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Python practice
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Python practice
Problems
Problems
9 problems for MLOps Engineer. Read any of them; sign in to code, run and submit.
All roles
Python Developer
DevOps Engineer
AI Engineer
Generative AI Engineer
Forward Deployed Engineer
Platform Engineer
Site Reliability Engineer
Cloud Engineer
AWS Engineer
Backend Engineer
Data Engineer
Machine Learning Engineer
MLOps Engineer
Kubernetes Engineer
Infrastructure Automation Engineer
Security Engineer / DevSecOps
Full Stack Engineer
Software Development Engineer
Automation Engineer
Solutions Architect
All levels
Beginner
Easy
Medium
Hard
Expert
All topics
Strings
Lists and tuples
Loops and control flow
Functions
Formatting output
Dates and times
Classes and objects
Dataclasses
Decorators
Dictionaries
Sets
Stacks and queues
Hashing
Heaps
Tries
Sorting
Graphs
Intervals
Binary search
Dynamic programming
Simulation and state machines
asyncio
Threads and concurrency
HTTP and REST APIs
Pagination
Rate limiting
Validation and schemas
Streaming responses
Files and configuration
Log analysis
Monitoring and alerting
Infrastructure as code
CI/CD automation
Security automation
Kubernetes
AWS SDK (Boto3-style)
IAM and policies
Vectors and embeddings
Retrieval-augmented generation
LLM integration
AI agents and tools
MCP and JSON-RPC
Model evaluation
JSON
Parsing text
Regular expressions
ETL pipelines
SQL patterns in Python
Statistics
Exceptions
Retries and backoff
Resilience patterns
Context managers
Testing and test data
Caching
Generators and laziness
Time and space complexity
Filter
Cumulative histogram buckets
Monitoring and alerting · Statistics
~10 min
Easy
Latest model version per stage
Dictionaries · Model evaluation
~10 min
Easy
Alert on error-rate windows
Monitoring and alerting · Intervals · Simulation and state machines
~25 min
Medium
Decide whether to promote a canary
Monitoring and alerting · Statistics
~20 min
Medium
Scale features for a model
Statistics · Vectors and embeddings · Lists and tuples
~15 min
Medium
Detect latency anomalies with z-scores
Statistics · Monitoring and alerting · Time and space complexity
~25 min
Hard
Precision, recall and F1
Model evaluation · Statistics
~25 min
Hard
Simulate the Horizontal Pod Autoscaler
Kubernetes · Simulation and state machines · Monitoring and alerting
~45 min
Expert
Weighted fair-share job scheduler
Heaps · Simulation and state machines
~60 min
Expert