Data, AI, and Cloud Courses

This course is for R users who want to get up to speed with Python!

Learn to build recommendation engines in Python using machine learning techniques.

Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.

Build real-world applications with Python—practice using OOP and software engineering principles to write clean and maintainable code.

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

Streamline your AI projects by building modular models and mastering advanced optimization with PyTorch Lightning!

Learn how to develop deep learning models with Keras.

Learn strategies for answering probability questions in R by solving a variety of probability puzzles.

Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.

Learn efficient techniques in pandas to optimize your Python code.

Master marketing analytics using Tableau. Analyze performance, benchmark metrics, and optimize strategies across channels.

Learn the basics of cash flow valuation, work with human mortality data and build life insurance products in R.

Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

Unlock your datas potential by learning to detect and mitigate bias for precise analysis and reliable models.

Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.

Create a healthcare AI agent using Haystack, an open-source framework for orchestrating LLMs and external components.

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

Learn basic business modeling including cash flows, investments, annuities, loan amortization, and more using Google Sheets.

Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!

Learn how to segment customers in Python.

Discover how to analyze and visualize baseball data using Power BI. Create scatter plots, tornado charts, and gauges to bring baseball insights alive.

This Power BI case study follows a real-world business use case where you will apply the concepts of ETL and visualization.

Learn how to build a graphical dashboard with Google Sheets to track the performance of financial securities.

In this course, youll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.