Building AI Agents with Google ADK
Build a customer-support assistant step-by-step with Google’s Agent Development Kit (ADK).
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
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By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Build a customer-support assistant step-by-step with Google’s Agent Development Kit (ADK).
Building on your foundational Power Query in Excel knowledge, this intermediate course takes you to the next level of data transformation mastery
In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.
In this course, you will use T-SQL, the flavor of SQL used in Microsofts SQL Server for data analysis.
Master sampling to get more accurate statistics with less data.
Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.
Unlock BigQuerys power: grasp its fundamentals, execute queries, and optimize workflows for efficient data analysis.
Gain the essential skills using Scikit-learn, SHAP, and LIME to test and build transparent, trustworthy, and accountable AI systems.
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 to perform linear and logistic regression with multiple explanatory variables.
Dive into the world of machine learning and discover how to design, train, and deploy end-to-end 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.
Transform almost any dataset into a tidy format to make analysis easier.
In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.
Learn to create your own Python packages to make your code easier to use and share with others.
Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.
R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.
Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.
Learn Snowflake data types and functions to manipulate text, numbers, and dates while building custom functions and pivot tables.
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.
Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.
Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.
Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.
Learn to work with Plain Old Java Objects, master the Collections Framework, and handle exceptions like a pro, with logging to back it all up!
Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!
Learn to start developing deep learning models with Keras.