Live Session Instructor - AI for Data

About Ziplines

Ziplines Education is a category-leading education company that partners with universities to deliver industry-focused certificate courses that prepare professionals for today’s digital-first workforce. Each year, we have the opportunity to help thousands of career advancers build the knowledge, skills, and credentials they need to move their careers forward. 92% of learners would recommend our programs, and our net promoter score is consistently in the excellent range. Together, we empower adult learners to confidently pursue the career they’ve always wanted.

About the Course

AI for Data Analysis is a course on building a repeatable AI-enabled process for turning data into clear, defensible business recommendations.

Managers and operators are drowning in data. Dashboards multiply, metrics pile up, and teams debate instead of act. At the same time, AI has lowered the barrier to working with data, making analysis, visualization, and interpretation accessible to professionals who were never trained as analysts.

Designed for professionals (non-data analysts) who regularly work with dashboards, reports, and datasets, this course teaches a structured approach to moving from data to decisions. Learners will frame business problems, identify and query relevant data, direct AI through analytical investigations, and validate outputs—building the judgment needed to determine what is reliable, what is not, and what matters to the business.

Learners will move beyond basic prompting to develop core AI competencies for data-driven decision making, including structured problem framing, AI-assisted analysis, output validation, and translating insights into clear recommendations. These capabilities are applied within a repeatable workflow that can be reused across future business problems.

Through a hands-on, end-to-end case, learners build this system step by step, culminating in a configured, reusable Claude Project that supports real-world decision-making workflows.

By the end of the course, learners will leave the course with:

• A proven decision-making framework that they can apply to new business questions

• A reusable AI-powered system to accelerate future analysis and decision-making

About You

• 7+ years of experience in business analytics or a related field, with a strong understanding of industry trends and best practices

• Passionate about enabling self-service problem-solving and building confidence in using AI effectively

• Experience applying analytics across multiple industries (e.g., finance, healthcare, business operations, sales)

• Skilled at framing business challenges, structuring solutions, and integrating AI into analytical workflows

• Dedicated to helping others grow, with a focus on making analytical skills accessible to non-technical learners

• Able to guide learners toward practical understanding and real-world problem-solving

• Experienced in setting up and running analyses, including building the necessary artifacts to support projects

• Able to clearly explain the strengths and limitations of different LLMs (e.g., Claude, GPT, Gemini) for data analysis—including common failure modes like hallucinations, calculation errors, and misinterpretation—and ability to teach learners how to critically evaluate, validate, and effectively use AI outputs

• Stays current with the rapidly evolving AI landscape, with a strong commitment to continuous learning and a genuine passion for staying up to date on new tools, trends, and best practices

• Skilled in using tools such as:

  • Claude Projects (with an emphasis on demos)

  • Excel / Google Sheets

  • Gamma

  • Google Docs

• Strong communication and interpersonal skills, with the ability to connect with diverse learners

• Confident leading engaging, interactive sessions in a Zoom environment

• Highly organized and detail-oriented, with a strong commitment to preparation

• Able to deliver a high-quality learner experience across a full 5-week program

Instructor Role Objectives

• Fully complete the course in advance, gaining hands-on experience with all tools, workflows, and assignments to provide expert-level support to learners throughout the program.

• Help learners apply AI for data analytics skills through hands-on projects, guided builds, and real-world use cases.

• Support learners in troubleshooting, refining, and expanding on the course’s core exercises, demos, and