Upload train.json
Browse files- train.json +170 -0
train.json
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| 1 |
+
[
|
| 2 |
+
{
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| 3 |
+
"prompt": "How would you design a URL shortener like bit.ly?",
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| 4 |
+
"completion": "Type: System Design\nSteps: Clarify scale β High-level components β Deep dive β Bottlenecks β Tradeoffs"
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| 5 |
+
},
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| 6 |
+
{
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| 7 |
+
"prompt": "Design a rate limiter for a public API.",
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| 8 |
+
"completion": "Type: System Design\nSteps: Clarify scale β High-level components β Deep dive β Bottlenecks β Tradeoffs"
|
| 9 |
+
},
|
| 10 |
+
{
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| 11 |
+
"prompt": "How would you architect a notification system for a banking app?",
|
| 12 |
+
"completion": "Type: System Design\nSteps: Clarify scale β High-level components β Deep dive β Bottlenecks β Tradeoffs"
|
| 13 |
+
},
|
| 14 |
+
{
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| 15 |
+
"prompt": "Design a distributed cache like Redis.",
|
| 16 |
+
"completion": "Type: System Design\nSteps: Clarify scale β High-level components β Deep dive β Bottlenecks β Tradeoffs"
|
| 17 |
+
},
|
| 18 |
+
{
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| 19 |
+
"prompt": "How would you build a real-time leaderboard for a gaming platform?",
|
| 20 |
+
"completion": "Type: System Design\nSteps: Clarify scale β High-level components β Deep dive β Bottlenecks β Tradeoffs"
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| 21 |
+
},
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| 22 |
+
{
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| 23 |
+
"prompt": "Design a search autocomplete system.",
|
| 24 |
+
"completion": "Type: System Design\nSteps: Clarify scale β High-level components β Deep dive β Bottlenecks β Tradeoffs"
|
| 25 |
+
},
|
| 26 |
+
{
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| 27 |
+
"prompt": "How would you design a ride-sharing service like Uber?",
|
| 28 |
+
"completion": "Type: System Design\nSteps: Clarify scale β High-level components β Deep dive β Bottlenecks β Tradeoffs"
|
| 29 |
+
},
|
| 30 |
+
{
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| 31 |
+
"prompt": "How would you design Spotify for rural areas with poor connectivity?",
|
| 32 |
+
"completion": "Type: Product Design\nSteps: Clarify scope β Identify users β Map pain points β Propose solution β Define metrics"
|
| 33 |
+
},
|
| 34 |
+
{
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| 35 |
+
"prompt": "How would you improve the onboarding experience for a fintech app?",
|
| 36 |
+
"completion": "Type: Product Design\nSteps: Clarify scope β Identify users β Map pain points β Propose solution β Define metrics"
|
| 37 |
+
},
|
| 38 |
+
{
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| 39 |
+
"prompt": "Design a feature to help elderly users navigate a mobile banking app.",
|
| 40 |
+
"completion": "Type: Product Design\nSteps: Clarify scope β Identify users β Map pain points β Propose solution β Define metrics"
|
| 41 |
+
},
|
| 42 |
+
{
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| 43 |
+
"prompt": "How would you design YouTube for blind users?",
|
| 44 |
+
"completion": "Type: Product Design\nSteps: Clarify scope β Identify users β Map pain points β Propose solution β Define metrics"
|
| 45 |
+
},
|
| 46 |
+
{
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| 47 |
+
"prompt": "How would you redesign the checkout flow for an e-commerce app?",
|
| 48 |
+
"completion": "Type: Product Design\nSteps: Clarify scope β Identify users β Map pain points β Propose solution β Define metrics"
|
| 49 |
+
},
|
| 50 |
+
{
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| 51 |
+
"prompt": "Design a feature to reduce churn in a subscription app.",
|
| 52 |
+
"completion": "Type: Product Design\nSteps: Clarify scope β Identify users β Map pain points β Propose solution β Define metrics"
|
| 53 |
+
},
|
| 54 |
+
{
|
| 55 |
+
"prompt": "How would you design Airbnb for pets?",
|
| 56 |
+
"completion": "Type: Product Design\nSteps: Clarify scope β Identify users β Map pain points β Propose solution β Define metrics"
|
| 57 |
+
},
|
| 58 |
+
{
|
| 59 |
+
"prompt": "How would you handle class imbalance in a fraud detection model?",
|
| 60 |
+
"completion": "Type: Data Science\nSteps: Check base rate β Choose right metric β Handle imbalance β Tune threshold β Evaluate"
|
| 61 |
+
},
|
| 62 |
+
{
|
| 63 |
+
"prompt": "How would you detect anomalies in a time series dataset?",
|
| 64 |
+
"completion": "Type: Data Science\nSteps: Define anomaly β Explore data β Choose method β Evaluate β Production concerns"
|
| 65 |
+
},
|
| 66 |
+
{
|
| 67 |
+
"prompt": "Walk me through building a churn prediction model.",
|
| 68 |
+
"completion": "Type: Data Science\nSteps: Define churn β Feature engineering β Baseline model β Iterate β Deploy"
|
| 69 |
+
},
|
| 70 |
+
{
|
| 71 |
+
"prompt": "How would you evaluate a recommender system?",
|
| 72 |
+
"completion": "Type: Data Science\nSteps: Define metric β Offline eval β A/B test β Business impact β Monitor"
|
| 73 |
+
},
|
| 74 |
+
{
|
| 75 |
+
"prompt": "How would you approach a dataset with 40% missing values?",
|
| 76 |
+
"completion": "Type: Data Science\nSteps: Understand missingness β Explore patterns β Imputation strategy β Validate β Document"
|
| 77 |
+
},
|
| 78 |
+
{
|
| 79 |
+
"prompt": "How would you build a model to predict customer lifetime value?",
|
| 80 |
+
"completion": "Type: Data Science\nSteps: Define CLV β Feature engineering β Baseline model β Iterate β Deploy"
|
| 81 |
+
},
|
| 82 |
+
{
|
| 83 |
+
"prompt": "How would you select features for a high-dimensional dataset?",
|
| 84 |
+
"completion": "Type: Data Science\nSteps: Understand data β Correlation analysis β Feature importance β Dimensionality reduction β Validate"
|
| 85 |
+
},
|
| 86 |
+
{
|
| 87 |
+
"prompt": "How would you build a RAG pipeline for a customer support chatbot?",
|
| 88 |
+
"completion": "Type: AI Engineering\nSteps: Define retrieval scope β Chunking strategy β Embedding model β Retrieval + rerank β Evaluate"
|
| 89 |
+
},
|
| 90 |
+
{
|
| 91 |
+
"prompt": "How would you reduce hallucinations in an LLM-based application?",
|
| 92 |
+
"completion": "Type: AI Engineering\nSteps: Identify sources β Grounding strategy β Prompt engineering β Evaluation β Monitoring"
|
| 93 |
+
},
|
| 94 |
+
{
|
| 95 |
+
"prompt": "How would you fine-tune an LLM for a specific domain?",
|
| 96 |
+
"completion": "Type: AI Engineering\nSteps: Define task β Curate data β Choose method β Train β Evaluate β Deploy"
|
| 97 |
+
},
|
| 98 |
+
{
|
| 99 |
+
"prompt": "How would you evaluate the quality of a RAG system?",
|
| 100 |
+
"completion": "Type: AI Engineering\nSteps: Define metrics β Retrieval eval β Generation eval β End-to-end eval β Monitor drift"
|
| 101 |
+
},
|
| 102 |
+
{
|
| 103 |
+
"prompt": "How would you deploy an LLM with sub-100ms latency requirements?",
|
| 104 |
+
"completion": "Type: AI Engineering\nSteps: Clarify latency budget β Quantisation β Runtime choice β Caching β Load test"
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"prompt": "How would you implement guardrails for an LLM in production?",
|
| 108 |
+
"completion": "Type: AI Engineering\nSteps: Define risks β Input filtering β Output validation β Monitoring β Escalation"
|
| 109 |
+
},
|
| 110 |
+
{
|
| 111 |
+
"prompt": "How would you handle prompt injection attacks in an LLM app?",
|
| 112 |
+
"completion": "Type: AI Engineering\nSteps: Define threat model β Input sanitisation β Prompt hardening β Detection β Response"
|
| 113 |
+
},
|
| 114 |
+
{
|
| 115 |
+
"prompt": "Tell me about a time you disagreed with your manager.",
|
| 116 |
+
"completion": "Type: Behavioural\nSteps: Situation β Task β Action β Result β Reflection"
|
| 117 |
+
},
|
| 118 |
+
{
|
| 119 |
+
"prompt": "Give me an example of when you had to deliver under a tight deadline.",
|
| 120 |
+
"completion": "Type: Behavioural\nSteps: Situation β Task β Action β Result β Reflection"
|
| 121 |
+
},
|
| 122 |
+
{
|
| 123 |
+
"prompt": "Describe a time you failed and what you learned from it.",
|
| 124 |
+
"completion": "Type: Behavioural\nSteps: Situation β Task β Action β Result β Reflection"
|
| 125 |
+
},
|
| 126 |
+
{
|
| 127 |
+
"prompt": "Tell me about a time you had to influence without authority.",
|
| 128 |
+
"completion": "Type: Behavioural\nSteps: Situation β Task β Action β Result β Reflection"
|
| 129 |
+
},
|
| 130 |
+
{
|
| 131 |
+
"prompt": "Give an example of a time you handled ambiguity well.",
|
| 132 |
+
"completion": "Type: Behavioural\nSteps: Situation β Task β Action β Result β Reflection"
|
| 133 |
+
},
|
| 134 |
+
{
|
| 135 |
+
"prompt": "Tell me about a time you took ownership of a failing project.",
|
| 136 |
+
"completion": "Type: Behavioural\nSteps: Situation β Task β Action β Result β Reflection"
|
| 137 |
+
},
|
| 138 |
+
{
|
| 139 |
+
"prompt": "Describe a situation where you had to learn something quickly.",
|
| 140 |
+
"completion": "Type: Behavioural\nSteps: Situation β Task β Action β Result β Reflection"
|
| 141 |
+
},
|
| 142 |
+
{
|
| 143 |
+
"prompt": "How many piano tuners are there in London?",
|
| 144 |
+
"completion": "Type: Estimation\nSteps: Clarify β Decompose β Anchor number β Calculate β Sanity check"
|
| 145 |
+
},
|
| 146 |
+
{
|
| 147 |
+
"prompt": "How many WhatsApp messages are sent per day globally?",
|
| 148 |
+
"completion": "Type: Estimation\nSteps: Clarify β Decompose β Anchor number β Calculate β Sanity check"
|
| 149 |
+
},
|
| 150 |
+
{
|
| 151 |
+
"prompt": "Estimate the storage required for all photos on Instagram.",
|
| 152 |
+
"completion": "Type: Estimation\nSteps: Clarify β Decompose β Anchor number β Calculate β Sanity check"
|
| 153 |
+
},
|
| 154 |
+
{
|
| 155 |
+
"prompt": "How many Ubers are active in London at 9am on a Monday?",
|
| 156 |
+
"completion": "Type: Estimation\nSteps: Clarify β Decompose β Anchor number β Calculate β Sanity check"
|
| 157 |
+
},
|
| 158 |
+
{
|
| 159 |
+
"prompt": "How much revenue does a McDonald's in central London make per year?",
|
| 160 |
+
"completion": "Type: Estimation\nSteps: Clarify β Decompose β Anchor number β Calculate β Sanity check"
|
| 161 |
+
},
|
| 162 |
+
{
|
| 163 |
+
"prompt": "How many golf balls fit in a Boeing 747?",
|
| 164 |
+
"completion": "Type: Estimation\nSteps: Clarify β Decompose β Anchor number β Calculate β Sanity check"
|
| 165 |
+
},
|
| 166 |
+
{
|
| 167 |
+
"prompt": "Estimate the number of software developers in the world.",
|
| 168 |
+
"completion": "Type: Estimation\nSteps: Clarify β Decompose β Anchor number β Calculate β Sanity check"
|
| 169 |
+
}
|
| 170 |
+
]
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