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Building AI Skills in Your Engineering Team: A 2025 Guide to Upskilling with Impact

ODSC - Open Data Science

Whether an engineer is cleaning a dataset, building a recommendation engine, or troubleshooting LLM behavior, these cognitive skills form the bedrock of effective AI development. Engineers who can visualize data, explain outputs, and align their work with business objectives are consistently more valuable to theirteams.

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Top Artificial Intelligence AI Courses from Google

Marktechpost

Introduction to AI and Machine Learning on Google Cloud This course introduces Google Cloud’s AI and ML offerings for predictive and generative projects, covering technologies, products, and tools across the data-to-AI lifecycle.

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Track LLM model evaluation using Amazon SageMaker managed MLflow and FMEval

AWS Machine Learning Blog

This record-keeping allows developers and researchers to maintain consistency, reproduce results, and iterate on their work effectively. By documenting the specific model versions, fine-tuning parameters, and prompt engineering techniques employed, teams can better understand the factors contributing to their AI systems performance.

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FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning Blog

After the completion of the research phase, the data scientists need to collaborate with ML engineers to create automations for building (ML pipelines) and deploying models into production using CI/CD pipelines. These users need strong end-to-end ML and data science expertise and knowledge of model deployment and inference.

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TOP 20 AI CERTIFICATIONS TO ENROLL IN 2025

Towards AI

Professional Development Certificate in Applied AI by McGill UNIVERSITY The Professional Development Certificate in Applied AI from McGill is an appropriate advanced and practical program designed to equip professionals with actionable industry-relevant knowledge and skills required to be senior AI developers and the ranks.

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Choose Your Weapon: Survival Strategies for Depressed AI Consultants

Towards AI

As an AI practitioner, how do you feel about the recent AI developments? Besides your excitement for its new power, have you wondered how you can hold your position in the rapidly moving AI stream? One example is prompt engineering. Prompt engineering has proved to be very useful.

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Use your data to build your AI moat: The Future of Data-Centric AI 2023

Snorkel AI

Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023. The free virtual conference is the largest annual gathering of the data-centric AI community. Enterprise use cases: predictive AI, generative AI, NLP, computer vision, conversational AI.