Data Science

If you are curious about how you can connect your strong math skills with programming and pave your way in the data-driven world, then this program is for you.

Registration Closes: September 19, 2025

Program Start: November 2025

Program Duration: 30 weeks

What will you learn?


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

• Basic Engineering
• Basic Statistics
• Exploratory Data Analysis
• Regression
• Classification
• Clustering
• Deep Learning Foundation
• Business + Advanced Data Science Overview
• Basic Machine Learning Engineering (MLE)
  
  
  

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

• You will immerse yourself in one of the mentoring programs:
• Computer Vision
• Natural Language Processing
• Machine Learning Engineering
• Time Series
• Recommendation Systems
  
  
  

Program Offerings:


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

What do we require?


Skills requirements:

• 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)
  
  
  

The program start date may change, so the selection period may be adjusted accordingly. Please regularly check for updates on this page and via email.

This educational program is completely free of charge and will be held online.

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.