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Introduction to ML

400 000 ₸
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Allocated 5 Quotas

The Introduction to Machine Learning course aims to provide students with fundamental knowledge and practical skills in machine learning. The program covers all key stages — from programming in Python and data analysis to building and evaluating machine learning and deep learning models.

Special condition

No

Course details

level

For all

Study format

Hybrid

Start

October

Entrance exams

No

Duration, in weeks

27

Duration in academic hours

216

Education language

Russian

Classes days_of_week

Tuesday, Saturday

Teaching methodology

There are more practices than theories

Qualifications

Classes format

The Introduction to Machine Learning course aims to provide students with fundamental knowledge and practical skills in machine learning. The program covers all key stages — from programming in Python and data analysis to building and evaluating machine learning and deep learning models.

Skills


Key Skills: Grasp key concepts and principles of machine learning, including task types (regression, classification, clustering), model building stages, and the ML project lifecycle Learn essential ML algorithms such as linear regression, KNN, decision trees, random forest, gradient boosting, k-means, PCA, and basic neural networks Master key steps in working with data: collection, cleaning, preprocessing, feature transformation, visualization, analysis, and preparation for modeling Program in Python for data analysis Work with libraries like Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn

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