# Table of Contents

## Review of math fundamentals

#### Statistics

### Data Processing

##### Web scraping

- Handling Google Maps Location Data (in-time problem)
- Class size paradox and web scraping (using Amrita University placement data)

##### Data cleaning and imputation

### Python tutorials

##### Python for data science

- Getting started with python
- Data Visualisation with python
- Visualisation of tabular data
- A Not-so-Quick-but-Conceptual guide to Python | Intermediate | Part 1
- A not so quick but conceptual guide to python notebook intermediate | part-2
- All you ‘really’ need to know | Python Notebook | Advanced – Pandas

##### Networks

- NetworkX introduction
- Introduction to network science
- Network Centrality
- Shortest path
- Network Flow problems
- Community detection
- Bipartite matching

##### Deployment

### Exploratory Data Analytics

- Univariate Analysis (in-time problem)
- Multivariate Analysis (in-time problem)
- Multicollinearity (in-time problem)
- Time Series EDA (in-time problem)
- Combined: EDA in python
- Visualising tabular data

### Factor analysis

### Inferential data analytics (Hypothesis testing)

- z-test and t-test (in-time problem)
- ANOVA test (smart cities data)
- Chi-Square Goodness of fit test (in-time problem)
- Chi-Square test of independence

### Prediction algorithms (Supervised learning)

- Classification
- Regression
- Machine Learning (Simulation on shiny apps.io)
- Handling Imbalanced Classes
- Feature engineering (Python)
- Streaming Machine Learning (Blog post on Rolls Royce Data Labs website)
- ML using scikit-learn

### Prescriptive Analytics (Optimization)

- Linear Programming and Sensitivity analysis (basic)
- Inventory planning model (with CPLEX code)
- Gradient descent for non-linear optimization (Adoption of a new product)
- Analytic Hierarchy Process for multi-criterion optimization (Selecting a phone)
- Bass forecasting model (Python)

### Reinforcement Learning (Stochastic modelling)

### Time series forecasting

- Introduction to stationarity
- Stationarity hypothesis tests (in-time problem)
- Forecasting using ARIMA (in-time problem)
- ARIMA in python
- Seasonal time series

### Clustering

- Hierarchical Clustering (Market segmentation using wine data)
- K means clustering (Customer segmentation using credit card data)

### Deep Learning

### Other interesting posts

### Higher education in Data Science

- Review on IIMB Business Analytics and Intelligence course
- Part-time data science masters – why and options
- What to look at when choosing part-time masters (as part of Imperial college student blogs)
- Why should you study MSc in Business Analytics part-time (as part of Imperial college student blogs)

Cannot see the heading of the post in mobile browser.

Thanks for the observation. Will update it next time.

Updated!!