Data, AI, and Cloud Courses

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

Apply PyTorch to images and use deep learning models for object detection with bounding boxes and image segmentation generation.

Gain the essential skills using Scikit-learn, SHAP, and LIME to test and build transparent, trustworthy, and accountable AI systems.

Learn how to design Power BI visualizations and reports with users in mind.

Learn how to perform financial analysis in Power BI or apply any existing financial skills using Power BI data visualizations.

Learn about Large Language Models (LLMs) and how they are reshaping the business world.

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Learn how to create pivot tables and quickly organize thousands of data points with just a few clicks.

Create new features to improve the performance of your Machine Learning models.

Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.

Master AWS security, governance, and cost optimization to prepare for the Cloud Practitioner certification.

Learn to use the KNIME Analytics Platform for data access, cleaning, and analysis with a no-code/low-code approach.

Conquer NoSQL and supercharge data workflows. Learn Snowflake to work with big data, Postgres JSON for handling document data, and Redis for key-value data.

In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.

Learn how to blend business, data, and AI, and set goals to drive success with an effectively scalable AI Strategy.

Master strategic data management for business excellence.

Learn how to use GPT tools responsibly and confidently. Discover how these tools work and techniques for writing prompts and evaluating outputs.

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

Learn how to clean data with Apache Spark in Python.

In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!

Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.

Master data preparation, cleaning, and analysis in Alteryx Designer, whether you are a new or seasoned analyst.

Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!

In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.

Build your OOP skills with descriptors, multilevel inheritance, and abstract base classes!

Master the key concepts of data management, from life cycle stages to security and governance.