Types of FDE Take-Home Assignments
Examine common take-home assignment formats, including data pipelines, API integrations, LLM applications, and written case studies. Identify the initial evidence required for each format. Learn to account for required deliverables, time constraints, submission requirements, and permitted assistance when planning your approach. Use these constraints to determine the appropriate first steps for each assignment.
Before selecting tools, identify the two required deliverables: a working integration and a written handoff. Choosing a dashboard framework before reviewing the deliverables could waste time on unnecessary implementation work.
Reconcile purchase order data from the provided supplier sandbox API against the warehouse CSV and generate a report of the results. Submit a private code repository, the reconciliation report, a README file, and a client email limited to 250 words. Limit active work to four hours and submit all deliverables within five calendar days.
Plan your approach around the required functionality, submission artifacts, time limits, and permitted tools or assistance. Assignments with similar goals may require different implementation approaches and initial priorities.
The following fictional assignments, time limits, and individual work plans are illustrative examples, not employer-defined requirements.
How formats differ
An assignment format defines the type of work required. These categories help identify the initial evidence to produce. They may overlap and do not dictate a specific architecture.
Data pipeline: Combining shipment CSV files requires transforming the provided data into validated outputs. Start by generating a reconciled dataset that identifies rejected records and flags missing or invalid data.
API integration: Retrieving supplier orders requires handling interactions with an external API. First, validate a basic end-to-end API request and response flow, including error handling. This helps reviewers distinguish successful requests from partial or failed data retrieval.
LLM application: A document Q&A application requires evidence that its answers are grounded in the source documents. Start by generating ...