AI Engineering Take-Home Assignments

Hosted by Alexey Grigorev

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752 students

In this video

00:00:00 Introduction and Webinar Series Overview
00:04:56 Deep Dive into AI Engineer Home Assignments
00:08:36 Setting Up the Q&A and Interactive Session
00:11:22 Analyzing Common Home Assignment Tasks
00:18:49 Audience Q&A on AI Engineering Roles
00:27:25 Defining the Live-Coding Task: Blood Test Analyzer
00:36:18 Project Scaffolding with an AI Assistant
00:48:52 Live Code Review and Refinement
01:00:11 Implementing and Running Application Tests
01:18:21 Strategies for Evaluation and Data Logging
01:23:29 Preparing for the Post-Assignment Deep Dive Interview
01:36:42 Live Demo: Testing with a German Blood Test Report
01:40:25 Conclusion and Final Remarks

What you'll learn

Home Assignments Analysis
Analyze very recent submissions and tasks from Q4 2025 and Q1 2026 to understand current AI hiring standards.
Implementation Discussion
Break down multiple real-world assignment prompts to discuss the most effective architectural approaches and trade-offs.
End-to-End Document Implementation
Build a complete solution for a document-instruction task, focusing on high-accuracy PDF parsing and data extraction.

Why this topic matters

The take-home assignment is where your ability to build production-ready systems is truly measured. By analyzing data from recent hiring cycles in late 2025 and early 2026, you’ll see what top-tier companies expect. You’ll move beyond understanding what is asked to mastering how it’s done, through deep discussion and a full end-to-end implementation of a complex document processing challenge.

You'll learn from

Alexey Grigorev
Principal Data Scientist | Book Author | Instructor to 100k+ Students World-Wide
Alexey Grigorev is the founder of DataTalks.Club and the creator of the popular Zoomcamp series. With 15 years of experience in software engineering and over 12 years in machine learning, he has built and deployed large-scale ML systems at companies like OLX Group and Simplaex.

An advocate for practical, hands-on education, Alexey has taught over 100,000 students, focusing on a code-first approach to help learners build real-world skills.

In the past, he was an active participant in data science competitions. A Kaggle Master, Alexey has achieved top rankings in several challenges, including 1st place in the NIPS'17 Criteo Challenge and 2nd place in the WSDM Cup 2017: Vandalism Detection.

He is also the author of several technical books, including the widely read Machine Learning Bookcamp.