Data, AI, and Cloud Courses

Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.

Explore data structures such as linked lists, stacks, queues, hash tables, and graphs; and search and sort algorithms!

Learn how to implement and schedule data engineering workflows.

Learn the fundamentals of working with big data with PySpark.

Start your reinforcement learning journey! Learn how agents can learn to solve environments through interactions.

What makes LLMs tick? Discover how transformers revolutionized text modeling and kickstarted the generative AI boom.

Master Python testing: Learn methods, create checks, and ensure error-free code with pytest and unittest.

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

This course focuses on feature engineering and machine learning for time series data.

Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.

Master Git’s advanced features to streamline data science and engineering workflows, from complex merging to large-scale project optimization.

Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.

Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.

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

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!

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

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

Learn about ARIMA models in Python and become an expert in time series analysis.

Prepare for your next coding interviews in Python.

Learn how to make GenAI models truly reflect human values while gaining hands-on experience with advanced LLMs.

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.

Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

Learn how to approach and win competitions on Kaggle.

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

In this course you will learn to fit hierarchical models with random effects.