Data Analytics Microcredential

Required Topics

Data Preparation and Management 2/5/24 - 3/22/24 (Tuesdays, 7 to 8:30 p.m.)

This provides participants with the expertise needed to handle complex data challenges. It delves deep into the intricacies of gathering, processing, refining, and analyzing vast datasets, all illustrated through real-world case studies.

Key areas of focus include:

  1. Techniques for efficient data loading, transformation, merging, and reshaping.
  2. Advanced strategies for filtering and summarizing datasets to extract meaningful patterns.
  3. Hands-on challenges that allow participants to apply what they learn to genuine data analysis scenarios.
  4. In-depth instruction in Python or R programming languages, equipping participants with proficiency in the industry’s and public sector’s leading data analysis tools.

By the end of this module, participants will have a deep understanding of data preparation and management and will be equipped to address data-driven challenges in their specific fields effectively.

Digital Marketing Analytics 4/1/24 - 5/24/24
(Tuesdays, 7 to 8:30 p.m.)

This will immerse students in the fundamental principles and essential tools of digital marketing analytics.

Students will delve into the intricacies of Search Engine Optimization (SEO), learn about Google’s web analytics service, and master how to use social media analytical tools to interpret web traffic and engagement metrics on social media platforms. Students will also explore advanced techniques in search advertising and display advertising.

The module will conclude with a culminating experience where students will apply all the knowledge and skills acquired throughout the module to design and implement a digital marketing campaign and use analytics to inform their strategies.

Data Visualization 5/28/24 - 7/12/24

This focuses on building creative and technical skills to transform data into visual reports for effective communication. Students will learn to use software (e.g., PowerBI, Tableau) to extract, cleanse, prepare, and display financial and non-financial data.

Students will become familiar with exploratory and explanatory data visualization techniques for data storytelling. By the end of the module, students will know how to select the appropriate software and chart types to model and visualize data designed for effective communication with their target audience in mind.

Students will also become comfortable thinking visually and producing visual reports using interactive charts and dashboards. In addition, students will demonstrate confidence in their ability to prepare data and draw from design principles to communicate and persuade using storytelling with data.

Data Security and Ethics 7/15/24 - 8/30/24 

This explores the critical aspects of safeguarding data, preserving privacy, and making ethical decisions in the era of big data and interconnected systems.

Students will explore the principles, strategies, and best practices for securing data and ensuring ethical data handling. This course equips participants with the knowledge and skills required to navigate the complex landscape of data security and ethics, addressing contemporary challenges and solutions.

By the end of the module, students will be able to understand common data security threats and vulnerabilities and their implications, apply encryption techniques to secure data at rest and in transit effectively, analyze ethical considerations in data collection, processing, and decision-making, and address bias and fairness. Students will also be able to identify and mitigate common cybersecurity threats and develop incident response plans.

Topics are offered rotationally. Start from any topic to earn a skill badge, and complete all four to earn a micro-credential badge.


Each topic is $399.  

Total cost for microcredential = $1,596. 

Data Analytics Microcredential

The Data Analytics Microcredential is designed to help you master the techniques and build the skills to understand better and process data, make analytical predictions and forecasts, effectively communicate your analysis, and make sound strategic decisions by using data securely and ethically.

Our hybrid design enables you to learn most materials at your own pace but also have the opportunity to learn from course instructors and interact with peers virtually every week to deepen your understanding of course materials, obtain feedback on assignments and projects, and seek support from like-minded peers who are equally curious and passionate about data.


Quick Facts

  • Geneseo faculty members who are experts in the field provide weekly live lessons and recorded lectures.
  • Individual assignments, projects, and timely instructor feedback will strengthen your learning.
  • Business implications of analytics that allow you to draw business-relevant insights to apply to work.
  • Enhanced analytic and presentation skills that enable you to grow and shine in your career.
  • Credly badges that can be shared on LinkedIn for current and future employers.

Example Careers

  • Business Intelligence Analyst
  • Data Analytics Consultant
  • Data Scientist/Analyst/Engineer
  • Financial Analyst
  • IT Systems Analyst
  • Market Research Analyst
  • Operations Research Analyst
  • Quantitative Analyst
  • Project Manager
  • Social Media Analyst
  • Supply Chain Analyst
  • Transportation Logistics Specialist

Data analytics can be applied to virtually any field, but especially in business, consulting, banking, politics, agriculture and manufacturing. 

Contact Info

Joanna Santos-Smith

School of Business

Business Faculty