THE PROJECTS

14 deliverables.
Every one earns its keep.

Each chapter that ships a project teaches one concrete skill. Three difficulty tiers each — Normal, Medium, Hard — so you can take the work as far as you want. The capstone is the final.

Week 1 · Reading

Read Like a Scientist

"What does it mean to search a matter out?"

The scientific method; basic vs applied research; research vs development; what makes work publishable; the kinds of computer-science research — and reading three recent conference papers to see the shape of the thing→

Week 2 · Problem-finding

Research Opportunity Report

"Is there truly nothing new under the sun?"

Gap analysis; industry- vs academic-driven research; turning an observation into a research question; three candidate areas and ten candidate questions→

Week 3 · Lit search

Annotated Bibliography (20+ sources)

"Why must we remember the generations before us?"

Google Scholar, the ACM Digital Library, IEEE Xplore, arXiv, Semantic Scholar, Connected Papers; building and managing a bibliography in Zotero; forward/backward citation chasing→

Week 4 · Synthesis

Literature Review Draft

"What does it mean to weigh many witnesses?"

Reading papers efficiently; extracting methodologies and datasets; identifying trends and limitations; building a comparison matrix that surfaces the gap your work will fill→

Week 5 · AI methods

Domain-Specific AI Integration Proposal

"How does a wise mind choose the right method?"

Modern LLMs, agents, retrieval-augmented generation, fine-tuning, computer vision, reinforcement learning, and multimodal AI; matching an AI method to a domain problem in security, software engineering, databases, networking, and more→

Week 6 · Hypotheses

Question, Hypothesis, and Variables

"What does it mean to make a claim you could be wrong about?"

Formulating a falsifiable hypothesis; independent and dependent variables; controls; threats to validity (internal, external, construct, conclusion)→

Week 7 · Design

Experimental Design Document

"Why must another be able to walk the same path?"

Benchmarks, baselines, control groups, ablations, and reproducibility; train/validation/test discipline; the design that another researcher could rerun and confirm→

Week 8 · Proposal

Proposal Presentation + Revised Proposal (MIDTERM)

"How does iron sharpen iron?"

Assembling problem, literature review, methodology, and expected outcomes into a 10-15 minute proposal talk; the peer-review session; revising under critique; plus the cumulative midterm on research methods→

Week 9 · Infra · Git

Reproducible Experiment Setup

"What is built so others can build on it?"

Data collection and tool selection; reproducibility from the start; Git and version control; environment pinning, seeds, dataset documentation, and the research portfolio→

Week 10 · Pilot

Pilot Results Report

"Why not despise the day of small things?"

A debugging methodology for experiments; validating your assumptions before you scale; sanity-checking metrics; measuring performance on a small run→

Week 11 · Execution

Raw Results Dataset

"What does it mean to bear true witness to your data?"

Running the primary experiments; collecting performance metrics, statistical results, and observations; recording faithfully what you saw, not what you hoped, with provenance for every number→

Week 12 · Stats · Python

Results Section Draft

"What does a just weight and a false balance have to do with statistics?"

Statistical significance and effect size; confidence intervals and multiple-comparison correction; visualization; error analysis; Python/Jupyter and R — and the discipline of an honest measure→

Week 13 · Discussion

Discussion Section

"What does it mean to test everything and hold fast what is good?"

Comparing your findings against prior work; explaining what you found; handling unexpected outcomes honestly; the line between what the data supports and what you wish it said→

Week 16 · Symposium

Final Paper, Talk, and Publication Roadmap (FINAL)

"For whom, in the end, do we do the work?"

A conference-style presentation; the finished conference-style paper; and a concrete publication roadmap — choosing a venue (workshop, conference, or journal), reading its call for papers, and mapping the path from draft to submission→