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DataBoom

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AI Engineer & Data Analyst (Python, DS, ML, AI) Level 2 Middle (for continuing students)

400 000 ₸
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Allocated 10 Quotas

About course

More on DataBoom

An advanced program for analysts who want to move into Data Science and ML. You will delve into Python, study statistics for the analysis of distributions and patterns, master machine learning algorithms (regression, clustering, classification), and immerse yourself in neural networks and Deep Learning. All skills are practiced on applied tasks: demand forecasting, text and image recognition, and building recommendation systems. Suitable for those who want to become an ML engineer or an AI specialist.

Special condition

Guarantee fee in the amount of 100,000 tenge. No later than 7 (seven) working days before the start of training under the Agreement, the Student is obliged to make a deposit in the amount of 100,000 (one hundred thousand) tenge to the current account of the School specified in the Agreement. The deposit is returned to the Student within 10 (ten) working days after the successful completion of his studies under the Agreement.

Course details

level

Для повышения квалификации

Study format

Online

Start

September

Entrance exams

No

Duration, in weeks

26

Duration in academic hours

347

Education language

Russian

Classes days_of_week

Mon-Sun

Teaching methodology

There are more practices than theories

Qualifications

Middle AI Data Analyst with Power BI, Excel, AI skills

Classes format

Online lessons 2 times a week for an hour and pre-recorded video assignments on the platform, office hours: constant communication with a personal mentor certified by Microsoft, career consultations with HR once a week for an hour.

Skills


TechOrda #4. AI Engineer & Data Analyst (Python, DS, ML, AI) Level 2 Middle (for intermediate) consists of 4 modules: 1. PYTHON FOR AI-POWERED DATA ANALYSIS: The student will master the basics of Python programming, including variables, lists, loops, conditionals, and dictionaries, as well as learn how to create functions and work with libraries for data analysis. They will learn how to process and combine data using Pandas, apply regular expressions to clean text, and visualize results using Matplotlib. 2. Basic Statistics with Python: The student will gain a solid foundation in applied statistics, including descriptive measures, distributions, correlations, and hypothesis testing, with practical use of Python. They will also master the basics of regression analysis and learn how to visualize and interpret statistical inference for real-world data. 3. Data Science & Machine Learning based on Python: The student will master the entire Data Science cycle: from data preparation and exploratory analysis to building and evaluating classification, regression, and clustering models. They will learn how to apply machine learning in practice, create effective models, perform feature selection and dimensionality reduction using Python and popular libraries. 4. Artificial Intelligence and Deep Learning based on Python: the student will master key tools and services for creating AI applications: from speech generation, image and text processing to working with Azure OpenAI and AutoML. They will learn how to apply computer vision, NLP, and automatic learning technologies, and in the final, they will develop and defend their own AI project.

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