Opetussuunnitelmat

Opetussuunnitelma

Osaamisalueet

Tietoa koulutuksesta

Description

IN00CR47	Basics of Machine Learning (5 cr)
Prerequisites	Not applicable
Objectives	• A student knows what machine learning can do and what it can not do. Student knows some topical machine learning solutions. • A student knows what mathematics is typically required for implementing machine learning solutions and student can implement matrix multiplication and gradient decent algorithm with Python. • A student knows what tools are available for machine learning solutions and student can implement simple Python programs using numPy and Matplotlib Python modules. • A student understands how neural network is used to identify numbers from gray scale pictures.
Content	• Introduction to machine learning • Mathematics (matrices, derivative and gradient) for understanding how machines learn • Programming tools (Python) for implementing machine learning algorithms • Machine learning "hello world" algorithm for identifying numbers from gray scale pictures with neural network.
Recommended optional programme components	If necessary, the student advisor will recommend optional programme components for each student based on their individual study plan.
Accomplishment methods	Not applicable
Execution methods	Not applicable
Materials	Not applicable
Literature	Not applicable
Evaluation Criteria	0-5
Evaluation Criteria
Assessment Frameworks	Arviointikehikko
Further Information	Not applicable
Responsible persons	Not applicable
Links	Arviointikehikko

Implementations

No implementations.