Extract relevant data from the database in a time efficient manner

Build powerful SQL queries to derive insights

Analyse and manage large datasets, and derive inferences from complex relational database

Enable students to create and modify databases for relevant business problems

Select and use relevant charts for appropriate data problems

Use PowerBI to connect with data belonging to diverse formats

Communicate key insights from business problem using Reports and Dashboards

Create advanced visualization on Power BI using DAX

Explain the significance of Python in data science and its real-world applications.

Apply Python to manipulate and analyze diverse data sources, using Pandas and relevant data types

Create informative data visualizations and draw insights from data distributions and feature relationships

Develop a comprehensive data preparation workflow for machine learning, including data rescaling and feature engineering

Explain how humans behave when given data to calculate results

Demonstrate  how perceptions, prejudices and biases affect human decision making

Illustrate that human decision making is challenging and humans need help to make better decisions

Summarize how humans can collaborate effectively with AI, overcoming their biases, perceptions and prejudices

Construct Machine Learning models using the various steps of a typical Machine Learning Workflow

Apply appropriate metrics for various business problems to assess the performance of Machine Learning models

Develop regression and tree based Machine learning  Models to make predictions on relevant business problems

Analyze  business problems where unsupervised Machine Learning models  could be used to derive value from data

Employ regularization techniques for enhanced model performance and robustness.

Leverage ensemble methods, such as bagging and boosting, to improve predictive accuracy.

Implement hyperparameter tuning and feature engineering to refine models for real-world challenges.

Combine diverse models for superior predictions, expanding your predictive toolkit.

Explain the importance of Data Storytelling in communicating insights and facilitating decision making

Apply various visualization techniques to create a compelling data story

Apply various techniques to craft a compelling narrative for a data story

Create a captivating  data story by integrating relevant data, clear visualization and a compelling narrative