Chương trình học phân tích dữ liệu

Discussion in 'Tableau' started by bsdinsight, Jan 14, 2018 at 7:28 PM.

  1. bsdinsight

    bsdinsight Well-Known Member

    data science.png

    Data Science & Analytics

    Data science and data analytics are at the core of every modern globalized industry. Working in today's technology-centric workforce not only requires superior leadership skills, but the ability to translate data problems into the bigger picture for the organization.

    The Program Curiculum on Data Science and Analytics is a 6 -month learning journey into the world of applied data science and analytics. The program will prepare you with the tools to build and lead data science teams through data -driven decision-making. You will learn how to promote a data -driven culture, how to translate business problems, and how to lead a team with a diverse set of skill sets towards solving these problems.

    Participants graduate with Certificate Of Excellence in Data Analytics.

    Program Curriculum

    Module I

    A. Economic Analysis for Decision Making :
    1. Tools for competitive advantage
    2. Product-line pricing analysis
    3. Decision making under uncertainty
    4. Designing effective incentives
    B. Data and Decisions :
    1. Statistical analysis in managerial decision making
    2. Statistical methods to solve business problems
    3. Effective data visualization

    Module II Virtual Sessions
    • A.
      Applications with Live Case Studies/Debrief by faculty

    Module III


    A. Inference and measurement :
    1. Micro-econometric data analysis
    2. A/B Testing
    3. Experiments to increase profits
    B. Forecasting and trends :
    1. Predictive analysis
    2. Time Series forecasting and analysis
    Module IV Virtual Sessions

    A. Feedback on Group Projects

    B. Faculty check-in & Coaching


    Module V

    A. Machine Learning and Artificial Intelligence :
    1. Leverage ML and AI for business insights from big data
    2. Tools for Supervised Learning Methods
    3. Tools for Unsupervised Learning Methods
    B. Assembling a Data Science Team :
    1. Mapping of resources from expert backgrounds to solve problems
    2. Design a tech eco-system which complements the data science team

    Applications
    • Application to Banking, Healthcare, Insurance, Retail, Public Policy, and more
    • Industry Panels, including leaders from Silicon Valley Hi-Tech companies
    • Application to Marketing, Business Development, Product, Finance, and more
    • Capstone Project Presentations
     
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