Data Science Trainee

EPAM Campus offers a free Data Science training program to help participants gain market-oriented hard and soft skills alongside IT professionals. In this intensive course, participants will study statistics and data analysis, regression, classification and clustering techniques, and neural network basics.

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

Requirements

General requirements:

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

Skills requirements:

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

Nice to have:

• Polish fluency at C1 (Advanced) level or higher

We offer

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