Explore how the Career Empowerment Center transformed opportunities and outcomes this past year through our 2024–25 Annual Report.

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Information Technology

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CEC Kicks Off Fall 2025 with Handshake Career Trek

The CSUEB Career Empowerment Center (CEC) kicked off the Fall 2025 semester with its first Career Trek of the semester. A visit to Handshake, the university’s primary career platform and a leading connector between students and employers nationwide. Partnering with …

By Rachel Ticas
Rachel Ticas Experiential Learning Coordinator
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Public Service and Business Career and Internship Fair

Over 450 students seized the chance to meet with 55+ employers who attended the Cal State East Bay Career Empowerment Center’s Public Service and Business Career and Internship on March 13, 2025.  The career fair featured employers like Lawrence Livermore …

By Danielle Islas
Danielle Islas
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LinkedIn Learning

Machine Learning with Python: Foundations

Taught by Frederick Nwanganga
You’ve probably heard about machine learning before, but have you ever wondered what that term really means? How does a…

Security Risks in AI and Machine Learning: Categorizing Attacks and Failure Modes

Taught by Diana Kelley
Like any software or process, machine learning (ML) is vulnerable to attack. In order to protect something, you must first…

Recommendation Systems: A Practical Hands-On Introduction

Taught by Miguel González-Fierro
Recommendation systems are among the most profitable artificial intelligence solutions you can deploy, for the simple fact that they can…

Machine Learning and AI Foundations: Advanced Decision Trees with KNIME

Taught by Keith McCormick
Every year, it seems, there is a new hot trend in data science. One of the hottest predictive analytics algorithms…

Azure Machine Learning Development: Part 1

Taught by Zarina Meeran
Machine learning as a concept has been around for over 60 years, but as artificial intelligence becomes more and more…

Machine Learning Foundations: Linear Algebra

Taught by Terezija Semenski
Ever wondered what’s really going on underneath a machine learning algorithm? The answer is linear algebra. Without it, machine learning…

Machine Learning and AI Foundations: Causal Inference and Modeling

Taught by Keith McCormick
This course with instructor Keith McCormick provides an introduction to some advanced techniques in causal inference and causal modeling. It…

Time Series Modeling in Excel, R, and Power BI

Taught by Helen Wall
The use of time series models has become a central topic in today’s data science world. In this course, instructor…

Azure AI Fundamentals (AI-900) Cert Prep: 2 Principles of Machine Learning on Azure

Taught by Emilio Melo
AI and machine learning are no longer a distant dream. All over the world, companies are turning to cloud technologies…

Self-Supervised Machine Learning

Taught by Janani Ravi
Are you a programmer looking to expand your model building skills in hopes of gathering more information from the data…

Machine Learning and AI Foundations: Decision Trees with KNIME

Taught by Keith McCormick
Suggested prerequisites General familiarity with supervised machine learning Understanding of terms such as target variable, input variable, algorithm, and train/test…

Machine Learning and AI Foundations: Decision Trees with SPSS

Taught by Keith McCormick
Many data science specialists are looking to pivot toward focusing on machine learning. This course covers the essentials of machine…

Introduction to Machine Learning with KNIME

Taught by Keith McCormick
KNIME is an open-source workbench-style tool for predictive analytics and machine learning. It is highly compatible with numerous data science…

Advanced Predictive Modeling: Mastering Ensembles and Metamodeling

Taught by Keith McCormick
Ensembles involve groups of models working together to make more accurate predictions. When creating complete deployed solutions, data scientists may…

Executive Guide to Predictive Modeling Strategy at Scale

Taught by Keith McCormick
Building world-class predictive analytics solutions requires recognizing that the challenges of scale and sample size fluctuate greatly at different stages…

Deploying Scalable Machine Learning for Data Science

Taught by Dan Sullivan
Machine learning models often run in complex production environments that can adapt to the ebb and flow of big data.…

Cognitive Technologies: The Real Opportunities for Business

Taught by Deloitte Insights
Cognitive technologies such as artificial intelligence and robotics are changing how businesses operate and the nature of work as we…

Machine Learning & AI Foundations: Linear Regression

Taught by Keith McCormick
Having a solid understanding of linear regression—a method of modeling the relationship between one dependent variable and one to several…

Machine Learning and AI Foundations: Clustering and Association

Taught by Keith McCormick
Unsupervised learning is a type of machine learning where algorithms parse unlabeled data. The focus is not on sorting data…

Machine Learning and AI Foundations: Classification Modeling

Taught by Keith McCormick
One type of problem absolutely dominates machine learning and artificial intelligence: classification. Binary classification, the predominant method, sorts data into…
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