Data, AI, and Cloud Courses

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

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

Fine-tune Llama for custom tasks using TorchTune, and learn techniques for efficient fine-tuning such as quantization.

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

Master sampling to get more accurate statistics with less data.

Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.

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

Master multi-stage builds, Docker networking tools, and Docker Compose for optimal containerized applications!

Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.

Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

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

Step right into the dynamic world of data modeling with Snowflake!

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

Build the foundation you need to think statistically and to speak the language of your data.

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

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

Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.

Learn the theory behind responsibly managing your data for any AI project, from start to finish and beyond.

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

Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

Learn how to build interactive and insight-rich dashboards with Dash and Plotly.

Learn to perform linear and logistic regression with multiple explanatory variables.

Discover how the Pinecone vector database is revolutionizing AI application development!

Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.

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

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

Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

Analyze text data in R using the tidy framework.

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

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.