Datacamp – Associate AI Engineer for Data Scientists 2025-2

Apr 18, 2025 - 09:11

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Associate AI Engineer for Data Scientists, Begin building AI solutions and gain the career-building skills you need to succeed as an AI Engineer, from model development to deployment into production! In this track, you’ll train and evaluate robust predictive models on real-world datasets across a variety of domains. Starting with the fundamentals of machine learning, you’ll get hands-on with some of the most popular Python libraries for machine learning and deep learning, including scikit-learn, PyTorch, and many more. As you progress, you’ll get hands-on with Large Language Models (LLMs) for a variety of natural language tasks. You’ll learn to fine-tune Llama 3 on custom data and integrate this into a LangChain application to begin surfacing predictions to end-users. Finally, you’ll discover what it takes to move an AI model from a notebook into production. You’ll build foundational skills in MLOps, including testing, version control, and monitoring performance in production.

What you’ll learn

Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this interactive course and learn how to make powerful predictions!
Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.
Learn how to build your first neural network, adjust hyperparameters, and tackle classification and regression problems in PyTorch.
Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.
Learn the theory behind responsibly managing your data for any AI project, from start to finish and beyond.
Learn the nuts and bolts of LLMs and the revolutionary transformer architecture they are based on!