Data, AI, and Cloud Courses

Learn how to design and implement triggers in SQL Server using real-world examples.

Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.

Learn to streamline your machine learning workflows with tidymodels.

Develop a better intuition for advanced probability, risk assessment, and simulation techniques to make data-driven business decisions with confidence.

Learn to analyze Airbnb data using SQL in Databricks, create dashboards, and derive actionable insights.

Learn vibe coding with Replit. Build apps like a Typeform clone, and master securing and deploying Replit apps.

Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.

In this Power BI case study you’ll play the role of a junior trader, analyzing mortgage trading and enhancing your data modeling and financial analysis skills.

Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.

Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.

Learn how to access financial data from local files as well as from internet sources.

Master GitHub Copilot to understand, write, and refine code with context, customization, and smart features.

Learn survey design using common design structures followed by visualizing and analyzing survey results.

Enhance your KNIME skills with our course on data transformation, column operations, and workflow optimization.

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

Learn business valuation with real-world applications and case studies using discounted cash flows (DCF).

Learn how computers work, design efficient algorithms, and explore computational theory to solve real-world problems.

In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.

Learn how to produce interactive web maps with ease using leaflet.

Learn how to load, transform, and transcribe speech from raw audio files in Python.

Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

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

Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.

Learn how to efficiently collect and download data from any website using R.

Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.

Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.