Certifications

Cassie Kozyrkov introduces decision-making for leaders working in data-rich organizations. The course covers how people frame decisions, use data and technology, delegate with trust, improve organizational decision practices, and build a healthy data culture, with discussion of how AI and machine learning affect business decisions.

An introduction to enterprise large language models, technical protocols, and data privacy. Listed in LinkedIn Learning’s August 2024 AI catalog, this course was completed on August 20, 2024, with 15 minutes of course content.

Apply ISO 27001 risk management to AI systems, identify vulnerabilities, and adapt ISO 27002 controls. The course connects security monitoring and compliance work with the practical challenges of AI deployments and the standards developing around them.

A short course on using Microsoft Copilot with organizational data. LinkedIn Learning lists it in the April 2024 business-software catalog; the original certificate identifies Microsoft Copilot and artificial intelligence for business as its skills, with 18 minutes of course content.

Jerich Beason’s course focuses on securing generative AI in an organization. The original certificate identifies network security and generative AI as the skills covered, with completion on July 27, 2024, and 1 hour 15 minutes of course content.

Doug Rose explains the values and principles behind an agile mindset, then connects them to teamwork and iterative delivery. Learners explore user stories, cross-functional collaboration, responding to change, popular frameworks such as Scrum and Kanban, common team roles, and exercises for improving how teams work.

Fulya Kocak introduces environmental, social, and governance factors and why organizations address them. The course surveys foundational ESG concepts and risks, sustainable investing, the three ESG pillars, common measures, reporting and ratings, communication that avoids greenwashing, and skills relevant to ESG work.

Examine the role of privacy for individuals, businesses, and policymakers. The course uses concrete scenarios to connect responsible data use with organizational safeguards, the consequences of misuse, and the choices that help people protect their information.

Recognize common forms of unconscious bias and how they influence decisions and workplace relationships. The course develops awareness of personal assumptions and offers approaches for responding to bias when collaborating with colleagues and participating in an organization.

Explore how transformers support natural language processing and how major large language models evolved after GPT-3. The course connects model architecture, training approaches, and the contributions of different LLMs to practical choices for AI work.

Oz du Soleil introduces Excel macros as a way to automate repeated spreadsheet tasks. Learners see when a macro is useful, record and review a basic macro, and get oriented to VBA, the Developer tab, launching macros, and common limitations such as errors and the lack of an undo action.

Jonathan Fernandes explores the changes introduced by the GPT-4 release. The course appears in LinkedIn Learning’s guide to generative AI and prompt engineering, and the original certificate records completion on June 12, 2023.

Build a foundation in generative AI: how it works, how models create content, and where different model families fit. The course considers changes to creative work and employment alongside ethical responsibilities and the practical use of generative tools.

Khaulat Abdulhakeem introduces reinforcement learning concepts and the problems they can solve. The course covers core terminology, how to represent learning problems, Monte Carlo and temporal-difference methods, and extensions including deep, multi-agent, and inverse reinforcement learning.

Scott Duffy’s LinkedIn Learning course focuses on controlling Microsoft Azure costs. The original certificate records completion on April 4, 2023, with 1 hour 22 minutes of course content.

Lynn Langit surveys ways to monitor and manage Google Cloud spending across compute, data, networking, and serverless workloads. Learners explore billing reports and filtered cost views, then examine budgets, alerts, quotas, payment settings, committed-use discounts, and dashboards for tracking costs.

Lynn Langit explains how to forecast and manage AWS service costs using billing tools and operational practices. The course covers consolidated billing and alerts, cost controls for services such as EC2, S3, and RDS, and architectural choices that affect spending across common cloud workloads.

Harshit Tyagi introduces data engineering and its relationship to data science. Learners explore data wrangling, database schemas, distributed processing, tools including Hadoop, Hive, Spark, and Airflow, and the stages of building ETL pipelines to extract, transform, load, and schedule data.

Keith McCormick frames classification as a central machine-learning task and compares strategies for building predictive models. The course reviews model assessment, a range of classification algorithms, and practical challenges such as imbalanced categories, interactions, missing data, overfitting, and data reduction.