Bachelor of Science in Data Science | Units, Syllabus & Study Materials - YNetStudyHub
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Bachelor of Science in Data Science Verified Syllabus

Master Bachelor of Science in Data Science with structured academic semester units, topic lecture notes, past examinations, CATs, and interactive 24/7 AI tutor support on YNetStudyHub.

9 Semester Units 258 Curriculum Topics 4 Years Commission for University Education (CUE) Aligned 24/7 AI Tutor Enabled
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9 Units
258 Syllabus Topics
4 Years Duration
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Course Units & Curriculum 9 Units

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Data Ethics And Privacy
30 Topics
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1 Bias and Fairness in Data
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2 Bias and Fairness in Data Analysis
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3 Case Studies in Data Ethics
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4 Consent and Data Collection
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5 Data Anonymization and De-identification
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6 Data Anonymization and Pseudonymization
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7 Data Anonymization and Pseudonymization
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8 Data Breaches and Security Measures
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9 Data Privacy Impact Assessments
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10 Data Security and Encryption
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11 Data Security and Encryption
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12 Developing a Data Ethics Framework
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13 Emerging Trends in Data Ethics
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14 Ethical AI and Machine Learning
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15 Ethical Considerations in Data Analysis
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16 Ethical Considerations in Data Collection
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17 Ethical Data Collection Practices
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18 Ethical Data Sharing and Transparency
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19 Ethical Use of Artificial Intelligence
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20 Ethical Use of Artificial Intelligence
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21 Ethics in Data Sharing and Collaboration
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22 Introduction to Data Ethics Free Preview
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23 Introduction to Data Ethics
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24 Introduction to Data Ethics
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25 Privacy Impact Assessments
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26 Privacy Laws and Regulations
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27 Privacy Laws and Regulations
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28 Regulatory Frameworks for Data Privacy
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29 Responsible Data Sharing Practices
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30 Social Implications of Data Ethics
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Past examination papers for this unit are being compiled.
1 Anomaly Detection
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2 Big Data and Data Mining
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3 Big Data and Data Mining
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4 Case Studies in Data Mining
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5 Classification and Prediction
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6 Clustering and Association Rule Mining
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7 Data Exploration and Visualization
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8 Data Mining Techniques
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9 Data Mining Techniques
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10 Data Mining Tools and Software
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11 Data Preprocessing
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12 Data Preprocessing
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13 Data Preprocessing
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14 Ethical and Privacy Considerations in Data Mining
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15 Ethical and Privacy Considerations in Data Mining
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16 Ethical and Privacy Issues in Data Mining
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17 Evaluation and Validation
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18 Evaluation of Data Mining Models
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19 Evaluation of Data Mining Results
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20 Feature Selection and Dimensionality Reduction
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21 Feature Selection and Dimensionality Reduction
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22 Introduction to Data Mining Free Preview
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23 Introduction to Data Mining
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24 Introduction to Data Mining
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25 Neural Networks and Deep Learning for Data Mining
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26 Text Mining and Sentiment Analysis
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27 Text Mining and Sentiment Analysis
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28 Text Mining and Sentiment Analysis
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29 Time Series Analysis
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Past examination papers for this unit are being compiled.
1 Best Practices in Data Visualization
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2 Case Studies in Data Visualization
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3 Dashboard Creation
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4 Data Storytelling through Visualization
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5 Data Storytelling through Visualization
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6 Data Visualization Best Practices
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7 Data Visualization Ethics and Misinterpretation
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8 Data Visualization for Big Data
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9 Data Visualization for Big Data
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10 Data Visualization for Decision Making
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11 Data Visualization for Exploratory Data Analysis (EDA)
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12 Data Visualization Techniques
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13 Data Visualization Tools
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14 Data Visualization Tools
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15 Data Visualization Tools and Software
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16 Design Principles in Data Visualization
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17 Designing Effective Visualizations
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18 Ethical Considerations in Data Visualization
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19 Ethical Considerations in Data Visualization
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20 Geographic Data Visualization
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21 Interactive Data Visualization
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22 Interactive Data Visualization
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23 Interactive Data Visualization
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24 Introduction to Data Visualization Free Preview
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25 Introduction to Data Visualization
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26 Introduction to Data Visualization
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27 Principles of Data Visualization
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28 Principles of Effective Data Visualization
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29 Types of Data Visualizations
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30 Types of Data Visualizations
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Past examination papers for this unit are being compiled.
1 Business Intelligence and Data Warehousing
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2 Data Modeling for Data Warehousing
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3 Data Quality and Governance in Data Warehousing
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4 Data Quality and Governance in Data Warehousing
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5 Data Warehouse Architecture
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6 Data Warehouse Architecture
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7 Data Warehouse Implementation
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8 Data Warehouse Implementation
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9 Data Warehouse Implementation and Maintenance
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10 Data Warehousing Best Practices
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11 Data Warehousing Best Practices
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12 Data Warehousing Best Practices
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13 Data Warehousing Challenges and Solutions
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14 Data Warehousing Tools and Technologies
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15 Data Warehousing Tools and Technologies
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16 Data Warehousing Trends and Future Directions
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17 Data Warehousing Trends and Future Directions
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18 Dimensional Modeling
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19 Dimensional Modeling
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20 ETL Processes in Data Warehousing
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21 ETL Processes in Data Warehousing
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22 ETL Processes in Data Warehousing
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23 Introduction to Data Warehousing Free Preview
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24 Introduction to Data Warehousing
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25 Introduction to Data Warehousing
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No standalone PDF materials uploaded yet. Use the Topics & Lecture Notes tab above to read notes for each topic.
Past examination papers for this unit are being compiled.
1 Big Data and Data Mining
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2 Big Data and Data Science
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3 Data Acquisition and Cleaning
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4 Data Analysis Techniques
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5 Data Collection and Cleaning
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6 Data Ethics and Privacy
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7 Data Preprocessing
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8 Data Science Applications
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9 Data Science Lifecycle
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10 Data Science Project Management
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11 Data Types and Data Sources
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12 Data Visualization
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13 Data Visualization
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14 Data Visualization
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15 Ethical Considerations in Data Science
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16 Ethics and Privacy in Data Science
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17 Exploratory Data Analysis (EDA)
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18 Exploratory Data Analysis (EDA)
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19 History of Data Science
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20 Introduction to Machine Learning
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21 Introduction to Python for Data Science
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22 Introduction to R for Data Science
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23 Machine Learning Basics
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24 Machine Learning Fundamentals
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25 Model Evaluation and Validation
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26 Model Evaluation and Validation
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27 Statistical Analysis for Data Science
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28 What is Data Science? Free Preview
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29 What is Data Science?
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30 What is Data Science?
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No standalone PDF materials uploaded yet. Use the Topics & Lecture Notes tab above to read notes for each topic.
Past examination papers for this unit are being compiled.
1 Bayesian Statistics
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2 Calculus for Data Science
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3 Calculus for Data Science
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4 Clustering Algorithms
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5 Data Visualization
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6 Data Visualization
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7 Descriptive Statistics
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8 Descriptive Statistics
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9 Eigenvalues and Eigenvectors
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10 Hypothesis Testing
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11 Introduction to Algebra Free Preview
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12 Introduction to Linear Algebra
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13 Introduction to Linear Algebra
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14 Linear Algebra for Data Science
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15 Linear Regression
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16 Machine Learning Foundations
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17 Machine Learning Fundamentals
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18 Neural Networks Basics
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19 Optimization Techniques for Data Science
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20 Principal Component Analysis (PCA)
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21 Probability and Statistics for Data Science
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22 Probability Theory
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23 Probability Theory
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24 Regression Analysis
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25 Singular Value Decomposition (SVD)
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26 Statistical Inference
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27 Time Series Analysis
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No standalone PDF materials uploaded yet. Use the Topics & Lecture Notes tab above to read notes for each topic.
Past examination papers for this unit are being compiled.
1 Control Flow in Python
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2 Data Cleaning and Preprocessing
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3 Data Cleaning and Preprocessing
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4 Data Manipulation with Pandas
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5 Data Structures in Python
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6 Data Structures in Python
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7 Data Structures in Python
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8 Data Visualization with Matplotlib
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9 Data Visualization with Matplotlib and Seaborn
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10 Data Visualization with Python
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11 Exploratory Data Analysis (EDA)
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12 File Handling in Python
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13 Functions and Modules
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14 Handling Big Data with PySpark
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15 Introduction to Deep Learning with Python
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16 Introduction to Deep Learning with TensorFlow
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17 Introduction to Machine Learning with Python
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18 Introduction to Machine Learning with Scikit-Learn
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19 Introduction to Natural Language Processing (NLP)
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20 Introduction to Python Programming Free Preview
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21 Introduction to Python Programming
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22 Introduction to Python Programming
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23 Machine Learning with Python
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24 Model Evaluation and Validation
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25 NumPy for Data Science
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26 Pandas for Data Science
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27 Web Scraping and Data Collection
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28 Working with Libraries for Data Science
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29 Working with NumPy for Data Science
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No standalone PDF materials uploaded yet. Use the Topics & Lecture Notes tab above to read notes for each topic.
Past examination papers for this unit are being compiled.
1 Best Practices and Advanced Topics
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2 Control Structures and Functions in R
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3 Data Import and Export in R
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4 Data Manipulation in R
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5 Data Manipulation with dplyr
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6 Data Types and Data Structures in R
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7 Data Types and Data Structures in R
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8 Data Visualization with ggplot2
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9 Data Visualization with ggplot2
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10 Data Visualization with ggplot2
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11 Data Wrangling and Cleaning
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12 Introduction to R Programming Free Preview
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13 Introduction to R Programming
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14 Introduction to R Programming
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15 Machine Learning Basics in R
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16 Machine Learning Basics in R
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17 Machine Learning with R
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18 R Markdown for Reproducible Research
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19 Reporting and Presenting Results
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20 Shiny App Development
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21 Statistical Analysis in R
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22 Statistical Analysis with R
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23 Statistical Analysis with R
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24 Text Mining and Natural Language Processing in R
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25 Text Mining and Natural Language Processing in R
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26 Time Series Analysis in R
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27 Working with APIs and Web Scraping in R
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28 Working with External Data Sources
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No standalone PDF materials uploaded yet. Use the Topics & Lecture Notes tab above to read notes for each topic.
Past examination papers for this unit are being compiled.
1 ANOVA and Experimental Design
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2 Bayesian Statistics
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3 Bayesian Statistics
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4 Bayesian Statistics
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5 Correlation Analysis
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6 Correlation and Regression Analysis
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7 Data Visualization
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8 Data Visualization
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9 Data Visualization
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10 Descriptive Statistics
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11 Descriptive Statistics
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12 Experimental Design
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13 Hypothesis Testing
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14 Inferential Statistics
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15 Inferential Statistics
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16 Introduction to Statistics Free Preview
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17 Introduction to Statistics
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18 Introduction to Statistics
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19 Machine Learning and Statistics
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20 Probability Theory
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21 Probability Theory
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22 Probability Theory
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23 Regression Analysis
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24 Regression Analysis
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25 Sampling and Estimation
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26 Sampling Methods
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27 Sampling Techniques
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28 Statistical Testing
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29 Time Series Analysis
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30 Time Series Analysis
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No standalone PDF materials uploaded yet. Use the Topics & Lecture Notes tab above to read notes for each topic.
Past examination papers for this unit are being compiled.

Curriculum Architecture

This program is structured into comprehensive academic units combining theoretical foundations, analytical research, practical tutorials, and continuous assessments. Each unit is mapped to key learning outcomes aligned with higher education qualification frameworks.

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Career & Professional Trajectories

Graduates of Bachelor of Science in Data Science are qualified for diverse professional opportunities across industry, public service, corporate consulting, research institutions, international organizations, and postgraduate specialization.

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