Upskill your employees with efficient and up-to-date learning to move faster and increase their impact on your business.
Our unique approach makes our course content always up-to-date to ensure your employees learn skills relevant to your business strategy.
Our courses offer a hybrid learning approach, combining self-paced online learning with live virtual instruction. Employees to have the flexibility to learn at their own pace and on their own schedule, while also providing the opportunity for real-time interaction and support from instructors.
The live virtual instruction is delivered through engaging video lectures and discussions, allowing students to ask questions and participate in discussions with their peers and instructors.
Employees receive a tailored and effective learning experience. This ensures that employees are able to fully understand and retain the material, leading to higher engagement and success rates.
Additionally, our AI-powered solution is able to provide personalized recommendations for additional resources and exercises to further support the employee's learning journey.
Relevant, up-to-date courses to help your company move faster and be more innovative. Our courses are both self-paced and live by world-class instructors (once per quarter for live courses) with regular office hours, hands-on labs and guest speakers.
Get in touchThis course covers the use of machine learning and stream processing for real-time data analysis and decision-making. Students will learn how to apply machine learning models to data streams and build efficient, real-time systems using stream processing frameworks. The focus is on techniques for handling large volumes of data with low latency.
A course that teaches students the theory and methods used to infer causal relationships from observational data. The course will cover topics such as potential outcomes, propensity score matching, and instrumental variables, as well as more advanced methods such as causal graphical models and Bayesian causal inference. The course will also discuss the assumptions and limitations of different causal inference methods and their applications in various fields.
A course on operationalizing machine learning models in a production environment, including topics such as model deployment, monitoring, and maintenance.
A course teaching advanced skills in SQL for designing and managing complex database systems and writing efficient queries.
A course teaching advanced skills in SQL for designing and managing complex database systems and writing efficient queries.
A course for leaders on how to ensure the quality of data and data-driven processes, including topics such as data governance, data quality standards, and data quality metrics.
A course for data producers on how to ensure the quality of data that they produce, including topics such as data cleansing, data validation, and data quality metrics.
A course on the data mesh approach to data management, which emphasizes decentralized ownership and governance of data assets, and a focus on data as a product. The course covers topics such as data ownership and accountability, data governance frameworks, and data product development.
A course on generating synthetic data and using generative AI techniques to create realistic, machine-generated data for a variety of purposes such as training machine learning models, testing software, and simulating scenarios. The course will cover topics such as synthetic data generation methods, generative models, and the ethical considerations of using synthetic data.
A course on the ethical considerations involved in the development and deployment of artificial intelligence systems. The course will cover topics such as bias in AI, the impact of AI on society, and ethical frameworks for AI development.
$99/mo/employee
billed annually