Branko Kovac

I am providing help and assistance to students of the Introduction to Data Science and Intermediate Data Science courses with learning R and Python and breaking into Data Science. In regular weekly video calls I am sharing my enthusiasm for data and trying to give career advice which can be useful for data science starters. Courses cover data wrangling, exploratory data analysis, feature engineering, statistics and Machine Learning algorithms (linear models, k-means, Random Forest, Naive Bayes).

During my internship at Academic Network of Serbia (AMRES) I was responsible for instalation and testing of open-source alternative to Splunk Enterprise, popular tool for real-time search, reporting and data analysis. That alternative consists of 3 separate tools: Fluentd - data collector and log management tool, Elasticsearch - real-time search engine and analytics engine, Kibana - GUI for Elasticsearch. Skills I practiced during my internship include: Linux administration, Rsyslog, RegEx.

Machine Learning and Artificial Intelligence Specialization; Exams taken: Artificial Intelligence, Soft-computing Methods, Data Mining, Computer Vision, Statistical Classification of Signals. Master Thesis: Telecommunication Links Fault Prediction using Random Forest algorithm.