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Strategies and Concepts for Data Scientists and Business Analysts

GK# 2487

Course Overview

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To be effective in a competitive business environment, analytics professionals need to use descriptive, predictive, and prescriptive analytics to translate information into decisions. An effective analyst also should be able to identify the analytical tools and data structures to anticipate market trends.

In this course, you will gain the skills that data scientists and statistical business analysts must have to succeed in today's data-driven economy. Learn about visualizing big data, how predictive modeling can help you find hidden nuggets, the importance of experiments in business, and the kind of value you can gain from unstructured data.

Schedule

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Outline

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Classroom Live Outline

1. Overview

  • Defining terms
  • Concepts of data science
  • Exploring and visualizing data

2. Segmentation

  • Pitfalls and good practices
  • Interpreting clusters

3. Predictive Modeling

  • Fundamentals
  • Decision trees
  • Random forests
  • Model comparison

4. Design of Experiments

  • Why experiment?
  • Types of business experiments

5. Unstructured Data

  • Text analytics
  • Social networks

6. Communicating Your Results

  • Knowing your audience
  • Creating effective messages
  • Demonstrating value

Labs

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Classroom Live Labs

Exercises or hands-on workshops are included with most SAS courses.

Prerequisites

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Who Should Attend

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Statisticians, market researchers, information technology professionals, data scientists, and business analysts who want to make better use of their data

Course Delivery

This course is available in the following formats:

Classroom Live

Receive face-to-face instruction at one of our training center locations.

Duration: 3 day

Virtual Classroom Live

Experience expert-led online training from the convenience of your home, office or anywhere with an internet connection.

Duration: 6 day

Request this course in a different delivery format.
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