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Bachelor of Science in Data Science
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Course Outline
9 sections
1. Introduction to Data Science
300 mins
30 topics
What is Data Science?
History of Data Science
Data Science Lifecycle
Data Types and Data Sources
Data Preprocessing
2. Mathematics for Data Science
270 mins
27 topics
Introduction to Algebra
Descriptive Statistics
Probability Theory
Linear Algebra for Data Science
Calculus for Data Science
3. Statistics for Data Science
300 mins
30 topics
Introduction to Statistics
Probability Theory
Data Visualization
Sampling and Estimation
Hypothesis Testing
4. Data Visualization
300 mins
30 topics
Introduction to Data Visualization
Types of Data Visualizations
Data Visualization Tools
Principles of Effective Data Visualization
Data Visualization Best Practices
5. Data Mining
290 mins
29 topics
Introduction to Data Mining
Data Preprocessing
Data Mining Techniques
Evaluation of Data Mining Models
Feature Selection and Dimensionality Reduction
6. Data Warehousing
250 mins
25 topics
Introduction to Data Warehousing
Data Modeling for Data Warehousing
ETL Processes in Data Warehousing
Data Warehouse Implementation
Data Warehousing Tools and Technologies
7. Python Programming for Data Science
290 mins
29 topics
Introduction to Python Programming
Data Structures in Python
Control Flow in Python
Functions and Modules
File Handling in Python
8. R Programming for Data Science
280 mins
28 topics
Introduction to R Programming
Data Types and Data Structures in R
Data Manipulation with dplyr
Data Visualization with ggplot2
Working with External Data Sources
9. Data Ethics and Privacy
300 mins
30 topics
Introduction to Data Ethics
Ethical Considerations in Data Collection
Privacy Laws and Regulations
Data Anonymization and Pseudonymization
Bias and Fairness in Data Analysis