Data Science Syllabus — Government College of Engineering and Technol…
Full syllabus, topics and curated resources for Data Science (Government College of Engineering and Technology, Jammu).
Data science fundamentals, exploratory data analysis, machine learning and probabilistic models
- Subject code: CST-3604
- University: Government College of Engineering and Technology, Jammu
- Course: BE (2022 onwards)
- Branch: CE
- Semester: 6
Data Science syllabus
Unit 1: Introduction to Data Science
- What is Data Science
- Applications of Data Science
- Data Lifecycle - Acquisition, Cleaning, Analysis and Interpretation
- Ethical Considerations in Data Science
- Relation to Data Mining, Machine Learning, Big Data and Statistics
- Data Sources and Types
- Data Collection Methods
- Data Cleaning and Pre-Processing Techniques
Unit 2: Exploratory Data Analysis
- Descriptive Statistics - Mean, Mode and Median
- Descriptive Statistics - Variance, Standard Deviation and Weighted Averaging
- Data Visualization - Histograms and Boxplots
- Data Visualization - Scatterplots and Time Series
- Spatial Data Visualization
- Introduction to Exploratory Data Mining
- Association Discovery - Definition, Challenges and Apriori Algorithm
- Clustering - Definition and Challenges
Unit 3: Machine Learning Fundamentals
- Introduction to Machine Learning
- Supervised vs. Unsupervised Learning
- Classification vs. Regression
- Decision Trees
- Rule Learners
- Linear Regression
- Logistic Regression
- Nearest Neighbour Learning
- Support Vector Machines
- K-Means Clustering
- Hierarchical Clustering
- DBSCAN
Unit 4: Measuring Model Performance
- Confusion Matrix
- Accuracy, Precision and Recall
- F1-Score
- ROC Curves and AUC-ROC
- Precision-Recall Curves
- Loss Functions for Regression
- Confidence Interval for Accuracy
- Hypothesis Tests for Comparing Models and Algorithms