Online Data analysis, Data Science, Semester machine and deep learning project

We are looking for a tutor for Wharton data science competition

Learn the Core Data Science Skills

You don't need advanced machine learning, but you should be comfortable with

Data cleaning

Descriptive statistics

Probability

Regression

Classification models

Data visualization

Spreadsheet analysis (Excel/Google Sheets)

Python (Pandas, NumPy, Matplotlib)

Wharton's own Data Science Academy curriculum emphasizes statistics, regression, classification, visualization, and data wrangling.

Wharton Global Youth Program

• Practice Sports Analytics

Recent competitions involved

Soccer playoff predictions

Basketball tournament predictions

Ice hockey performance predictions

Students were asked to

Rank teams

Predict match outcomes

Create performance metrics

Build visualizations

Explain their reasoning clearly

Wharton Sports Analytics +1

A good practice project

Download IPL, NBA, EPL, or Cricket World Cup datasets from Kaggle.

Predict match winners.

Build team rankings.

Create visual dashboards.

• Master Feature Engineering

Winning teams often create new variables instead of relying only on raw data.

Examples

Point differential

Home-field advantage

Possession-adjusted statistics

Recent form metrics

Offensive/defensive ratings

Wharton's competition playbooks specifically highlight feature engineering as a key differentiator.

Wharton Sports Analytics +1

• Learn These Models

Start with

Linear Regression

Logistic Regression

Elo Rating Systems

Random Forests

XGBoost (optional)

Many successful teams use relatively simple models but explain them well.

Wharton Sports Analytics +1

• Build Presentation Skills

The competition has multiple rounds

Initial analysis

Slide presentation

Live finalist presentation to judges

Wharton Sports Analytics

Judges care about

Clear storytelling

Visualizations

Reasoning behind decisions

Team communication

Level: Beginner

Teacher's Gender: Any

Meeting options

Available online - via skype etc. We are looking for a tutor for Wharton data science competition

Learn the Core Data Science Skills

You don't need advanced machine learning, but you should be comfortable with

Data cleaning

Descriptive statistics

Probability

Regression

Classification models

Data visualization

Spreadsheet analysis (Excel/Google Sheets)

Python (Pandas, NumPy, Matplotlib)

Wharton's own Data Science Academy curriculum emphasizes statistics, regression, classification, visualization, and data wrangling.

Wharton Global Youth Program

• Practice Sports Analytics

Recent competitions involved

Soccer playoff predictions

Basketball tournament predictions

Ice hockey performance predictions

Students were asked to

Rank teams

Predict match outcomes

Create performance metrics

Build visualizations

Explain their reasoning clearly

Wharton Sports Analytics +1

A good practice project

Download IPL, NBA, EPL, or Cricket World Cup datasets from Kaggle.

Predict match winners.

Build team rankings.

Create visual dashboards.

• Master Feature Engineering

Winning teams often create new variables instead of relying only on raw data.

Examples

Point differential

Home-field advantage

Possession-adjusted statistics

Recent form metrics

Offensive/defensive ratings

Wharton's competition playbooks specifically highlight feature engineering as a key differentiator.

Wharton Sports Analytics +1

• Learn These Models

Start with

Linear Regression

Logistic Regression

Elo Rating Systems

Random Forests

XGBoost (optional)

Many successful teams use relatively simple models but explain them well.

Wharton Sports Analytics +1

• Build Presentation Skills

The competition has multiple rounds

Initial analysis

Slide presentation

Live finalist presentation to judges

Wharton Sports Analytics

Judges care about

Clear storytelling

Visualizations

Reasoning behind decisions

Team communication

Level: Beginner

Teacher's Gender: Any

Meeting options

Available online - via skype etc.