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Management’s Guide to Data Science

Who Should Attend?

CORPORATE ADMINISTRATOR, BUSINESS MANAGER

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Duration: 1 Day

This introductory course seeks to expose business managers and corporate administrator to the world of data science and its application to enhance business performance and facilitate better information processing and business decision making. This course will be beneficial to personnel involved in strategic business planning, corporate planning and finance.

  • Expose to the world of data science
  • Understand the application of data science to enhance business performance
  • Understand how data science facilitate better information processing
  • Understand how data science enhance business decision making
  1. What is Data Science?
    • Customer Segmentation Workflow
    • Building a Customer Service Chatbot
    • Improving OKRs
    • Applications of Data Science
    • Assigning Data Science Projects
    • Investment Research
    • Building a Data Science Team
    • Interpreting a Team Sprint
    • Editing a Job Posting
    • Matching Skills to Jobs
    • Classifying Data TasksWhat is Data Science?
  2. Data Collection and Storage
    • Data Sources and Risks
    • Classifying Data for Security
    • Creating Web Data Events
    • Protecting PII
    • Solicited Data
    • Identifying Question Purpose
    • Validating Focus Group Feedback
    • Net Promoter Score
    • Collecting Additional Data
    • Sorting Data Sources
    • Asthma Frequency
    • Data Storage and Retrieval
    • Cloud Platforms
    • Querying a Database
    • Which Type of Database?
  3. Analysis and Visualization
    • Dashboards
    • Classifying Dashboard Elements
    • Improving a Dashboard
    • Choosing the Right Dashboard
    • Ad Hoc Analysis
    • Filling Out an Ad Hoc Request
    • Classifying Requests
    • A/B Testing
    • Creating an A/B Testing Workflow
    • Sample Size
    • Intermediate Results
  4. Prediction
    • Supervised Machine Learning
    • When to Use Supervised Learning?
    • Features and Labels
    • Model Evaluation
    • Clustering
    • Supervised vs Unsupervised
    • Cluster Size Selection
    • Special Topics in Machine Learning
    • Classifying Machine Learning Tasks
    • Sentiment Analysis
    • Deep Learning and Explainable AI
    • Finding the Correct Solution
    • Should I Use Deep Learning?

Register Now

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