Online or onsite, instructor-led live Stata training courses demonstrate through interactive hands-on practice how to analyze large data sets for use cases such as economics, sociology, biomedicine, etc.
Stata training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Stata training can be carried out locally on customer premises in Poznan or in NobleProg corporate training centers in Poznan.
This instructor-led, live training in Poznan (online or onsite) is aimed at intermediate-level to advanced-level computer science professionals who wish to leverage Stata for statistical analysis and integrate it with R.
By the end of this training, participants will be able to:
Effectively use Stata for data analysis and statistical modeling.
Compare Stata’s functionalities with SPSS and R.
Integrate Stata with R for seamless statistical computing.
This instructor-led, live training in Poznan (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.
By the end of this training, participants will be able to:
Employ algorithms to buy and sell securities at specialized increments rapidly.
Reduce costs associated with trade using algorithmic trading.
Automatically monitor stock prices and place trades.
This instructor-led, live training in Poznan (online or onsite) is aimed at data analysts who wish to analyze large data sets with Stata.
By the end of this training, participants will be able to:
Create statistic models for predicting key interest variables and events.
Generate descriptive visualizations, summary tables, frequencies, and more.
Manage and structure large datasets, ready for data analysis.
This instructor-led, live training in (online or onsite) is aimed at data analysts who wish to use Stata and R to analyze big data for statistical analysis.
By the end of this training, participants will be able to:
Create statistic models for predicting key interest variables and events.
Generate descriptive visualizations, summary tables, frequencies, and more.
Manage and structure large databases to preapare for data analysis.
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Data management, reporting and statistics concepts.
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