Data Science is one of the most trending technologies at the intersection of mathematics, programming and business. YouTube video recommendations, machine translation, news aggregators, medical diagnostics, spam detection, credit scoring, self-driving cars – this is not even a complete list of areas where Data Science has become or is gradually becoming a part of our everyday lives.   

TRAINING PROCESS

The program lasts 20 weeks and embraces self-study training with lectures, practical homework and weekly Q&A sessions. You will work closely with our experienced trainers and mentors, who will navigate you through 12 educational modules. They focus on the practical study of Machine Learning algorithms using Python packages such as Pandas, NumPy, Sklearn, Gensim, NLTK and others. 

The training begins with basic engineering, installation and configuration of the Python environment. The main concepts are reinforced with a brief review of basic statistics. Then, as the first and most important step in any Data Science problem, students begin to work on data exploration.  

The following modules are dedicated to the classification problem, where we will provide you with some text processing tips. At the end of this training stage, students participate in a competition. 

The final modules are more advanced. You will dive deep into unsupervised algorithms for clustering and outlier detection problems, advanced regression models, time series analysis and deep learning issues. 

If you perform well in the first stage, we will invite you to continue your practice studies at the next intensive stage (it usually lasts 3 months).

WORK AT EPAM COMPANY

Program graduates who have completed all their homework and successfully presented the final project will be invited to a technical interview for EPAM company production projects. 

PROGRAM TIMELINE AND DETAILS:

• Registration end date: 7 October 2022
• Technical Assessment: 3 November 2022
• Training start date: 21 November 2022
• Format: online 
• Total program duration: 33 weeks
• 20 weeks of external self-study training with Q&A sessions, lectures, homework checking and discussions with mentors on weekly basis
• 13 weeks of the intensive practice in the Data Lab (deep learning in one of the program (Computer Vision / Natural Language Processing / Recommendation System / ML Engineering))