computing, data pipelines, and scalable architectures.
  • Integration of cloud services in data science projects.

Module 4: Natural Language Processing and Text Mining (20 credits)

  • Techniques for processing and analyzing textual data.
  • Sentiment analysis, named entity recognition, and topic modeling.
  • Building text-based applications and models.

Module 5: Advanced Data Visualization and Interpretation (20 credits)

  • Design principles for effective data visualizations.
  • Interactive dashboards, geospatial visualization, and storytelling with data.
  • Communicating complex insights through visualizations.

Module 6: Data Ethics and Governance (10 credits)

  • Ethical considerations in data science and AI.
  • Data privacy regulations, bias mitigation, and fairness in algorithms.
  • Establishing data governance frameworks.

Module 7: Capstone Project (30 credits)

  • A substantial data science project demonstrating mastery of advanced skills.
  • Problem-solving, data collection, feature engineering, and modeling.
  • Presentation of findings, insights, and recommendations.

Grading System:

  • Distinction: 70% - 100%
  • Merit: 60% - 69%
  • Pass: 50% - 59%
  • Fail: Below 50%
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