- Understand a wide variety of learning algorithms.
- Understand how to evaluate models generated from data.
- Apply the algorithms to a real problem
- optimize the models learned and report on the expected accuracy that can be achieved by applying the models
- Ability to learn new machine learning and deep learning algorithms
- Good knowledge of Statistics and modeling
- Familiarity with the programming languages
- Ability to write algorithms to find patterns and learning
- Good analytical skills
- Working computer
- Willingness to learn
- Internet
You will be introduced to a wide range of Machine Learning (ML)
methods and AI based approaches, acquiring skills that are directly
translatable for a career in data Science in industry today. You will
learn how to develop and implement a full ML pipeline, from processing
raw data to training an advanced model for a particular task.
The
course will cover both the theoretical and practical applications of
these methods. The theoretical elements will provide a good and solid
foundation, followed then by practical lab sessions to give you the
confidence to use these methods on a wide range of applications in
different careers.
This course is specifically designed to meet the current needs of the market and give you skills that make you attractive to employers and to pursue a career in data science.
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