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Recruitment Machine Learning [UC Berkeley School of Information]

Purchase Information
Type of purchase: Collaborative
Price: 3000 USD
Participants: 0 of 100
Organizer: Missing
Status: A set of participants
Payment: 31.2 USD
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Staff member
Duration: 6 weeks (excluding orientation)
Companies using machine learning to optimize business processes and decision-making have distinct advantages over those that aren’t. By wielding machine learning technology to make business objectives more predictive and prescriptive, data-driven enterprises are redefining how to create and measure value. With the development of free, open-source machine learning and artificial intelligence tools, it’s never been easier for companies of all sizes to harness the power of data.
Effectively integrating machine learning applications into your business requires a practical understanding of its models. The Machine Learning online short course from the UC Berkeley School of Information (I School) aims to equip your workforce with the skills to understand the impact of machine learning and aptly communicate its integration. Your employees will learn to analyze the models, techniques, and ethical ramifications of machine learning applications, and present a business case for utilizing it in your organization.

Is this course for you?

The course aims to help your workforce understand how machine learning can be effectively used to problem-solve in your organization, providing the solutions to lead innovation to gain a competitive edge. Designed for mid- to senior-level managers eager to maximize team productivity and unlock new efficiencies, the course provides an operational perspective on the practical functioning of machine learning in business.
Both data-centric professionals and business executives will benefit from the expert-led modules and evidence-based approach. Those in technical or data-centric positions will gain tools to leverage and manage machine learning models. Business executives will learn to establish communication and collaboration between technical and business-oriented teams. No prior programming knowledge is required.