Data Analyst

1. 1. Mathematics

1.1. Calculus

1.2. Standard Deviation

1.3. System of Linear Equation

1.4. Matrix Operation

1.4.1. Inverse

1.4.2. Transpose

1.5. Solving Linear Equation using Gaussian Elimination

1.6. Row Echelon Form

1.7. Matrix Approximation

1.8. Vector Operations

1.9. Linear Mappings

1.10. Linear Algebra

1.11. Probability

2. 2. Statistics

2.1. Mean, Standard Deviation, and Variance - Implementation

2.2. Descriptive and Inferential Statistics

2.3. Probability Theory and Distribution

2.4. Sampling Distribution

2.5. Linear Regression

2.6. Sample Error and True Error

2.7. Bias Vs Variance and Its Trade-Off

2.8. Hypothesis Testing

2.9. Confidence Intervals

2.10. Correlation and Covariance

2.11. Correlation Coefficient

2.12. Covariance Matrix

2.13. Pearson Correlation

2.14. Spearman’s Rank Correlation Measure

2.15. Kendall Rank Correlation Measure

2.16. Robust Correlations

3. 3. Programming Languages

3.1. Python

3.2. R Programming

3.3. MATLAB

3.4. Scala

3.5. Julia

3.6. SQL

4. 5. Tools

4.1. MS Excel

4.2. Tableau

4.3. RapidMiner

5. 4. Basic Skills Required

5.1. Problem Solving

5.2. Data Wrangling

5.2.1. Data Collection

5.2.2. Data Cleaning

5.2.3. Data Visualization

5.3. Database Knowledge