Introduction to Analytics and AI

  • Overview
  • Why Choose a Certificate?

Program Administrator

Contact for program-related questions Joel Sokol
Overview

Introduction to Analytics and AI

Be sure to review program requirements for this certificate

Analytics and AI are transforming how organizations understand data, generate predictions, and make decisions. The Introduction to Analytics and AI Certificate helps learners understand many different analytics and AI approaches, so they know how to choose and build the right models, datasets, and techniques to solve a problem or answer a question. Participants will then gain hands-on practice implementing these solutions using common industry tools. Learners will deepen their expertise in specific methods, such as machine learning, optimization, statistical learning, and modern regression, based on their choice of elective courses. To earn the Analytics and AI Certificate, learners must complete COMP 2001P: Analytics and AI: Introduction (Requirement A) followed by two of the four course options listed under Requirement B below.

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Why Choose a Certificate?

Why Choose a Certificate?

Professional Certificates are ideal for developing new skills and building deep expertise in a specialized area to update your professional profile, advance your career, or broaden your knowledge base.

Certificates are an “anytime” credential
Start anytime - after graduation or later in your career - and gain deeper know-how in a specific area without the commitment to a degree.

Certificates demonstrate commitment
The dedication of time to earn a certificate demonstrates that you are committed to achieving a higher standard of professional knowledge in your industry.

Certificates provide immediate “ROE”
Georgia Tech learners master real-world skills and apply them to their career the day after completion.

Certificates stand out on your resume
A Georgia Tech credential carries the professional weight to give you a competitive edge.

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What You Will Learn

  • Analytics/AI models for answering important data-driven questions, making predictions, and supporting decision-making
  • Data science-based approaches for classification, clustering, change detection, time-series and feature-based relationship analysis and prediction, and feature selection
  • Decision-support approaches like optimization and simulation
  • Cross-cutting techniques for data preparation, validation, experiment design, and missing data response
  • Practical implementation using software and coding
  • State-of-the-art techniques in machine learning, optimization, statistical learning, and modern regression
Woman sits in front of three monitors reviewing Python code with her male coworker for the FlexStack in Python AI Principles Certificate.

How You Will Benefit

  • Apply analytics and AI models to understand data, generate predictions, and make decisions.
  • Learn how to choose or create the right models, datasets, and techniques to address questions and challenges.
  • Practice implementing analytics/AI approaches using common industry tools.
  • Obtain deeper practical skills and knowledge in specific analytics and AI approaches like machine learning, optimization, statistical learning, and modern regression.
  • Stay competitive as the field evolves by learning how to understand new models and techniques more quickly.
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    Grow Your Professional Network
  • Taught by Experts in the Field icon
    Taught by Experts in the Field

Course Offerings

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