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How machine learning can make your organization more efficient?
It is estimated that 80% of the data processed in organisations is not in structured form. Machine learning enables this information to be brought into a structured form that opens new dimensions to software robotics in organisations.
Methods of Machine Learning –training provides you the understanding of how to utilize machine learning in business to achieve efficiency. You will learn all the key aspects:
- how it works
- what are the regulatory and ethical challenges
- how to find uses for it
- how to succeed in deployment projects
We will also discuss the requirements from various stakeholders such as end users, regulatory bodies, and organizations, which must be considered in projects. In addition, you will learn about the apps available on the market and their capabilities.
The training is held in english.
For whom is the training suited for?
People responsible for improving process efficiency, level C, business unit managers, specialists.
See other our similar trainings here.
UNDERSTAND
the opportunities from a business perspective
REALISE
the needs, requirements, and limitations of machine learning projects
KNOW
the different uses of machine learning
SEE
machine learning solution in action
Ohjelma
- Machine Learning and its different types
- Use cases of Machine Learning in different business scenarios
- Extracting Intelligence from Big Data
- Building and evaluating ML models
- Training, evaluating, and deploying an ML model
- Explainable Machine learning
- Machine learning applications and examples
- Challenges to Adoption of ML in day-to-day business.
- Constraints
- Requirements from various stakeholders
- Regulatory and ethical requirements
- What to consider building responsible services using machine learning
- Example responsible services
- Overview of different tools
- The differences between pricing models
- Machine learning and other technologies to streamline the overall process
- How to measure success?
- Machine learning solution in action
- Practice series: Analyze the ML use cases
Kouluttajat

Post-Doctoral Researcher, LUT University
Prabhat Kumar
Prabhat is currently working as a Post-Doctoral Researcher with the Department of Software Engineering, LUT School of Engineering Science, LUT University, Lappeenranta, Finland. He has many research contributions in the area of Machine Learning, Deep Learning, Federated Learning, Big Data Analytics, Cybersecurity, Blockchain, Cloud Computing, Internet of Things and Software Defined Networking. He has authored or coauthored over 20+ publications in high-ranked SCI journals.

Associate Professor at Software Engineering, LUT University
A.K.M Najmul Islam
Najmul Islam is an adjunct professor of Information Systems at Tampere University, Finland. He has received his PhD from the University of Turku, Finland, and M.Sc. from Tampere University of Technology, Finland. He has published in other highly ranked journals such as IEEE.
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