GLOBAL STARTUP LABS

Montevideo, Uruguay  

    Hosts
    Partners & Donors
    • Plan Ceibal
    • JWEL
    • AWS

    Location

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    IAP

    A 4 weeks hands-on workshop, led by grad students mentors, focused on developing technical and business knowledge/skills in the field of data science and machine learning. 

    OBJECTIVES

    • Recognize, manipulate and apply to a basic level a variety of machine learning techniques.
    • Understand the current and future business opportunities in the fields of machine learning and data science.
    • Develop entrepreneurship and intrapreneurship skills.
    • Develop effective communication skills for Data Science-related pitch.
    • Promote a space to build working teams in the community of data scientists. 

    CORE ELEMENTS

    • First module/week: Assessing the learners’ Python skills and machine learning knowledge, introducing the fundamental concepts of machine learning and its applications in industry.  Students will learn strategies for ideation, particularly for data science and machine learning applications, and receive an initial look at three specific industries that we will cover in the remainder of the course – e-commerce, healthcare, and finance.
    • Second module/week: Understanding machine learning techniques for e-commerce and its current and future applications in industry. After learning the business aspects of machine learning applied to e-commerce, students will gain the tools to effectively communicate as a team and persuade an audience both with and without data.
    • Third module/week: Understanding machine learning techniques in Healthcare and its applications in the field. students will learn and apply considerations in determining decision-making units within an organization and how to navigate implementation. 
    • Fourth module/week: Machine Learning techniques in the Financial industry, and its current and future applications in finances. Students will have two days to work on their own projects, finalizing with a pitch competition on Friday.