This course covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases.
NumPy, pandas, Matplotlib, scikit-learn; Python REPLs; Jupyter Notebooks; Data analytics life-cycle phases; Data repairing and normalizing; Data aggregation and grouping; Data visualization; Data science algorithms for supervised and unsupervised; Machine Learning.
Online LIVE - 2 Days
Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming and also be familiar with Python.