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.
or
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).
This course focuses on feature engineering and machine learning for time series data.
Learn about string manipulation and become a master at using regular expressions.
Create interactive data visualizations in Python using Plotly.
Gain the essential skills using Scikit-learn, SHAP, and LIME to test and build transparent, trustworthy, and accountable AI systems.
Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!
Build the foundation you need to think statistically and to speak the language of your data.
Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.
Build your OOP skills with descriptors, multilevel inheritance, and abstract base classes!
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 how to build intelligent agents that reason, act, and solve real-world tasks using Python.
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 to create your own Python packages to make your code easier to use and share with others.
Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.
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.
Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.
Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.
Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!
Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.
Learn to start developing deep learning models with Keras.
Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.
Learn about ARIMA models in Python and become an expert in time series analysis.
Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.
Learn techniques to extract useful information from text and process them into a format suitable for machine learning.
In this course, youll learn the basics of relational databases and how to interact with them.
Learn to manipulate and analyze flexibly structured data with MongoDB.
Learn how to design, automate, and monitor scalable forecasting pipelines in Python.