Foundation of Data Science

Foundation of Data Science - Engineering Subject

Foundation of Data Science - CS3352 3rd Semester CSE Dept | 2021 Regulation | Anna University Engineering Subject Paper

Unit I: Introduction

1. Data Science and Big Data - Definition, Characteristics, Comparison, Benefits, Uses

2. Facets of Data - Data Science

3. Data Science Process

4. Defining Research Goals - Data Science

5. Retrieving Data - Data Science

6. Data Preparation - Operations | Data Science

7. Exploratory Data Analysis - Data Science

8. Build the Models - Model and Variable Selection, Model Execution, Diagnostics, Comparison | Data Science

9. Presenting Findings and Building Applications - Data Science

10. Data Mining - Reasons for using, Functions, Mining Tasks, Architecture, classification

11. Data Warehousing - Characteristics, Multitier Architecture, Needs, Benefits, Metadata

12. Basic Statistical Descriptions of Data - Data Science

13. Two marks Questions with Answers - Introduction | Foundation of Data Science

Unit II: Describing Data

1. Types of Data - Describing Data | Data Science

2. Types of Variables - Describing Data | Data Science

3. Describing Data with Tables - Describing Data | Data Science

4. Graphs for Quantitative Data - Describing Data | Data Science

5. Graph for Qualitative (Nominal) Data - Describing Data | Data Science

6. Misleading Graph - Describing Data | Data Science

7. Describing Data with Averages - Data Science

8. Describing Variability - Data Science

9. Normal Distributions and Standard (z) Scores - Describing Data | Data Science

10. Two marks Questions with Answers - Describing Data | Foundation of Data Science

Unit III: Describing Relationships

1. Correlation - Types, Coefficient, Properties, Example Solved Problems | Data Science

2. Scatter Plots - Examples, Advantages, Disadvantage | Data Science

3. Correlation Coefficient for Quantitative Data - Properties, Formula, Example Solved Problems | Data Science

4. Regression - Properties, Formula, Example Solved Problems | Data Science

5. Interpretation of R2 - Characteristics, Spurious Regression | Data Science

6. Multiple Regression Equations - Data Science

7. Regression Towards the Mean - Data Science

8. Two marks Questions with Answers - Describing Relationships | Foundation of Data Science

Unit IV: Python Libraries for Data Wrangling

1. Data Wrangling - Data Science

2. Introduction to Python - Features, Advantages and Disadvantages of Python

3. Numpy - Python Libraries for Data Wrangling

4. Basics of Numpy Arrays - Python Libraries for Data Wrangling

5. Aggregations - Python Libraries for Data Wrangling

6. Computations on Arrays - Python Libraries for Data Wrangling

7. Comparisons, Masks and Boolean Logic - Python Libraries for Data Wrangling

8. Fancy Indexing - Python Libraries for Data Wrangling

9. Structured Arrays - Python Libraries for Data Wrangling

10. Data Manipulation with Pandas - Python Libraries for Data Wrangling

11. Hierarchical indexing - Python Libraries for Data Wrangling

12. Combining Datasets - Python Libraries for Data Wrangling

13. Aggregation and Grouping - Python Libraries for Data Wrangling

14. Pivot Tables - Python Libraries for Data Wrangling

15. Two marks Questions with Answers - Python Libraries for Data Wrangling | Foundation of Data Science

Unit V: Data Visualization

1. Importing Matplotlib - Data Visualization

2. Scatter Plots - Matplotlib | Data Visualization

3. Visualizing Errors - Matplotlib | Data Visualization

4. Density and Contour Plots - Matplotlib | Data Visualization

5. Histogram - Matplotlib | Data Visualization

6. Legend - Matplotlib | Data Visualization

7. Subplots - Matplotlib | Data Visualization

8. Text and Annotation - Matplotlib | Data Visualization

9. Customization - Matplotlib | Data Visualization

10. Three Dimensional Plotting - Matplotlib | Data Visualization

11. Geographic Data with Basemap - Matplotlib | Data Visualization

12. Visualization with Seaborn - Matplotlib | Data Visualization

13. Two marks Questions with Answers - Data Visualization | Foundation of Data Science