Course Logistics and Policies
Prerequisites & Course Focus
Required Skills
You must be able to read Python code in Colabs
- Python comprehension for data processing
- Jupyter/Colab notebook familiarity
- Basic programming logic understanding
Soft Prerequisites
CS161 and CS111 recommended
Sample refresher materials:
- RAM (1st 2 sections) - Memory management concepts
- Filesystems and OS - Operating system basics
- Merge-sort in RAM - Sorting algorithms
- Complexity - Algorithmic analysis
Scale Focus
100-1000x bigger data problems
- Beyond single-machine limits
- Distributed system challenges
- Performance at TB/PB scale
- Real production workloads
Course Philosophy
Full Data Stack
Not a SQL-only class
- SQL skills
- System design principles
- Performance optimization
- Build your own database
For a SQL-only class, look for the MSE or Data Science class offerings.
How to Build Systems
66% on system internals
- How databases work internally
- Query optimization strategies
- Storage and indexing
- Distributed execution
Data Interview Preparation
Industry-scale problems
- BigQuery at scale
- Experiment with LLMs as co-pilot
- Cost optimization
- Real GBs of datasets
Exam & Attendance Policies
Exam Conflict Policy
No alternate exam schedules will be accommodated
- Applies to both midterm and final exams
- OAE accommodations: Same day, extended hours only
- Check for conflicts before enrolling in CS145
Guest Lectures
Mandatory attendance requirement
- Must attend 3 of 4 guest lectures
- In-class short quiz for verification
- See schedule for specific dates
- Not required for SCPD students
Class Size Note
Large enrollment class
- Strict policies due to scale
- Plan ahead for all requirements
- Check Ed for announcements
- No individual exceptions
Grading Breakdown
| Component | Weight | Details |
|---|---|---|
| Exam #2 (Final) | 30% | Comprehensive, focus on systems |
| Project 2 | 25% | Build database system or advanced SQL |
| Exam #1 (Midterm) | 20% | SQL fundamentals on paper |
| PSETs | 12% | Weekly problem sets |
| Project 1 | 10% | BigQuery SQL project |
| Guest Lectures | 3% | Attend 3 of 4 lectures |
Extra Credit Opportunity
Up to 2% at teaching team discretion for insightful in-class and Ed participation. See Gradescope - Extra credit for detailed instructions.