Requirements

Expected technologies

Python

NumPy

Pandas

Our requirements

• Second-to-last or final year university students and recent graduates
• Individuals aged 18 years and older
• English level B2 (Upper-Intermediate) or higher
• Proficiency in mathematical analysis (main topics of derivatives, integrals, extrema of functions in multidimensional real space)
• Skills in linear algebra (vectors, matrices, tensors, linear equations, eigenvalues and eigenvectors, quadratic forms)
• Knowledge of probability theory (definition of probability, conditional probability, Bayes theorem, expectation)
• Command of statistics (basic concepts, hypothesis testing, concept of likelihood, estimation of distribution parameter)
• Understanding of basic optimization concepts and methods (stationary points, Lagrange multipliers, gradient descent)
• Knowledge of data structures and algorithms (sorting algorithms, algorithm complexity)
• Familiarity with Python fundamentals (NumPy and Pandas in particular)

Your responsibilities

Data Science is a promising IT area that lies at the intersection of math, statistics, programming and domain expertise and helps get valuable data insights.

Training process

The program is designed to guide you through two engaging stages:

Stage 1: Fundamentals (3 months with ~12 hours per week)

In this stage, you'll build a strong foundation in Data Science. Here's what to expect:

Weekly learning. Explore video lessons and self-study materials, then practice through tasks and tests – all within set deadlines to ensure steady progress. Mentor guidance. Submit your weekly practical assignments for feedback and approval from expert mentors. Interactive support. Join weekly group Q&A sessions with professionals to discuss questions and deepen your understanding.

Perform well to pass the technical interview and advance to the next level!

Stage 2: Specialization (3.5 months with ~20 hours per week)

This stage is all about taking your skills to the advanced level with a more intensive approach. You will join one of the proposed mentoring programs:

Computer Vision Natural Language Processing Machine Learning Engineering Time Series Recommendation Systems By the end, you'll acquire job-ready skills to tackle real-world data challenges confidently.