The Data Analysis Certification is an accreditation that endorses you both for the knowledge and practical application of best practices used in analyzing statistical data.
The certification is the result of a complex, experiential learning program that has 3 sections: pre-course activities, core-course exercises and post-course assignments.
You will acquire the tools and skills needed to develop complex data analysis, useful for the processing and interpretation of data and relevant for your company's profile.
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Bonus: Premium subscription on smartKPIs.com - Available for 6 months, providing access to 500 fully documented KPIs and over 20.000 KPIs enlisted and one research report from the Top 25 KPIs series.
The course is designed for anyone who has basic mathematical training and basic competences in using Microsoft Excel. Statistical knowledge, intermediate or advanced knowledge of Excel, practical experience with data analysis and related duties are not necessary.
The course is addressed to Managers, HR Representatives, Analysts, Auditors or Logistics and Acquisitions Experts, as well as to professionals from other business areas, who deal with data analysis.
The course is ideal for those interested in pursuing career opportunities in data analysis, data modelling and related activities (e.g. campaign management, data mining, statistics, risk management, reporting, data processing for survey analysis etc.)
Adrian Otoiu gained more than 15 years of experience in statistical, economic and business analysis in various roles within the government, academic organizations and multinational corporations.
Throughout his experience, he has garnered work expertise and had undergone training in the following fields: labor market, health economics, migration, quantitative marketing - including online surveys, composite indicators, default and risk models, business analytics and business intelligence, data preparation and processing, teaching and coaching.
The work he has been performing includes doing statistical analysis by using the following main methods: regression analysis, including logistic analysis, panel data/hierarchical models, factor and PCA analysis, Bayesian regression analysis, cluster analysis, market basket analysis, decision trees, and natural language processing. Adrian has supplemented his process portfolio by adding data analysis and reports targeted at specific needs, including industry and competition analyses, SWOT and SBP studies, government briefings and notes, and academic paper and conference proceedings, retrieval of specialized data from various sources, presentation of results to non-specialized audiences and fact-finding for high-level analyses.
These skills and abilities are supported by extensive experience and training in SAS and R, machine learning and modelling methods, backed by constant contact with the academia either in the form of hands-on research, continuous training offered by SAS and Johns Hopkins University Data Science program, and through teaching statistics and quantitative methods.
You can communicate with your instructor through the eLearning forum or by email. You are highly encouraged to use these ways of communications.
Operating Systems: Windows 7 and newer, Mac OSX 10.6 and newer, Linux - chromeOS.