Advanced Tools and Techniques for Data Analysis (Live Online)

Overview

Enhance your analytical skills with our 2-day online seminar focused on advanced data analysis techniques. Designed for business professionals, this course will teach you to implement predictive analytics in areas such as marketing, finance, and operations without requiring a background in statistics or programming.

Course Highlights:

• Develop insights using tools like histograms, ANOVA analysis, and A/B testing.
• Learn clustering, box plots, scatter diagrams, and partitioning techniques.
• Analyze unstructured text and apply multivariate regression analysis.

This hands-on course emphasizes practical application with tools like Google OpenRefine and Excel’s Analysis Tool Pack, facilitating complex data manipulation for valuable business insights.

Key Learning Outcomes:

• Enhanced data analytics comprehension and application in business contexts.
• Data wrangling, cleansing, and shaping expertise.
• Hands-on experience with multivariate statistics, T-Test, and factor analysis.
• Practical knowledge of JMP, Tableau, SPSS, and R for advanced analysis.

Benefits of Attending:

• Surpass traditional business intelligence methods.
• Confidently address complex data analysis challenges.
• Identify the appropriate analysis techniques for various business issues.
• Eliminate the need for a statistics degree to obtain conclusive results from diverse data sets.
• Gain insights from unstructured text through basic text analysis tools.
• Employ advanced functions in Excel and open-source tools to enhance analytics.
• Leverage a foundational understanding of spreadsheets for powerful analytical applications.

Who Should Attend:

This seminar is ideal for business professionals seeking effective data analysis tools to tackle challenges such as customer churn, web-page optimization, and online customer feedback analysis.

Categories:

Data Analysis Courses, Business Intelligence Courses, Predictive Analytics Courses, A/B Testing Courses, ANOVA Courses, Clustering Courses.

Subjects