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Data Science

850 000 ₸
Allocated 9 Quotas

The Data Science program is designed for professionals who want to advance their career in developing data-driven solutions for complex business problems. The course aims to teach participants the fundamentals of data science, including industry technologies such as machine learning, deep learning, data analysis using modern libraries, natural language processing, and graph neural networks.The program is suitable for both beginners and senior executives, including technical managers, business analysts, and data science enthusiasts. The level of academic/professional preparation in applied mathematics and statistics directly affects the efficiency and speed of learning. However, all participants can benefit maximally from this program.

Special condition

Additional Fees. Upon successful enrollment in the course, a prospective participant is required to pay the remaining amount of the course fee before the start of the training. The 6-month training costs 850,000 tenge, and the grant within the Tech Orda program amounts to 600,000 tenge. Thus, there is a remaining balance of 250,000 tenge that must be covered by the student.

Course details

level

For beginner

Study format

Online

Start

September

Entrance exams

No

Duration, in weeks

26

Duration in academic hours

156

Education language

Russian

Classes days_of_week

Tuesday, thursday, saturday

Teaching methodology

There are more practices than theories

Qualifications

Machine Learning Engineer, Data Scientist, Data Analyst

Classes format

Lessons are conducted online 3 times a week for 2 hours each

Skills


▸ Implement various machine learning techniques to solve complex problems and make data-driven business decisions.

▸ Understand the core areas of machine and deep learning, on elective tracks neural networks or computer vision.

▸ Solve various technical problems using algorithms and methods from data science.

▸ Choose how to represent data in forecasting.

▸ Have an industry portfolio of projects and experience in demonstrating your ability to extract useful information from data for the business.

▸ Select the most effective model for forecasting.

FAQ

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