Machine Learning Engineer Interview Simulation
In this experience, you'll take on the role of a candidate interviewing for a Machine Learning Engineer position at a subscription streaming company. As part of the interview process, you're given a real business problem to solve: predicting which customers are about to churn, before they do. You'll build an end-to-end pipeline — exploring data, engineering features, training and evaluating a classification model, and generating churn probability predictions — using the same tools and techniques real ML teams use. Then you'll walk through your implementation in a simulated technical interview
Skills you'll learn
We may earn a commission if you enroll through our links — it never affects the price you pay.
Similar courses
Foundations of Artificial Intelligence
This course introduces learners to the core principles of artificial intelligence, including its history, definitions, and the role of data in AI. You’ll explore algorithms, specialized hardware, and delve into machine learning and deep learning fundamentals. Ethical considerations around AI, especially generative AI (GenAI), will also be discussed, ensuring you understand the broader impact AI has on society and the workforce. With clear explanations and real-world examples, the course ensures you not only learn theoretical concepts but also understand their practical implications. You’
All levels
H2O Gen AI Ecosystem Overview - Level 2
Expand your understanding of H2O's GenAI platform with the Ecosystem Overview - Level 2 course, presented by H2O's very own Sanyam Bhutani! This course provides an in-depth comprehensive exploration of the tools, applications, and methodologies tailored for artificial intelligence (AI) and machine learning (ML) within the H2O ecosystem. You will delve deeper into efficient data preparation techniques, advanced model training, deployment strategies, and real-time monitoring solutions, covering the full spectrum of all the capabilities available. Through engaging modules, you will soon master t
All levels
Six Sigma Tools for Analyze
This course will cover the Measure phase and portions of the Analyze phase of the Six Sigma DMAIC (Define, Measure, Analyze, Improve, and Control) process. You will learn about lean tools for process analysis, failure mode and effects analysis (FMEA), measurement system analysis (MSA) and gauge repeatability and reproducibility (GR&R), and you will be introduced to basic statistics. This course will outline useful measure and analysis phase tools and will give you an overview of statistics as they are related to the Six Sigma process. The statistics module will provide you with an overview o
All levels
Introduction to Image Generation
This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.
All levels