Data Science

Enables learners to transform raw data into reliable business insights by mastering data cleaning, governance, and statistical reasoning within a spreadsheet environment. Learners will develop the technical proficiency to source and prepare datasets, apply descriptive analytics, and use AI-powered tools to visualize patterns and validate assumptions for data-driven decision-making.

Outcomes

Transform raw data into reliable business insights by mastering data cleaning, statistical analysis, and AI-powered visualization within a spreadsheet environment..

A comprehensive foundation in relational database management, focusing on the ability to design, query, and optimize complex data structures using SQL. Learners will master everything from basic data retrieval to advanced analytical functions, window functions, and database normalization, all while applying best practices within production-grade notebook environments.

Outcomes

Design, query, and optimize relational databases using SQL—from basic data retrieval to advanced analytical functions and database normalization.

This course focuses on transforming complex datasets into impactful visual stories by mastering data modeling, Power Query transformations, and DAX expressions within Power BI. Learners will develop the skills to design interactive dashboards and accessible reports that effectively communicate insights to both technical and non-technical stakeholders.

Outcomes

Build interactive Power BI dashboards and reports that turn complex data into compelling visual stories using data modeling, Power Query, and DAX.

Master Python fundamentals from data structures and control flow to modular functions while integrating Git/GitHub and AI-assisted coding (Copilot/Claude) into a professional development workflow.

Outcomes

Master Python fundamentals data structures, control flow, and modular functions while building a professional workflow with Git, GitHub, and AI coding tools.

Explore software architecting by mastering Object-Oriented Programming (OOP), algorithmic complexity (Big O), and advanced functional techniques. Learn to build professional-grade, scalable codebases and leverage NumPy and pandas for high-performance data manipulation, all while using AI to optimize class hierarchies and complex data transformations.

Outcomes

Write scalable, professional-grade Python code using Object-Oriented Programming, algorythmic complexity analysis, AI optimization, and advanced functional techniques with NumPy and pandas for high-performance data manipulation.

Transition from data analysis to predictive modeling by mastering the supervised machine learning workflow. Build, diagnose, and optimize Linear Regression models (Simple and Multiple) using scikit-learn, handle high-dimensional data with Ridge and LASSO regularization, and deploy your models via object serialization (pickling). Use AI to scaffold ML pipelines and translate complex error metrics (RMSE/MAE) into actionable business insights.

Outcomes

Develop predictive models. Build, evaluate, and deploy supervised machine learning models using scikit-learn, applying regularization techniques and translating model performance into actionable business insights.

Master the art of predicting categories and managing complex model trade-offs. Build non-linear models like Decision Trees and Random Forests, solve classification problems with Logistic Regression, and learn to handle “needle-in-a-haystack” scenarios using SMOTE for imbalanced data. Use AI to trace complex decision logic and translate technical metrics like Precision and Recall into high-stakes business strategies.

Outcomes

Predict categories and navigate model trade-offs using Decision Trees, Random Forests, and Logistic Regression—including strategies for handling imbalanced datasets in high-stakes business scenarios.

Use the most powerful tools in the classifier’s arsenal, moving beyond basics to Support Vector Machines (SVMs), K-Nearest Neighbors (KNN), and Naive Bayes. Bridge the gap to deep learning by architecting Neural Networks with TensorFlow/Keras and learn the rigorous science of Model Selection—using cross-validation and automated Grid Search to systematically prove which algorithm is truly the “best fit” for your data.

Outcomes

Apply advanced classifiers SVMs, KNN, Naive Bayes, and Neural Networks and use cross-validation and Grid Search to rigorously identify the best model for your data.

Uncover the hidden architecture of unlabeled data by mastering Clustering and Dimensionality Reduction. Simplify massive datasets using Principal Component Analysis (PCA), visualize high-dimensional structures with t-SNE and UMAP, and segment populations using K-Means and Hierarchical Clustering. Use AI to detect anomalies and transform abstract cluster centroids into vivid, actionable business personas.

Outcomes

Uncover hidden patterns in unlabeled data using clustering and dimensionality reduction techniques PCA, t-SNE, K-Means, and more and translate results into actionable business personas.

Explore the science of personalization and spatial analysis by implementing Gaussian Mixture Models (GMMs) for probabilistic “soft clustering” and building advanced Recommendation Engines. Process geographic data using GeoPandas, implement both Content-Based and Collaborative Filtering, and leverage AI zero-shot classification to solve the “Cold-Start” problem for new items.

Outcomes

Build recommendation engines and analyze geographic data using probabilistic clustering, content-based and collaborative filtering, and AI-powered zero-shot classification to solve cold-start challenges.

Transform messy, unstructured text into actionable intelligence by mastering Natural Language Processing (NLP). Build robust text-cleaning pipelines covering Regex, tokenization, and lemmatization and convert language into math using TF-IDF and N-Grams. Step into modern AI by deploying Hugging Face Transformers for high-accuracy text classification without the need for manual training.

Outcomes

Transform unstructured text into actionable intelligence using NLP pipelines, TF-IDF, and modern Hugging Face Transformers for high-accuracy text classification.