verified_user
Target Output
Weekly Production Deliverable
Deliverable: Modern Java (Optional, Records,
var, sealed classes, pattern matching) done. Two closed-out Kaggle competitions. DDIA Ch. 1–4 done. Production observability live.Monday
0 / 2 done
DSA
Optional
using it properly (never calling
.get() blindly), map, flatMap, orElseGet, avoiding "Optional anti-patterns"
1.5h
AI/ML
Kaggle Refinement
Cross-validation tuning, hyperparameter search, error analysis on validation predictions
2.5h
Tuesday
0 / 2 done
DSA
Records (Java 16+)
replacing boilerplate DTOs/value objects, canonical & compact constructors, record patterns
1.5h
CORE
DDIA Part 1: Foundations
Designing Data-Intensive Applications (Kleppmann) Ch. 1: Reliable, Scalable, Maintainable Applications & Ch. 2: Data Models (Relational vs Document vs Graph)
2.5h
Wednesday
0 / 2 done
DSA
var for local type inference
where it improves readability vs where it obscures types
1.5h
AI/ML
Kaggle Model Blending
Train complementary models; blend predictions using weighted averaging or stacking
2.5h
Thursday
0 / 2 done
DSA
Sealed classes + pattern matching for
switch (Java 21)
modeling closed algebraic hierarchies
1.5h
CORE
DDIA Part 1: Storage & Evolution
DDIA Ch. 3: Storage and Retrieval (LSM-Trees vs B-Trees, SSTables, Bloom filters) & Ch. 4: Encoding and Evolution (Schema evolution, Protobuf, Avro)
2.5h
Friday
0 / 2 done
DSA
Refactor Phase 7 backend's DTOs into Java Records
1.5h
AI/ML
Kaggle Competition Closeout
Submit final predictions; read top solutions; write reflection on model choices (Two closed Kaggle competitions on profile!)
2.5h
⚡
Weekend High-Load Execution
• 8.0h Daily Deep Focus Lab
Saturday
0 / 3 done
DSA
Contest + revise Modern Java features
1.5h
AI/ML
MLOps & Model Monitoring Lab (4.0h)
Set up MLflow for experiment tracking; log hyperparameters, metrics, and model artifacts.
4.0h
JAVA
Structured Logging with SLF4J & Logback
SLF4J + Logback: Structured JSON logging, log levels (INFO/WARN/ERROR), masking secrets and PII; trace requests through layers
2.5h
Sunday
0 / 3 done
DSA
Full revision
modern Java features self-test
1.5h
AI/ML
Data Drift & Concept Drift Detection (4.0h)
Implement Evidently AI or custom statistical drift tests (KS-test, PSI) on incoming inference data.
4.0h
JAVA
Production Metrics with Actuator & Micrometer
Spring Boot Actuator endpoints (
/health, /metrics), custom Health Indicators, Micrometer metrics collection; push observable backend to GitHub
2.5h
edit_note
Week 37 Technical Notes & Journal
#LeetCode
#Java
#DSA
#Week37