Data Science Trainee

EPAM Campus offers a free Data Science training program designed to build market-oriented hard and soft skills alongside IT professionals.

Description

This intensive course covers statistics and data analysis, regression, classification, clustering, and neural network basics.

The program lasts approximately 4 months and requires approximately 15 hours of engagement per week. Completing the program does not guarantee a job, but it provides a solid foundation for entering the profession confidently.

Requirements

General requirements:

• Available to citizens and permanent residents of Poland
• Second-to-last or final-year university students and recent graduates
• Aged 18 years or older

Skills requirements:

• English level B2 (Upper-Intermediate) or higher
• Strong knowledge of Python, including NumPy and Pandas
• Proficiency in mathematical analysis: derivatives, integrals, and extrema of functions in multidimensional real space
• Linear algebra skills: vectors, matrices, tensors, linear equations, eigenvalues and eigenvectors, and quadratic forms
• Knowledge of probability theory: probability definitions, conditional probability, Bayes theorem, and expectation
• Statistics knowledge: basic concepts, hypothesis testing, likelihood, and distribution-parameter estimation
• Understanding of basic optimization concepts and methods: stationary points, Lagrange multipliers, and gradient descent
• Knowledge of data structures and algorithms, including sorting algorithms and algorithm complexity

Nice to have:

• Polish fluency at C1 (Advanced) level or higher

Benefits

• Industry-focused learning
• Free access to practitioner-designed and regularly refreshed materials and resources
• Intensive hands-on training through practical assignments
• Regular guidance and actionable feedback from professionals
• Modern educational ecosystem with built-in AI tools
• Certificate of completion upon successfully fulfilling all certification requirements
• Opportunity to join the team after successfully completing all stages