This course runs for a duration of .
The class will run daily from 8:30 am CST to 4:30 pm CST.
Class Location: Houston - Houston, TX.
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This three-day course, organized into key topic areas, leverages straightforward business examples to explain practical techniques for understanding and reviewing data quality. You will learn how to make more informed, intelligent business decisions by analyzing data using Excel functions and the R programming language.
You will get an overview of data quality and data management, followed by foundational analysis and statistical techniques. Throughout the course, you will learn to communicate about data and findings to stakeholders who need to quickly make decisions that drive your organization forward.
In–Class Exercises, Demos, and Real-World Case Studies
This data analyst training class is a lively blend of expert instruction combined with hands-on exercises so you can practice new skills. Leave prepared to start performing practical analysis techniques the moment you return to work. Every Data Analysis Boot Camp instructor is a veteran consultant and data guru who will guide you through effective best practices and easily accessible technologies for working with your data. Through a combination of demonstrations and hands-on practice, you will learn to use data analysis techniques, which are typically the domain of expensive consultants.
Labs for this course are primarily in Microsoft Excel, however, students will get an opportunity to practice using R in some labs. Labs for this course can also be taught using the Python programming language for private onsite clients only.
In This Data Analysis Training Course, You Will:
Who Should Attend:
This data analysis training course is designed for the following professions:
Part 1: The Value and Challenges of Data-Driven Disruption
Part 2: Tying Data to Business Value
CLASS EXERCISE: Data-driven project checklist
LAB: Data analysis techniques: Aggregations
Part 3: Understanding Your Data
LAB: Prioritizing data quality
Part 4: Analyzing Data
LAB: Central Tendency
LAB: Feature Engineering
LAB: Univariate Linear Regression
LAB: Multivariate Linear Regression
LAB: Monte Carlo Simulation
Part 5: Thinking Critically About Your Analysis
Part 6: Data Analysis in the Real World
Part 7: Data Visualization & Reporting
Part 8: Hands-On Introduction to R and R Studio
LAB: Intro to R Studio
LAB: Univariate Linear Regression in R
LAB: Multivariate Linear Regression in R